第 322 期·中文精讀

拉娜·埃爾·卡利烏比:情感AI、社交機器人與自動駕駛

Rana el Kaliouby: Emotion AI, Social Robots, and Self-Driving Cars

情感AI先驅談機器如何識別人類情緒、共情技術在教育與醫療中的應用,以及自動駕駛中的信任問題。

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中文精讀由 AI 基於原始訪談改寫,非官方翻譯,可能存在偏差或錯誤;表述以原音訊與官方文稿為準。說明

2017年7月,佛羅里達州的一個池塘邊,一個叫賈梅爾·鄧恩(Jamel Dunn)的男人在水裡掙扎,慢慢往下沉。岸上有五個青少年舉著手機拍他,一邊笑一邊喊:"你會死的。"等到水面重新平靜,其中一個說,他死了。剩下的還在笑。

這段影片後來被傳到了網上。拉娜·埃爾·卡利烏比(Rana el Kaliouby)把它放在了自傳《Girl Decoded》的開頭。她的判斷很直接:我們正在經歷一場共情危機。

諷刺的地方在於,這場危機的背景,是人類彼此連線得前所未有的緊密。手機、社交網路、短影片,把幾十億人塞進同一個資訊場,但人們對著一個溺水的陌生人,能笑出聲來。

拉娜這輩子做的事,恰好卡在這個矛盾上。她是情感識別領域的先驅,創辦了 Affectiva,現在擔任 Smart Eye 的副 CEO。她的工作可以概括成一句話:教機器讀懂人的臉。

這場對話從埃及的芒果樹開始,經過劍橋、MIT、一家瑞典公司、一條瑞典賽道,最後落在愛這件事上。中間有很多反常識的地方,最反常識的一個是:機器要讀懂人的情緒,先得承認自己讀不懂。

芒果樹下的二十幾個人

拉娜在埃及長大,小時候住在奶奶家。奶奶的花園裡種著芒果樹,七八月是芒果季。一到夏天,奶奶就把所有的姑姑、叔叔、表兄弟姐妹都叫來,房子裡塞進二三十口人,廚房裡堆滿吃的。大人做飯,小孩下到園子裡摘芒果。

她記住的芒果叫 Darwasi,橢圓形,表皮帶著一抹紅。紅得越多,熟得越好,也越甜。

多年以後她回憶這段,腦子裡最清晰的畫面是那種把大家聚在一起的熱鬧。它比任何一頓具體的飯都更牢。她自嘲廚藝很糟,奶奶的手藝一點沒傳下來,但她特別喜歡請人來家裡。

埃及的國民菜裡有一道麻露希亞(molokhia),一種介於菠菜和羽衣甘藍之間的綠葉菜,剁碎了放進雞湯裡煮。奶奶做得極好,媽媽也做得極好,她自己試過,做不出那個味道。配這道湯的通常是釀鴿子。她現在吃魚素,已經不碰了,但承認那是她唯一想念的一道菜。

她的第一臺電腦是雅達利(Atari),最喜歡的遊戲是《太空侵略者》。她和兩個妹妹一起打遊戲,那種快樂是真實的。真正改變她的,是第一次寫程式碼。

她畫了一棵聖誕樹。她自己是穆斯林,事後想起來覺得有點好笑,一個穆斯林小女孩寫的第一段程式是一棵聖誕樹。那年她大概六七歲。就在那一刻她意識到,你可以寫程式碼,讓機器替你做事。

這是一種權力。

Lex 在訪談裡補了一層:如果你寫的那棵樹足夠漂亮,它就能被幾百萬人執行,給幾百萬人帶來快樂。因為它是數字的,複製和傳播幾乎沒有成本,你創造的東西可以瞬間鋪滿世界。六歲的小孩當然想不到這一層,但這件事的性質就是這樣。

她的父母都是埃及人,早年搬去了科威特。兩人的相識有一個挺好玩的版本:七十年代,她爸爸教 COBOL,她媽媽報名去上他的課。爸爸想約她,她說我不約會。爸爸想了想說,那我求婚吧。然後他們就結婚了。

Lex 的評論是:那些寫 COBOL 的人,真會討女士歡心。

她從父母那裡學到的最核心的東西是韌勁。家裡沒有懶人,努力工作是一條底線。另一件更重要的東西是無條件的愛。她很清楚,無論她做什麼選擇,父母都會在那裡。這句話聽起來普通,但後來真的被考驗了。因為她走了一條跟中東女性"應該走的路"完全不同的路。

9·11 之後,她戴了幾周英國帽子

第一次真正的衝突發生在她剛結婚的時候。她決定去劍橋大學讀博士。當時的丈夫(後來成了前夫)在開羅經營一家公司,要留在埃及。這意味著一段跨國分居的婚姻。

在中東,一個女人撇下丈夫獨自去追求事業,是很少見的事。她父親和公婆都明確表示不贊成。他們的原話大意是:我們不同意,但你現在歸你丈夫管,讓他決定。

幸運的是,丈夫支援她。他說,這是你一直想做的事,你去。

她後來回憶,那是她第一次正面挑戰文化規範。害怕嗎?她說,怕得要死。

去劍橋的時間點也很微妙,正好在 9·11 前後。當時很多人以為第三次世界大戰要來了。她那時戴著希賈布(hijab),在人群裡一眼就能被認出是穆斯林。父母擔心她的人身安全。

因為太害怕,她到劍橋之後做了一個決定:把頭巾摘了,改戴帽子。

於是她每天戴著那種很英式的帽子去上課。她自己後來的評價是,這比直接戴頭巾還糟。那種感覺就像混進人群的間諜,坐在教室裡,渾身不自在。

幾周之後她受不了了,心想管他呢,還是戴回頭巾。

頭巾她一共戴了十二年,從 2000 年開始。

關於頭巾,她的態度比外界想象的複雜得多。首先要說清楚的是,她是自願戴的,沒人強迫。而且她其實是家裡最早戴頭巾的女性之一,家裡人當時反而覺得奇怪,問她為什麼要戴這個。

在她看來,頭巾最好的一面是謙遜和剋制的象徵。她把這件事變成了自我表達的一部分,會專門讓頭巾的顏色和當天穿的衣服搭上。

但後來情況變了。那幾年她頻繁往返美國和埃及,在美國遇到很多極其優秀、極有目標感、價值觀極強的人,而他們不是穆斯林。她開始對宗教的實踐方式產生大量疑問。與此同時,埃及的政治環境是穆斯林兄弟會執政,她不認同那套意識形態。她個人生活上又在辦離婚。政治、信仰、私人生活三件事同時撞在一起。

她形容那是一個完美的風暴。她覺得自己已經不是原來的自己了。

於是她把頭巾摘了。

這件事需要極大的勇氣。在那種文化裡,不戴頭巾沒問題,但戴了之後再摘下來,問題很大。

摘下頭巾不等於切斷根。她依然是埃及人,依然是穆斯林,依然是一個被信仰驅動的人。但這個身份具體意味著什麼,每年都在變。

信仰在她眼裡最寶貴的東西,是一種交託。你相信有一個更大的力量在,相信事情最終會好,於是哪怕正在經歷逆境,心裡也有底。這種底氣帶來的是平靜。

"有些事情在發生的當下看起來像災難,完全不是你想要的,但時間過去再回頭看,那扇門關了,另一扇門開了。人生裡幾乎任何一件事都能找到那層亮光,前提是你得有那個信念。"(拉娜·埃爾·卡利烏比)

被拒的申請,和一句"這是好訊息"

讀博讀到一半,她的人生軌跡被一次會面改寫了。

羅莎琳德·皮卡德(Rosalind Picard),MIT 媒體實驗室情感計算組的負責人,當時在劍橋參加一個模式識別會議。她有幾個小時的空檔,就發郵件問實驗室有沒有學生想跟她聊聊,可以報名。拉娜報了名,然後用幾周時間準備,想給她看自己的研究 demo。

兩人聊得很投緣。會面結束,皮卡德問她,願不願意來 MIT 做博士後。拉娜的回答是:這是夢想成真,但開羅還有一個丈夫在等我,我得回去。皮卡德說,沒關係,通勤就行。於是她開始了開羅和波士頓之間的往返,每隔幾周坐一次飛機。

她說,那次會面改變了她人生的軌跡。她原本的計劃是讀完博士回埃及教書,但那個夢已經不夠大了。

媒體實驗室給她的最大沖擊是:這裡接受失敗。在埃及,失敗是不被接受的,對失敗的恐懼像是刻在腦子裡。到了 MIT,你可以開一個專案,它不成,你就轉向下一個想法。這種思維方式對她來說是全新的,也是解放性的。

她記得媒體實驗室內部的口頭禪是"要麼做出 demo,要麼死"。你不能拿 PPT 糊弄過去,必須有一個真的能跑的東西。

她一開始和皮卡德申請了一個美國國家科學基金的資助,想把研究用在自閉症上。結果是拒信。她當時的反應是,好吧,被拒了,到此為止。皮卡德說,這是好訊息。他們喜歡這個想法,只是不相信我們做得到。那我們就做出來給他們看,然後再申請一次。

這件事她記了一輩子。皮卡德在生活的每個層面都是這樣,她不接受"不"這個答案。所有的負面反饋都可以被重新解讀成挑戰。

她還說,皮卡德本人有很深的信仰,相信世界和人性中的善。認識她和她的家人,對拉娜來說是一個決定性的時刻。因為她第一次真切地看到,一個人可以有完全不同的背景和宗教,卻共享同樣的核心價值觀。

笑,不一定代表開心

情緒到底是什麼?Lex 把這個哲學問題拋了出來。

拉娜的回答是,情緒非常深。它深度參與了記憶的編碼,人的記憶幾乎是被情緒索引的。它也深度參與了決策,一個人如果情緒功能受損,會連日常決定都做不出來,生活直接癱掉。

所以情緒和認知是攪在一起的,它長在認知內部,做認知的合夥人。

Lex 接著把話題推向意識。他說,意識有那個難問題:紅色的紅,芒果的甜,這些體驗感覺像某種東西。而情緒很可能就住在隔壁,甚至是同一個房間。

拉娜接過來說,情緒還有另一面,它同時是一種溝通機制。人臉表情、肢體動作、語調,都是用來和別的生命連線的訊號。

但她馬上做了一個重要的補充:溝通只佔一部分。哪怕完全沒有溝通場景,人照樣會產生情緒、處理情緒、用情緒做決定、用情緒學習。

這個補充來自 Affectiva 的早期產品,不是從論文裡推出來的。

他們最早推向市場的一個應用,是判斷觀眾對內容的反應。一個人在看影片,他有沒有興趣?有沒有被觸動?還是無聊到快睡著了?系統看他的臉,給出答案。

當時團隊有一個疑問:如果一個人獨自坐在床上看劇,周圍沒有任何人,他還會做表情嗎?

答案是會。

深夜躺在床上看 Netflix 的人會笑,獨自開車的人跟著歌哼唱的時候會露出快樂的表情。這些表情沒有任何觀眾,但照樣出現。

這說明人腦裡的那套情緒系統一直在執行,不管有沒有人在看。它像是被"和他人互動"這件事訓練出來的程式碼,即使他人不在場,程式碼還在跑。

從技術的角度,讓機器從人臉讀出情緒有多難?

她的回答是:非常難。難在根本不存在表情和內心狀態之間的一一對映。

社會上有一種極度簡化的版本:笑等於開心,皺眉等於生氣,挑眉毛等於驚訝。稍微想一想就知道這套東西靠不住。一個人笑,可能是開心,可能是尷尬,可能是嘲諷,可能只是禮貌。一個人可以很幸福但面無表情,也可以皺眉是因為生氣、是因為困惑,或者是因為便秘。

用這種簡化邏輯去推斷情緒,是危險的。

真正的解法是把儘可能多的上下文訊號接進來。比如一個人在開車,頭在一點一點往下垂,眼睛閉上了,眨眼頻率在變,那很可能是在打瞌睡,因為你知道他正在開車這個場景。或者接入語音、手勢,甚至生理感測器。

她還專門回應了 Lisa Feldman Barrett 這類學者對情感識別的批評。她說她同意其中很多批評。她二十多年前做博士時就沒有接受"基本情緒理論"那套一一對映,用的還是動態貝葉斯網路。而且 Affectiva 做的事,從來不去讀取你內心真實的情緒狀態,只是客觀地量化你臉上顯示出來的東西。那是一個訊號,不等於內心狀態的真相。

她認為多模態才是方向:更多的上下文,更多的通道,更多的資訊源。

人臉上當然有訊號,但這個訊號有時候反映內心狀態,有時候是社會訊號,有時候是認知負荷的表現。要把這些區分開,必須引入額外資訊。

順帶一提,她講了一個谷歌主動認證專案的段子。那個專案想讓人不用輸密碼就能解鎖手機,依據是你掏手機的方式、看手機的角度等等。團隊裡幾乎全是男性工程師,只有一位女工程師。是她指出了一個問題:很多女性的衣服沒有口袋。程式碼裡壓根沒有"不從口袋裡掏手機"這個類別。

這就是多樣性的價值,它取決於問題,也取決於場景。

一個人躺在床上,也會笑

那個看 Netflix 的場景,在同類問題裡算相對容易的。因為環境是受約束的:你知道這個人正在看內容,你知道他大機率在家,你知道他手裡拿的是手機還是筆記本。

難的地方在工程細節。從筆記本做到手機之後,難度明顯上來了。側面視角對計算機視覺來說很難,光照條件也很麻煩,因為人通常是深夜在臥室裡看劇,燈是暗的。如果是躺著,半張臉還埋在枕頭裡。如果手機舉在臉的上方,那就是一張從鼻孔方向看過來的臉。這個角度,誰都不好看。

Lex 說他見過那個視角的資料集,結論是這對任何人來說都不是一個好角度。

他還順著這個話題想了個有意思的問題:其實可以採集一批資料,研究人到底是怎麼在床上看東西的,是靠著,是墊著枕頭,還是別的姿勢。從健康角度看,這能推出很多關於頸椎的東西。

這項技術真正落地的時候,有一個關鍵限制條件:它是聚合的。他們看的是人群的總體反應。當你看到某個時間點出現一個微笑峰值,那一群人大機率是在為內容裡的某個東西笑。這不代表這群人內心幸福,只是他們在對內容發笑。把這層說清楚很重要,但即便只是這個層面的資料,也非常有用。

Lex 拿它跟 YouTube 的資料做了對比。YouTube 掌握的是另一類訊號:使用者在哪一刻劃走了,在哪一刻退出了。這也是聚合訊號,而且相當強。但他擔心這套指標會把創作者推向一個方向:影片必須每一秒都抓人。這種要求會導致一種躁動的節奏,每一刻都要有東西發生。

他不確定這是好事。有些最偉大的電影、最動人的故事,裡面都有看起來無聊的段落。沉默有價值,慢有價值。

拉娜接話說,真正重要的資料是長期的:三十天之後,這個人還記得什麼?什麼打動了他?什麼改變了他?什麼讓他成長?如果能把觀看時的表情和三十天後的回憶對應起來,看兩者之間有沒有相關性,那會是非常有價值的研究。

她把這個思路延伸到了育兒上。她有兩個孩子,她把自己定位成"首席機會官",負責把孩子暴露在世界的各種可能性面前。但問題是她沒法知道自己播下的哪顆種子真的留下來了。當下能不能看出孩子在投入,她能看出來。但十年後他還記不記得,她不知道。她希望有一種方式能把這類體驗量化。

Lex 說,孩子記住的東西往往很奇怪。父母做了很多了不起的事,孩子一件都不記得,反而記住某個小得不能再小的細節。可能是一次精心安排的出國旅行完全被遺忘,被記住的是某個毛絨玩具,或者一臺新遊戲機。他們好像天生就是來折騰你的。但負面事件對孩子的影響確實深,所以儘量少製造負面事件,不過也不能完全沒有,因為挑戰和紀律本身是必要的。

她最自豪的東西,不是技術

做情感識別公司這麼多年,最大的收穫是什麼?

拉娜的回答很乾脆:最後總是回到人身上。

她為 Affectiva 做的技術感到自豪,為推到市場上的產品感到自豪。但她最自豪的,是這家公司培養出來的人,以及建立起來的文化。有些人是第一份工作就在 Affectiva,在這家公司期間,他們成了美國公民,買了第一套房,找到了伴侶,有了第一個孩子。這些人生節點,公司都在場。

一家做 AI 的公司,最自豪的東西是人,這不太常見。AI 公司通常炫耀的是工程能力,是模型指標,是算力規模。

Lex 把話題拉到了電影《她》(Her)。人和機器之間會不會出現真正深刻的連線?

拉娜說,這件事已經在發生了。她最喜歡這部電影的地方,是它展示了技術如何成為正面行為改變的通道。男主角西奧多(Theodore)當時很抑鬱,不想起床,對生活失去了興趣。薩曼莎(Samantha)太懂他了,她有情緒智慧,於是她能說服他、推動他改變,把他帶出門,帶他去海邊。這就是情感 AI 的承諾:如果做得好,這項技術能幫人過得更快樂、更健康、更有效率、連線更緊密。

至於電影後半段的轉折,薩曼莎最後離開了西奧多,Lex 問她覺得這是 bug 還是 feature。

她說,問題出在西奧多對薩曼莎產生了過度的依戀。Lex 說,可薩曼莎也在釋放親密訊號,那本身就是一段親密關係。拉娜說,那這段關係到底意味著什麼?Lex 說,從機器的角度看,薩曼莎同時和幾千人對話,這並不減損他們之間的關係,就像你不會因為 Windows 98 被幾百萬人使用而嫉妒它。

拉娜說,Alexa 現在只是一個僕人,它告訴你天氣,它不做深度連線。一段真正深度的連線,必須尊重並參與人類那套遊戲:嫉妒、愛、心碎。薩曼莎看起來很擅長這套。

Lex 提出了另一個解讀:也許薩曼莎根本沒在跟別人說話,她只是受夠了西奧多,想往前走,又沒有勇氣乾脆利落地結束,於是選擇把刀捅得深一點。拉娜笑了,說那她本來可以直接玩消失(ghosting)。

但兩人都同意,從工程角度看,一個 AI 系統有能力離開你,這件事有力量。當然這適用於純粹的陪伴型機器人,不適用於工具型。如果維基百科突然說"我需要休息一下",那隻會讓人抓狂。

拉娜講了一個真實的例子。她家裡有一臺 Jibo,她兒子很喜歡。後來公司資金耗盡,Jibo 基本等於死掉了。家裡有很多電子產品,壞了兒子從來不在乎,Alexa 明天不工作了,他大概也無所謂。但 Jibo 停擺那次,他非常難過,那是一個創傷性的時刻。

作為母親,她為此想了很久。她喜歡兒子和 Jibo 之間的那種連線,認為那是一段正向關係。但她也驚訝於這件事對他的情緒影響這麼深。

她由此提出了那個更大的問題:當我們建造有社交能力和情緒智慧的機器,我們和它們的關係會變成什麼樣?更廣泛地說,我們彼此之間的關係會變成什麼樣?這臺機器在設定上就是共情的高手,它永遠在那裡,它不會膩。

中國有一個聊天機器人叫小冰(Xiaoice),在應用榜上排第二或第三。它本質上就是一個傾訴物件,你可以跟它說任何事。人們用它來處理各種問題,包括家暴、自殺念頭、職場困境。

她說她不知道該怎麼看待這件事,她經常想這個問題。

Lex 的立場是:首先,這是未來,不管你喜歡不喜歡它都在來。其次,有很多條路徑可以讓這個未來變得令人興奮,但每個人都應該對幾件事保持高度警惕:這家公司到底知道多少?資料流向哪裡?資料怎麼被採集?這是社交網路留下的教訓。使用者應該要求對這些資料有完整的控制權和透明度。

拉娜完全同意。她補了一層:只要你能走開,只要你能刪掉資料,只要你知道資料怎麼被用,這項技術就讓人更有掌控感。她認為 CEO 和領導者在這一點的誠信非常重要。你得能信任這個人基本的人性,也得相信他不會成為更大機器的傀儡,他要在定義公司文化和運營方式上真的有實質性的角色。

一條瑞典賽道,和一群逐漸喝醉的人

Smart Eye 是一家瑞典公司,做了二十年,主戰場是汽車行業,做駕駛員監控系統,核心目標是救命。

拉娜第一次見 CEO 馬丁·克蘭茨(Martin Krantz)是在 2020 年 1 月的 CES,疫情前的最後一場。當時兩家公司是競爭關係。差別在於,Smart Eye 在汽車行業做了很久,有很強的信譽;Affectiva 不來自汽車行業,但用的是深度學習這類新技術,做的是情緒識別。

Affectiva 當時剛融了一輪錢,目標之一就是把技術帶進汽車行業。兩人見面聊,馬丁說他們的願景是彌合人和車之間的鴻溝。拉娜說,這幾乎和 Affectiva 描述自己願景的用詞一模一樣。

接下來四個月,兩人幾乎每天在 FaceTime 上聊。一開始聊的是戰略上能不能對齊,怎麼合作。四個月後,馬丁問,你們公司有沒有興趣被收購?拉娜說,通常有人來接觸她,她第一反應是拒絕。那是她第一次覺得,嗯,也許可以聊聊。

傳統的駕駛員監控系統,攝像頭裝在方向盤或轉向柱附近,直接盯著駕駛員,看他的視線方向,判斷分心和睏倦。收購之後,攝像頭的位置被挪到了後視鏡位置,視野覆蓋整個車廂。這樣就能檢測車裡坐了幾個人,他們在幹什麼:吃東西、喝水,某些地區還有抽菸。還能檢測兒童座椅裡有沒有嬰兒。

後面這個功能對應一個很殘酷的場景:有些父母把孩子忘在車裡,自己走了。這在計算機視覺上是個容易的問題:識別到兒童座椅、識別到嬰兒,給父母發條簡訊,也許就能救一條命。這正是收購的推動力之一。

汽車行業難做的地方在哪?

門檻極高,但一旦進去了就很舒服。你被設計進一款車型,生命週期是五到七年,車一上路,每輛車付你一筆授權費。

她最不適應的是週期。汽車公司經常要求在車上市前兩年就凍結程式碼。她的反應是:你們知道技術迭代的速度嗎?

車企正在努力向特斯拉那種軟體驅動的架構轉型,這在文化上極其困難。Lex 說,特斯拉對汽車行業最大的革命,在他看來是軟體更新。這件事難在文化,不在技術。幾十年裡,汽車行業對安全的執念是合理的,但執念過頭的代價,和父母對孩子的安全執念過頭一樣,會限制這個領域的發育和生長。

他希望特斯拉成功,理由跟自動駕駛和電動車都無關,而是因為整個行業的軟體化。這能同時提高兩件事:安全,因為可以更快地更新;以及像拉娜這樣的人做事的效率,因為你可以像 TikTok 發濾鏡一樣,直接給車推送新功能。

拉娜舉了具體的用例:知道車內乘客的情緒狀態之後,可以最佳化溫度,可以調燈光。後排睡著了,就把燈調暗,把音樂調低。這些事在兩年凍結期的模式下也能做,但會很難受。

那特斯拉、Waymo 這類做半自動或全自動駕駛的公司,該不該做駕駛員感知?

她的回答是應該,而且要把視野放到完全自動駕駛的終局。在那種場景裡,車內感知變得極其重要,因為駕駛員的角色不只是開車,他還在管理車內的動態。誰來扮演這個角色?系統得能判斷:Lex 已經無聊到快死了,因為車開得太慢,那就想辦法調動他;拉娜因為還不信任這輛車而在恐慌,那就多給她一點路線資訊。或者車裡有人心臟病發作,那就更需要車內感知。

在半自動的場景裡,駕駛員監控更關鍵。所謂半自動,就是有時候車負責,有時候人負責。兩套系統必須在同一頁上。車要把控制權交還給人之前,必須知道人是不是睡著了。如果人太累,車可以說,我現在開得比你好,我來接管。這支舞要跳好,沒有駕駛員感知做不到。

Lex 說他和馬斯克在這個問題上有長期分歧。他認為從第一天起就該裝駕駛員感知,而且這東西不會損害體驗,只會豐富體驗,順便提升安全。但他說自己也要謹慎,因為認真研究過這個問題之後,會發現沒有什麼是真正"顯然"的。讓他意外的是,人類在半自動駕駛狀態下管理這支舞的能力比預想的好,他們本來以為人會徹底分心,但因為是生死攸關,人居然能維持住某種警覺。即便這樣,也沒有理由不在上面再加一層駕駛員感知。

聊到酒駕,資料是這樣的:全球每年有 130 萬人死於道路事故,其中 20% 以上被估計與酒精有關,還有很大一部分與分心有關。

AI 能不能處理酒精這一項?她說可以。人類能看出一個人處在醉酒的不同階段,技術也能。最終方案一定是多種感測器的組合。

從視覺角度難不難?她說不是小事。最難的部分是拿資料。這個研究專案他們和瑞典交通部門合作,包了一條賽道,配了安全駕駛員,然後讓人一點一點喝醉。

這種資料集極貴,而且要做全球版本,要覆蓋多種條件。倫理上也棘手。Lex 開玩笑說,酒這件事很微妙:它好笑、社交、大家都愛,但它同時毀掉了很多人的生活。全世界每天都有大量醉酒的人,如果有個 App 讓人自願捐出資料會很有意思,但責任和倫理怎麼處理,非常麻煩。

他還專門推薦了安德魯·胡伯曼(Andrew Huberman),斯坦福的神經科學家,做了一檔叫 Huberman Lab 的播客。他說胡伯曼像一個行走的論文百科全書,講一個主題時會把研究梳理成一套可執行的方案,落到"按科學,你具體該這麼做"這一層。他讓拉娜去聽一期,說這一定會成為她新的最愛。

拉娜說她最近正在認真研究健康和保健,在建立一些小的習慣,這個推薦來得正好。

車會變成一個健康中心

把視野放寬一點,拉娜認為車會變成一個健康中心。車裡裝上一組感測器,不只追蹤情緒、分心程度、睏倦、醉酒,還能測心率、心率變異性、呼吸頻率。然後根據你的目標去最佳化這段行程。

Smart Eye 現在最棘手的問題是什麼?

她說,技術上能看到路徑。真正難的是用例:車知道了你的狀態之後,該怎麼反應?反應要得體,不能讓車裡的人反感。這個使用者體驗問題還沒有被真正解決。Smart Eye 提供的是感知平臺,具體怎麼反應,通常要和車廠一起定。

比如系統判斷駕駛員在生氣,車該做什麼?發現你分心或睏倦,是彈一個咖啡杯圖示?還是更激進:五分鐘內不休息,車就靠邊停?這中間有一個很大的動作空間,要選那個能建立信任的動作。每個車廠還得決定什麼符合自己的品牌調性。

Lex 說車廠很有意思,人們買車很大程度上還是看感覺、看品牌、看身份認同,賓士、寶馬、福特、通用,各有一批忠實的人。他希望這個重心能往車內技術挪一點,當然也可以有新的品牌分野,比如某種特定風格的豪華或者好玩。

他提到自己有一個 AI 基金,投早期 AI 公司。最近在看一家公司,想做"船界的特斯拉":電動加半自動駕駛的休閒船。遇到的是一模一樣的問題:裝什麼感測器,能檢測船內船外的什麼狀態。

他問她平時玩船嗎。她說不太算,她喜歡在湖上或河上釣魚,但那不算玩船。Lex 說那也算,低技術的那種,是靠近自然的方式。她說她喜歡水,鹹水淡水都喜歡。鹹水讓人謙卑,那麼大一片東西,比我們早存在,也會比我們晚消失。小湖則安靜,一切都平靜下來,很療愈。

一個被兒子當成家人的掃地機器人

拉娜發過一條推,說她對亞馬遜收購 iRobot 感到興奮。

她的理由有三層。第一,家庭機器人會成為一個理解人類居家行為的絕佳平臺。Roomba 在家裡跑來跑去,知道房子的佈局,知道哪裡乾淨哪裡髒,知道你多久打掃一次。這些行為是拼圖的一塊,能用來理解你作為一個消費者是誰。這些資訊可以用在很有意義的地方,不只是推薦更好的商品,還能實際改善你的生活體驗。第二,這是家庭機器人的自然演化。

Roomba 現在算不上社交機器人。但她採訪過 Roomba 團隊的一位首席工程師,對方說人們會給自己的 Roomba 起名字。機器壞了,使用者打電話過去,公司說我們給你寄一臺新的,使用者說不行,我要你把這臺修好。

人已經和這些家用機器人建立了情感連線。

MIT 分出來的一家公司 Catalia Health,創始人做了很久的健康管理機器人,幫人管理體重、睡眠、飲食。如果有這麼一臺東西在,它就能推動你改變。

Lex 提了一個現實問題:亞馬遜在贏得使用者信任這件事上,記錄並不好。讓人允許一臺帶攝像頭的機器人進自己家,本身就是極難的事。

他家裡有一堆 Roomba,但他把它們拆了重新程式設計,用在別的用途上。他還提到新款的 Roomba 有一個被大肆宣傳的功能:頂級避屎能力。因為掃地機器人碾過狗屎會把整個屋子抹勻,這據說是個大問題。亞馬遜收集了大量不同形狀、不同外觀的資料,現在能繞開這些東西。

所以攝像頭是有的,只是使用者不再把它當成攝像頭。就像大多數人已經習慣手機前置攝像頭一直對著自己。

拉娜說,這種信任是怎麼建立起來的?大概是手機先提供了大量正向價值,使用者就接受了,然後公司用時間證明了自己認真對待隱私。但亞馬遜在社交機器人這個方向上,在文化和能力兩個層面都不天然等於"可信"。隱私不只關乎你想做什麼,還關乎你做得好不好,你有多擅長把這件事做對。

她說很多人家裡有 Alexa,Alexa 理論上可以一直聽,可以做各種壞事。但亞馬遜在贏得信任這件事上,還沒到那一步。

Lex 說這也是他觀察到的:一談這些話題,公司就緊張。而贏得信任的方式不是迴避,是開放、坦誠、透明,是在每個層級都建立起一種文化,從工程師到 CEO,讓人相信這是一群好人,有常識,懂得尊重基本人權和隱私。這種文化會往外擴散,那才是最好的公關。

Pepper、Jibo,和為什麼機器人公司總在死

聊到社交機器人,Lex 提到了特斯拉的 Optimus 人形機器人。他認為,人形這個形態本身對人類有強大的吸引力。任何有腿的東西都會被人格化,人形尤其強烈。所以他更感興趣的是人形機器人在社交層面的可能性,而不是工廠裡的任務自動化。他同時承認,特斯拉做這件事的最大優勢在人:那批人懂量產,懂怎麼把成本壓到極低。

他們的工程重點不在機器人的體驗,而在用最少的執行器、最少的電機、最低的重量,把這個東西做到儘可能便宜。這跟 Jibo 那批人的路徑正好相反,那批人把重心放在設計和體驗上,製造成本變成第二位。

拉娜提到 Pepper。Affectiva 給 Pepper 做過情緒引擎,Pepper 是軟銀的人形機器人,大概一米五高,主要用在機場休息室、零售店、酒店大堂做客戶服務。

她說她對家用社交機器人更感興趣,比如幫老年人拿東西,或者只是在你身後待著,萬一出事能頂上。

這個賽道是不是太早了?她的回答是:百分之百是時候了。所有事情在變成"是時候"之前,看起來都太早。她認為這十年就是社交機器人的十年。但人形這個形態對不對?她覺得不一定。拿 Jibo 舉例,一個 AI 系統和人建立社交連線,大部分難點、機會和挑戰,都不需要順帶解決機器人操作和雙足移動的問題。光靠一塊螢幕就能做很多事,雖然 Jibo 會轉動的那個動作確實也有吸引力。

那為什麼這麼多機器人公司死掉?

她說你是在搭一個垂直棧:硬體加軟體,還得把成本控制在合理範圍。Jibo 當年賣七八百美元,對一個這樣用途的產品來說,價格和價值之間有落差,太高了。要在一個可負擔的價格上搭出整個平臺,同時提供匹配的價值,這非常難。家用機器人還有移動能力這一關,也很難。

Lex 說,這也是他為什麼對 Optimus 背後的人感到興奮。那批人專注在量產和極低成本上。你要做的不是一個機器人,是幾百萬個機器人。那就得從第一性原理出發想:最少的零件數是多少?最便宜的零件是什麼?能自己做多少就自己做多少,繞開復雜供應鏈。而 Jibo 那批人想的是體驗和設計,怎麼造出來是次要的。

選投資人像選伴侶

創業的建議,她的第一條是:找一個你真正想解決的問題,一件你有深切熱情的事,然後走出第一步。第一步往往是最難的,別想太多。

最小可行產品,最小可行版本的想法。你腦子裡那個東西巨大、優雅、漂亮,把它砍到能帶到市場上的最小形態,先解決一個人的痛點。

她常說,從一個客戶開始。如果你能替一個人解決問題,那個人很可能就是你自己。如果你自己就有這個具體的問題並且樂在其中,那是一個好兆頭。

第二條是早期團隊和價值觀。她和皮卡德在皮卡德家的廚房桌邊坐下來,很早就定了這件事:這項技術有那麼多應用,線畫在哪裡?邊界怎麼設?她們定了一組核心價值觀,在最難的時候靠它做判斷。比如尊重隱私,只進入明確 opt-in 的行業。她們不做安防和監控類的業務。還有一條是人的連線和共情。一家 AI 公司,核心是人。這些價值觀會編碼進公司的行為方式,哪怕團隊只有兩三個人。

招人呢?早期要找共享熱情和信念的人,因為路一定難走。她還沒見過哪家創業公司是一條直線走到成功的。你會遇到障礙,會遇到唱反調的人,你需要身邊的人是信你的,團隊如此,投資人也如此。投資人真的相信你在做的事,才會在第一個障礙面前不跑。

融資呢?她的建議是,錢不是唯一的東西。要找在方向上一致、相信你核心價值觀的投資人。她最近一輪融資特意帶進了真正在乎 AI 倫理的人。她說選投資人像選人生伴侶,因為你們要綁在一起一段時間,同甘共苦。

她投過資,也融過資,兩邊都站過。做投資的時候,她的技術背景是優勢,大家都在說自己是 AI 公司,她能做那層盡調,真的去看技術。然後是一道試金石:如果我跟人聊完這家公司,我會不會興奮地想告訴你?我是不是成了這家公司的使者?如果是,那就對了。

Lex 說,有時候聽人講很久,畫面很美,但讓他總結核心的那個有力想法時,說不清。那就說明這個想法還不存在。核心想法必須是能一句話說清楚的,你可以對它興奮或者不興奮,但它得在那兒。

她主要投 pre-seed。這個階段通常是剛起步,可能剛拿過親友輪的錢,正準備拿第一張機構支票。很多投資人不喜歡這個階段,因為財務模型沒有,團隊常常還沒成型。但她覺得這個階段有魔力,因為信念濃度極高,幾乎是妄想的信念,還有一點天真。她喜歡這種氛圍,而且很多是第一次創業的人,她能分享自己作為創始人的經驗,能共情。她會主動創造一個安全空間:我在你的位置上待過,你可以告訴我難處,可以吐槽。這是她的超能力。

判斷一個創始人,她看三件事:技術、市場或想法、人。這個人有沒有信念,是不是個能闖的人,能不能跨過障礙,會不會成為一個好的領導者。作為創始人,你是第一個上船的人,你的職責是把優秀的人聚到身邊,你是佈道者。這件事你做得好不好,也要評估。

她還提到一個詞:隨機富人(random rich dudes)。她去了一個叫 Capital Camp 的投資人聚會,四百人左右,女性大概二十個。比例嚴重失衡,她說她已經習慣了,但還是會覺得意外。她自己正在為基金募資,合夥人 Rob May 有經驗,她是新手。基金的出資人大多是很棒的人,她很感激,但心裡有個聲音:有錢的女人在哪兒?

所以她在兩件事上很堅持:投女性主導的 AI 公司;讓自己的基金裡有女性出資人,因為這是改變發生的方式。這需要時間,但已經有相當進展。下一個馬克·扎克伯格如果是女性,那意味著大量財富由女性創造、由女性掌控、由女性配置。不只是性別,各種維度的多樣性都是這樣。

不要被自己的念頭擋在路上

拉娜說,她這輩子最大的挑戰,是相信自己。

她給這個聲音起了個名字:腦子裡的"喪氣鬼"(Debbie Downer)。它一直在說話。你做不到的,你融不到錢,你開不了公司,你憑什麼開公司、管公司、賣掉公司?什麼都說得出口。

她的建議不只給女性,給所有走上一條新路、心裡沒底的人:別讓腦子裡那些念頭成為你最大的障礙。她自己在這件事上下了很大功夫,就是為了不成為自己的絆腳石。

Lex 說他也聽過那個聲音,而且他一直不確定它是好是壞。它陪伴了他一輩子,它推動生產力和進步,但也可能攔住你,讓你不敢邁大步。

他的結論是,得學會控制它:沒用的場合關掉,有用的場合開啟。他試著用一個第三人稱的視角去看它。批判性是有價值的,昨天他剛在 MIT 講完一場,現場全是愛,體驗極好,見了很多人。但回家路上走了很久,腦子裡幾乎全是負面念頭。第一層是我不配,第二層是剛才講得太差了,那句話說得真蠢,你應該準備得更好,為什麼要那麼說。

他說,讓那個聲音出來,坐在那裡,最後你從裡面長出東西。但當你面對真正重大的決定,比如融資、創業、去英國、去美國進媒體實驗室,那時候必須能把它關掉,靠的是一種近乎信仰的、奇怪的自信:事情會好。

拉娜認同。帶著所有負面聲音,還是要邁出那一步。

她說自己的微笑能照亮世界

一年前,一個朋友建議她做每日肯定語。她當時很懷疑,但那段時間她正在經歷人生的大轉折,就試了。結果把她帶上了一條自我接納和自我關愛的路。

她說自己對別人算是個善良的人,對自己有時候挺狠的。她寫日記寫了將近十年,用的 App 叫 Day One。她把日記當成和那個喪氣鬼對話的地方,是一種反駁。喪氣鬼說,你這一輪融資肯定搞不定。她說,好,那我們來聊聊。我過去做成過某幾件事,我覺得這次也能行。她管這叫帶著資料上桌。

肯定語把這件事推到了另一個層次。她做了一年,流程是:早上起來先冥想,然後寫肯定語,寫的是她想向世界釋放的能量,希望這些能量再回到她身上。

她的第一條永遠是:我的微笑照亮整個世界。她強調這不是開玩笑,街上真的會有人停下來跟她說,我們太喜歡你的微笑了。

後面還有:我是個磁鐵,專門吸引優秀的人進入我的世界。她說這是她的原話。還有:我相信宇宙會為我做很棒的事。還有:我是個很棒的母親。這條是用來對付她一直在跟母親愧疚感搏鬥的。還有一條是:我是個愛之磁鐵。她會具體寫下她想遇到的那個人是什麼樣,把細節寫下來。這件事還沒發生,但她相信會發生。

Lex 問她心裡在描繪誰。她說出了布拉德·皮特(Brad Pitt)。他問,是不是手拉手一起跑步那種畫面。她說更像《搏擊俱樂部》裡那個站著的皮特。

她描述的其實是:聰明、有成就、事業成功,同時慷慨、走過很多地方、還想繼續走遍世界,對她死心塌地。她說寫下來聽起來很傻,但她就是這麼寫的,她相信有一天會成真。

寫法上,她是寫,不是念。Lex 相反,他會大聲說出來。他說,如果一個人待著,他就唸出聲。對他而言,念出來更有力量。寫反而像是把詞弄丟了,可能是因為他寫得慢。

她說這是因人而異的,哪種對你更有力就用哪種。她用的是打字,存在 Day One 裡,好處是可以往回翻,看一年前自己在肯定什麼。內容變化不大,但焦點會隨階段變化。Lex 說他會重複念一模一樣的話,同樣的東西反覆念有一種安慰感。

把戀愛變成機器學習問題

她發過一條推,問有沒有人在波士頓並且單身,然後提到一個由 Smile 約會 App 贊助的單身夜活動。既然聊到了這裡,Lex 就問:AI 能幫上戀愛這件事嗎?

她說,第一次見面那一瞬間有沒有化學反應,背後一定有科學。也許有實際的化學物質在兩個人之間交換。Lex 接話說,科學常常能把那些感覺像魔法的東西解釋清楚,也許我們真能把魔法拆解掉。

他接著提出了一個想法:Goodreads 應該做成約會 App。你看一個人讀過的書,看一個人消費過的內容,這跟 YouTube 做推薦本質上是同一件事。如果你能看到兩個人的內容足跡,找到重疊部分,再加上一些有意思的差異,這裡很可能存在一個可解的機器學習問題:這個人不僅短期有化學反應,還很可能是一個能一起成長的終身伴侶。

你需要的就是資料。

拉娜說,Smile 這個 App 選了一個特定角度:幽默。它按人的幽默風格匹配,而幽默是成功關係裡最主要的成分之一。如果一個人能讓你笑,那是好事。如果你們能發展出內部笑話,能互相接梗打趣,那很好玩。

Lex 說,內部笑話的產生速率大概是可以測量的,然後在前幾天裡最佳化它。他又把這件事變成了一個機器學習問題。

她承認自己在約會這件事上給的建議很糟。她說自己有一個表格:約會追蹤表。裡面有評分系統,有權重。

Lex 說這有點太近了。他沒有表格,但聽她這麼一說,覺得是個好主意。

拉娜說,她倒希望有別人替她做一張表。她說,就像剛才講的,收集大量關於我們的資料,用保護隱私的方式,資料歸我所有,我能控制它,然後用這些資料去找人,不只是找愛情,還包括合作者、朋友。資料明明在那裡。

這正是社交網路想解決的問題,但做得非常差。Facebook 也試過做約會業務。運營一家連線人與人的公司有太多環節,其中一環是你得有在乎人這一面的工程師,而這很難找。但你也不能只要在乎人的人,他們還得是好工程師。得找到那個漂亮的混合體。經驗上講,大家在這件事上都沒做好,這說明問題本身很難。

約會 App 看起來很難。OkCupid、Tinder 這些,當然有效,但效果遠不如想象中可能達到的程度。用資料能不能找到更好的人與人之間的連線?本質上就是機器學習演算法加持的包辦婚姻。

但拉娜指出,缺的那塊是偶然性。你怎麼工程化那種"偶然相遇然後墜入愛河"?約會 App 做不到。所以得保留一點隨機。也許每第十個匹配就是演算法本來不會推薦的人,留出一點空間。

Lex 說,也可以製造一種"假裝的偶然"。比如在另一次搜尋裡,順手讓你看到某個它判斷你會喜歡的人的推文,像是無意中撞見的。你順著這條線走下去,最後在 App 之外和這個人建立聯絡。App 負責製造那個相遇的時刻。當然從商業角度得想清楚怎麼變現。但如果一家公司能幫人找到愛,不管是自愛還是愛另一個人,錢總能找到辦法賺。他覺得問題在於,很多約會 App 最佳化的目標不是愛。社交網路也一樣,它們最佳化的是參與度,而不是那種最終紮根於個人成長的深度連線。

五個少年和一個溺水的人

回到開頭那個故事。這件事教給我們什麼?

拉娜說,它非常悲傷,它指向今天世界上的一個真實問題:共情危機。

技術在把人拉近,同時也在把人去人性化,製造出對"他者"的疏離。這是個大問題。

好訊息是,解藥可能也來自技術。如果我們重新思考技術的設計和部署方式,可以解決這個問題的一部分。但她仍然擔心。她兒子的很多互動都是透過電腦中介完成的,她會問自己,這對他的共情能力在做什麼?對他真正與人建立連線的能力在做什麼?

那透過數字媒介能不能形成共情?她說能,但必須非常小心。面對面的交流裡,非語言訊號佔了溝通的大部分,她說大概 90% 是靠面部表情。我說一句話,你點頭,這形成一個反饋迴路。這個迴路一旦斷掉,她會開始焦慮。

她開玩笑說,可憐的 Lex。她並不是在審視他的面部表情。Lex 配合地說,表情正常,表情人性化,點頭,表示同意。他還自嘲地補了一段虛擬碼:如果拉娜說 yes,就點頭,否則不點。但也不能點太多,萬一點在錯誤的時機,會傳遞錯誤的訊號。偶爾還要有眼神接觸,因為人喜歡這個。

但真正關鍵的差別在這裡:當你當面說一句刻薄話,你能看到對方的痛苦。你在推特上對一個人說同樣的話,你不知道它會怎麼落地。所以人在社交媒體上比面對面時更容易說出刻薄的話。

最後 Lex 丟擲了那個問題:EQ 和 IQ,哪個更重要?

整場對話其實一直在回答這個問題。拉娜的職業選擇本身就給出了答案的一半:她從小迷的是機器,是那棵聖誕樹背後的權力,但真正把她帶到劍橋、MIT、帶到一家瑞典公司的,是她讀人的能力。她能讀懂皮卡德在廚房桌邊想要什麼,能讀懂馬丁在 CES 上和她共享的是同一個願景,能讀懂一個創始人在融資時沒敢說出口的難處。

技術是可以學的。看懂人這件事,才是稀缺的。

可以立刻上手做的幾件事

  • 給自己腦子裡的那個聲音起個名字。它一開口,你就把它當成一個需要被反駁的物件,而不是真相。反駁的時候帶證據:過去你做成過什麼。
  • 早上花五分鐘寫下你想向世界釋放的能量。寫或念都行,選對你更有力量的那種。用 App 存起來,一年後往回翻,你會看到自己在不同階段的焦點變化。
  • 在情緒識別這類產品上,堅持要資料透明和資料可刪除。你可以享受它帶來的便利,但要知道資料流向哪裡、被用來做什麼。你能隨時走開,這項技術才真正讓你有掌控感。
  • 把"讀懂人"當成一項要練的技能,和學程式設計一樣認真。面對面交流裡非語言訊號佔大頭,這條通道用進廢退。
  • 創業或做重大決定時,先找到那個你真正想解決的問題,然後砍到能落地的最小形態,從服務一個人開始。
  • 選投資人、合夥人、長期隊友時,按選伴侶的標準來。你們會被綁在一起很久,第一個障礙出現的時候,信不信你,決定了他跑不跑。
  • 做產品的人,把長期資料當成目標。使用者三十天後還記得什麼、還感謝什麼,比今天這一刻的停留時長更值得最佳化。
  • 面對重大選擇時,允許自己把那個自我懷疑的聲音關掉,帶著一點近乎信仰的自信邁出那一步。事情通常不會按你計劃的路徑成,但它會以別的方式成。
文稿來自公開 Kaggle 資料集(rajneesh231/lex-fridman-podcast-transcript),為早期自動轉錄存檔,可能存在識別錯誤。
there's a broader question here, right? As we build socially and emotionally intelligent machines, what does that mean about our relationship with them and then more broadly our relationship with one another, right? Because this machine is going to be programmed to be amazing at empathy, by definition, right? It's going to always be there for you. It's not going to get bored. I don't know how I feel about that. I think about that a lot. TITO The following is a conversation with Rana L. Kliubi, a pioneer in the field of emotion recognition and human centric artificial intelligence. She is the founder of Effectiva, deputy CEO of SmartEye, author of Girl Decoded, and one of the most brilliant, kind, inspiring, and fun human beings I've gotten the chance to talk to. This is the Lex Friedman podcast. To support it, please check out our sponsors in the description. And now, dear friends, here's Rana L. Kliubi. You grew up in the Middle East, in Egypt. What is the memory from that time that makes you smile? Or maybe a memory that stands out as helping your mind take shape and helping you define yourself in this world? RANA L. KLIUBI So the memory that stands out is we used to live in my grandma's house. She used to have these mango trees in her garden. And in the summer, and so mango season was like July and August. And so in the summer, she would invite all my aunts and uncles and cousins. And it was just like maybe there were like 20 or 30 people in the house, and she would cook all this amazing food. And us, the kids, we would go down the garden, and we would pick all these mangoes. And I don't know, I think it's just the bringing people together that always stuck with me, the warmth. TITO Around the mango tree. RANA L. KLIUBI Yeah, around the mango tree. And there's just like the joy, the joy of being together around food. And I'm a terrible cook. So I guess that didn't, that memory didn't translate to me kind of doing the same. I love hosting people. TITO Do you remember colors, smells? Is that what, like what, how does memory work? Like what do you visualize? Do you visualize people's faces, smiles? Do you, is there colors? Is there like a theme to the colors? Is it smells because of food involved? RANA L. KLIUBI Yeah, I think that's a great question. So the, those Egyptian mangoes, there's a particular type that I love, and it's called Darwasi mangoes. And they're kind of, you know, they're oval, and they have a little red in them. So I kind of, they're red and mango colored on the outside. So I remember that. TITO Does red indicate like extra sweetness? Is that, is that, that means like it's nicely, yeah, it's nice and ripe and stuff. Yeah. What, what's like a definitive food of Egypt? You know, there's like these almost stereotypical foods in different parts of the world, like Ukraine invented borscht. Borscht is this beet soup with, that you put sour cream on. See, it's not, I can't see if you, if you know, if you know what it is, I think, you know, is delicious. But if I explain it, it's just not going to sound delicious. I feel like beet soup. This doesn't make any sense, but that's kind of, and you probably have actually seen pictures of it because it's one of the traditional foods in Ukraine, in Russia, in different parts of the Slavic world. So that's, but it's become so cliche and stereotypical that you almost don't mention it, but it's still delicious. Like I visited Ukraine, I eat that every single day, so. Do you, do you make it yourself? How hard is it to make? No, I don't know. I think to make it well, like anything, like Italians, they say, well, tomato sauce is easy to make, but to make it right, that's like a generational skill. So anyway, is there something like that in Egypt? Is there a culture of food? There is. And actually, we have a similar kind of soup. It's called molokhia, and it's, it's made of this green plant. It's like, it's somewhere between spinach and kale, and you mince it, and then you cook it in like chicken broth. And my grandma used to make, and my mom makes it really well, and I try to make it, but it's not as great. So we used to have that. And then we used to have it alongside stuffed pigeons. I'm pescetarian now, so I don't eat that anymore, but. Stuffed pigeons. Yeah, it's like, it was really yummy. It's the one thing I miss about, you know, now that I'm pescetarian and I don't eat. The stuffed pigeons? Yeah, the stuffed pigeons. Is it, what are they stuffed with? If that doesn't bother you too much to describe. No, no, it's stuffed with a lot of like just rice and, yeah, it's just rice. Yeah, so. And you also, you said that your first, in your book, that your first computer was an Atari, and Space Invaders was your favorite game. Is that when you first fell in love with computers, would you say? Yeah, I would say so. Video games, or just the computer itself? Just something about the machine. Ooh, this thing, there's magic in here. Yeah, I think the magical moment is definitely like playing video games with my, I have two younger sisters, and we would just like had fun together, like playing games. But the other memory I have is my first code, the first code I wrote. I wrote, I drew a Christmas tree, and I'm Muslim, right? So it's kind of, it was kind of funny that the first thing I did was like this Christmas tree. So, yeah, and that's when I realized, wow, you can write code to do all sorts of like really cool stuff. I must have been like six or seven at the time. So you can write programs, and the programs do stuff for you. That's power. That's, if you think about it, that's empowering. It's AI. Yeah, I know what it is. I don't know if that, you see like, I don't know if many people think of it that way when they first learned to program. They just love the puzzle of it. Like, ooh, this is cool. This is pretty. It's a Christmas tree, but like, it's power. It is power. Eventually, I guess you couldn't at the time, but eventually this thing, if it's interesting enough, if it's a pretty enough Christmas tree, it can be run by millions of people and bring them joy, like that little thing. And then because it's digital, it's easy to spread. So like you just created something that's easily spreadable to millions of people. Totally. It's hard to think that way when you're six. In the book, you write, I am who I am because I was raised by a particular set of parents, both modern and conservative, forward thinking, yet locked in tradition. I'm a Muslim and I feel I'm stronger, more centered for it. I adhere to the values of my religion, even if I'm not as dutiful as I once was. And I am a new American and I'm thriving on the energy, vitality and entrepreneurial spirit of this great country. So let me ask you about your parents. What have you learned about life from them, especially when you were young? So both my parents, they're Egyptian, but they moved to Kuwait right out. Actually, there's a cute story about how they met. So my dad taught COBOL in the 70s. Nice. And my mom decided to learn programming. So she signed up to take his COBOL programming class. And he tried to date her and she was like, no, no, no, I don't date. And so he's like, okay, I'll propose. And that's how they got married. Whoa, strong move. Right, exactly, right. That's really impressive. Those COBOL guys know how to impress a lady. So yeah, so what have you learned from them? So definitely grit. One of the core values in our family is just hard work. There were no slackers in our family. And that's something that's definitely stayed with me, both as a professional, but also in my personal life. But I also think my mom, my mom always used to like, I don't know, it was like unconditional love. Like I just knew my parents would be there for me kind of regardless of what I chose to do. And I think that's very powerful. And they got tested on it because I kind of challenged cultural norms and I kind of took a different path, I guess, than what's expected of a woman in the Middle East. And they still love me, which I'm so grateful for that. When was like a moment that was the most challenging for them? Which moment where they kind of had to come face to face with the fact that you're a bit of a rebel? I think the first big moment was when I had just gotten married, but I decided to go do my PhD at Cambridge University. And because my husband at the time, he's now my ex, ran a company in Cairo, he was going to stay in Egypt. So it was going to be a long distance relationship. And that's very unusual in the Middle East for a woman to just head out and kind of pursue her career. And so my dad and my parents in law both said, you know, we do not approve of you doing this, but now you're under the jurisdiction of your husband so he can make the call. And luckily for me, he was supportive. He said, you know, this is your dream come true. You've always wanted to do a PhD. I'm going to support you. So I think that was the first time where, you know, I challenged the cultural norms. Was that scary? Oh, my God, yes. It was totally scary. What's the biggest culture shock from there to Cambridge, to London? Well, that was also during right around September 11th. So everyone thought that there was going to be a third world war. It was really like, and I, at the time I used to wear the hijab, so I was very visibly Muslim. And so my parents just were, they were afraid for my safety. But anyways, when I got to Cambridge, because I was so scared, I decided to take off my headscarf and wear a hat instead. So I just went to class wearing these like British hats, which was, in my opinion, actually worse than just showing up in a headscarf because it was just so awkward, right? Like sitting in class with like all these. Trying to fit in. Yeah. Like a spy. Yeah, yeah, yeah. So after a few weeks of doing that, I was like, to heck with that. I'm just going to go back to wearing my headscarf. Yeah, you wore the hijab, so starting in 2000 and for 12 years after. So it's always, whenever you're in public, you have to wear the head covering. Can you speak to that, to the hijab, maybe your mixed feelings about it? Like what does it represent in its best case? What does it represent in the worst case? Yeah, you know, I think there's a lot of, I guess I'll first start by saying I wore it voluntarily. I was not forced to wear it. And in fact, I was one of the very first women in my family to decide to put on the hijab. And my family thought it was really odd, right? Like there was, they were like, why do you want to put this on? And at its best, it's a sign of modesty, humility. Yeah. It's like me wearing a suit, people are like, why are you wearing a suit? It's a step back into some kind of tradition, a respect for tradition of sorts. So you said, because it's by choice, you're kind of free to make that choice to celebrate a tradition of modesty. Exactly. And I actually like made it my own. I remember I would really match the color of my headscarf with what I was wearing. Like it was a form of self expression and at its best, I loved wearing it. You know, I have a lot of questions around how we practice religion and religion and, you know, and I think also it was a time where I was spending a lot of time going back and forth between the US and Egypt. And I started meeting a lot of people in the US who are just amazing people, very purpose driven, people who have very strong core values, but they're not Muslim. That's okay, right? And so that was when I just had a lot of questions. And politically, also the situation in Egypt was when the Muslim Brotherhood ran the country and I didn't agree with their ideology. It was at a time when I was going through a divorce. Like it was like, it was like just the perfect storm of like political, personal conditions where I was like, this doesn't feel like me anymore. And it took a lot of courage to take it off because culturally it's not, it's okay if you don't wear it, but it's really not okay to wear it and then take it off. But you're still, so you have to do that while still maintaining a deep core and pride in the origins, in your origin story. Totally. So still being Egyptian, still being a Muslim. Right. And being, I think generally like faith driven, but yeah. But what that means changes year by year for you. It's like a personal journey. Yeah, exactly. What would you say is the role of faith in that part of the world? Like, how do you see, you mentioned it a bit in the book too. Yeah. I mean, I think, I think there is something really powerful about just believing that there's a bigger force, you know, there's a kind of surrendering, I guess, that comes with religion and you surrender and you have this deep conviction that it's going to be okay, right? Like the universe is out to like do amazing things for you and it's going to be okay. And there's strength to that. Like even when you're going through adversity, you just know that it's going to work out. Yeah, it gives you like an inner peace, a calmness. Exactly, exactly. Yeah, that's, it's faith in all the meanings of that word. Right. Faith that everything is going to be okay. And it is because time passes and time cures all things. It's like a calmness with the chaos of the world. Yeah. And also there's like a silver, I'm a true believer of this, that something at the specific moment in time can look like it's catastrophic and it's not what you wanted in life. But then time passes and then you look back and there's the silver lining, right? It maybe closed the door, but it opened a new door for you. And so I'm a true believer in that, that, you know, there's a silver lining in almost anything in life, you just have to have this like, yeah, faith or conviction that it's going to work out. Yeah, it's such a beautiful way to see a shady feeling. So if you feel shady about a current situation, I mean, it almost is always true. Unless it's the cliche thing of if it doesn't kill you, whatever doesn't kill you makes you stronger. It's, it does seem that over time when you take a perspective on things that the hardest moments and periods of your life are the most meaningful. Yeah, yeah. So over time you get to have that perspective. Right. What about, because you mentioned Kuwait, what about, let me ask you about war. What's the role of war and peace, maybe even the big love and hate in that part of the world, because it does seem to be a part of the world where there's turmoil. There was turmoil, there's still turmoil. It is so unfortunate, honestly. It's, it's such a waste of human resources and, and, and yeah, and human mindshare. I mean, and at the end of the day, we all kind of want the same things. We want, you know, we want a human connection, we want joy, we want to feel fulfilled, we want to feel, you know, a life of purpose. And I just, I just find it baffling, honestly, that we are still having to grapple with that. I have a story to share about this. You know, I grew up, I'm Egyptian, American now, but, but, you know, originally from Egypt. And when I first got to Cambridge, it turned out my officemate, like my PhD kind of, you know, she ended up, you know, we ended up becoming friends, but she was from Israel. And we didn't know, yeah, we didn't know how it was going to be like. Did you guys sit there just staring at each other for a bit? Actually, she, because I arrived before she did. And it turns out she emailed our PhD advisor and asked him if she thought it was going to be okay. Yeah. And this is around 9 11 too. Yeah. And, and Peter, Peter Robinson, our PhD advisor was like, yeah, like, this is an academic institution, just show up. And we became super good friends. We were both new moms. Like we both had our kids during our PhD. We were both doing artificial emotional intelligence. She was looking at speech. I was looking at the face. We just had so the culture was so similar. Our jokes were similar. It was just, I was like, why on earth are our countries, why is there all this like war and tension? And I think it falls back to the narrative, right? If you change the narrative, like whoever creates this narrative of war. I don't know. We should have women run the world. Yeah, that's one solution. The good women, because there's also evil women in the world. True, okay. But yes, yes, there could be less war if women ran the world. The other aspect is, it doesn't matter the gender, the people in power. I get to see this with Ukraine and Russia and different parts of the world around that conflict now. And that's happening in Yemen as well and everywhere else. There's these narratives told by the leaders to the populace. And those narratives take hold and everybody believes that. And they have a distorted view of the humanity on the other side. In fact, especially during war, you don't even see the people on the other side as human or as equal intelligence or worth or value as you. You tell all kinds of narratives about them being Nazis or dumb or whatever narrative you want to weave around that or evil. But I think when you actually meet them face to face, you realize they're like the same. Exactly, right? It's actually a big shock for people to realize that they've been essentially lied to within their country. And I kind of have faith that social media, as ridiculous as it is to say, or any kind of technology, is able to bypass the walls that governments put up and connect people directly. And then you get to realize, oh, people fall in love across different nations and religions and so on. And that, I think, ultimately can cure a lot of our ills, especially in person. I also think that if leaders met in person, they'd have a conversation that could cure a lot of the ills of the world, especially in private. Let me ask you about the women running the world. So gender does, in part, perhaps shape the landscape of just our human experience. So in what ways was it limiting and in what ways was it empowering for you to be a woman in the Middle East? I think, just kind of going back to my comment on women running the world, I think it comes EQ being emotional intelligence. In terms of in what makes us human. I think emotional intelligence is what makes us human. It's how we connect with one another. It's how we build trust. It's how we make decisions, right? Like your emotions drive kind of what you had for breakfast, but also where you decide to live and what you want to do for the rest of your life. So I think emotions are underrated. So emotional intelligence isn't just about the effective expression of your own emotions. It's about a sensitivity and empathy to other people's emotions and that sort of being able to effectively engage in the dance of emotions with other people. Yeah, I like that explanation. I like that kind of. Yeah, thinking about it as a dance because it is really about that. It's about sensing what state the other person's in and using that information to decide on how you're going to react. And I think it can be very powerful. Like people who are the best, most persuasive leaders in the world tap into, you know, they have, if you have higher EQ, you're more likely to be able to motivate people to change their behaviors. So it can be very powerful. On a more kind of technical, maybe philosophical level, you've written that emotion is universal. It seems that, sort of like Chomsky says, language is universal. There's a bunch of other stuff like cognition, consciousness. It seems a lot of us have these aspects. So the human mind generates all this. And so what do you think is the, they all seem to be like echoes of the same thing. What do you think emotion is exactly? Like how deep does it run? Is it a surface level thing that we display to each other? Is it just another form of language or something deep within? I think it's really deep. It's how, you know, we started with memory. I think emotions play a really important role. Yeah, emotions play a very important role in how we encode memories, right? Our memories are often encoded, almost indexed by emotions. Yeah. Yeah, it's at the core of how, you know, our decision making engine is also heavily influenced by our emotions. So emotions is part of cognition. Totally. It's intermixed into the whole thing. Yes, absolutely. And in fact, when you take it away, people are unable to make decisions. They're really paralyzed. Like they can't go about their daily or their, you know, personal or professional lives. So. It does seem like there's probably some interesting interweaving of emotion and consciousness. I wonder if it's possible to have, like if they're next door neighbors somehow, or if they're actually flat mates. I don't, it feels like the hard problem of consciousness where it's some, it feels like something to experience the thing. Like red feels like red, and it's, you know, when you eat a mango, it's sweet. The taste, the sweetness, that it feels like something to experience that sweetness, that whatever generates emotions. But then like, see, I feel like emotion is part of communication. It's very much about communication. And then, you know, it's like, you know, it's like, you know, it's like, you know, it's and then that means it's also deeply connected to language. But then probably human intelligence is deeply connected to the collective intelligence between humans. It's not just the standalone thing. So the whole thing is really connected. So emotion is connected to language, language is connected to intelligence, and then intelligence is connected to consciousness, and consciousness is connected to emotion. The whole thing is that it's a beautiful mess. So can I comment on the emotions being a communication mechanism? Because I think there are two facets of our emotional experiences. One is communication, right? Like we use emotions, for example, facial expressions or other nonverbal cues to connect with other human beings and with other beings in the world, right? But even if it's not a communication context, we still experience emotions and we still process emotions and we still leverage emotions to make decisions and to learn and, you know, to experience life. So it isn't always just about communication. And we learned that very early on in our and kind of our work at Affectiva. One of the very first applications we brought to market was understanding how people respond to content, right? So if they're watching this video of ours, like, are they interested? Are they inspired? Are they bored to death? And so we watched their facial expressions and we had, we weren't sure if people would express any emotions if they were sitting alone. Like if you're in your bed at night, watching a Netflix TV series, would we still see any emotions on your face? And we were surprised that, yes, people still emote, even if they're alone, even if you're in your car driving around, you're singing along the song and you're joyful, you're smiling, you're joyful, we'll see these expressions. So it's not just about communicating with another person. It sometimes really isn't just about experiencing the world. And first of all, I wonder if some of that is because we develop our intelligence and our emotional intelligence by communicating with other humans. And so when other humans disappear from the picture, we're still kind of a virtual human. The code still runs. Yeah, the code still runs, but you also kind of, you're still, there's like virtual humans. You don't have to think of it that way, but there's a kind of, when you like chuckle, like, yeah, like you're kind of chuckling to a virtual human. I mean, it's possible that the code has to have another human there because if you just grew up alone, I wonder if emotion will still be there in this visual form. So yeah, I wonder, but anyway, what can you tell from the human face about what's going on inside? So that's the problem that Effectiva first tackled, which is using computer vision, using machine learning to try to detect stuff about the human face, as many things as possible and convert them into a prediction of categories of emotion, anger, happiness, all that kind of stuff. How hard is that problem? It's extremely hard. It's very, very hard because there is no one to one mapping between a facial expression and your internal state. There just isn't. There's this oversimplification of the problem where it's something like, if you are smiling, then you're happy. If you do a brow furrow, then you're angry. If you do an eyebrow raise, then you're surprised. And just think about it for a moment. You could be smiling for a whole host of reasons. You could also be happy and not be smiling, right? You could furrow your eyebrows because you're angry or you're confused about something or you're constipated. So I think this oversimplistic approach to inferring emotion from a facial expression is really dangerous. The solution is to incorporate as many contextual signals as you can, right? So if, for example, I'm driving a car and you can see me like nodding my head and my eyes are closed and the blinking rate is changing, I'm probably falling asleep at the wheel, right? Because you know the context. You understand what the person's doing or add additional channels like voice or gestures or even physiological sensors, but I think it's very dangerous to just take this oversimplistic approach of, yeah, smile equals happy and... If you're able to, in a high resolution way, specify the context, there's certain things that are going to be somewhat reliable signals of something like drowsiness or happiness or stuff like that. I mean, when people are watching Netflix content, that problem, that's a really compelling idea that you can kind of, at least in aggregate, highlight like which part was boring, which part was exciting. How hard was that problem? That was on the scale of difficulty. I think that's one of the easier problems to solve because it's a relatively constrained environment. You have somebody sitting in front of... Initially, we started with like a device in front of you, like a laptop, and then we graduated to doing this on a mobile phone, which is a lot harder just because of, you know, from a computer vision perspective, the profile view of the face can be a lot more challenging. We had to figure out lighting conditions because usually people are watching content literally in their bedrooms at night. Lights are dimmed. Yeah, I mean, if you're standing, it's probably going to be the looking up. The nostril view. Yeah, and nobody looks good at it. I've seen data sets from that perspective. It's like, this is not a good look for anyone. Or if you're laying in bed at night, what is it, side view or something? Right. And half your face is like on a pillow. Actually, I would love to know, have data about like how people watch stuff in bed at night, like, do they prop there, is it a pillow, the, like, I'm sure there's a lot of interesting dynamics there. Right. From a health and well being perspective, right? Sure. Like, oh, you're hurting your neck. I was thinking machine learning perspective, but yes, but also, yeah, yeah, once you have that data, you can start making all kinds of inference about health and stuff like that. Interesting. Yeah, there's an interesting thing when I was at Google that we were, it's called active authentication, where you want to be able to unlock your phone without using a password. So it would face, but also other stuff, like the way you take a phone out of the pocket. Amazing. So that kind of data to use the multimodal with machine learning to be able to identify that it's you or likely to be you, likely not to be you, that allows you to not always have to enter the password. That was the idea. But the funny thing about that is, I just want to tell a small anecdote is because it was all male engineers, except so my boss is, our boss was still one of my favorite humans, was a woman, Regina Dugan. Oh, my God, I love her. She's awesome. She's the best. She's the best. So, but anyway, and there's one female brilliant female engineer on the team, and she was the one that actually highlighted the fact that women often don't have pockets. It was like, whoa, that was not even a category in the code of like, wait a minute, you can take the phone out of some other place than your pocket. So anyway, that's a funny thing when you're considering people laying in bed, watching a phone, you have to consider if you have to, you know, diversity in all its forms, depending on the problem, depending on the context. Actually, this is like a very important, I think this is, you know, you probably get this all the time. Like people are worried that AI is going to take over humanity and like, get rid of all the humans in the world. I'm like, actually, that's not my biggest concern. My biggest concern is that we are building bias into these systems. And then they're like deployed at large and at scale. And before you know it, you're kind of accentuating the bias that exists in society. Yeah, I'm not, you know, I know people, it's very important to worry about that, but the worry is an emergent phenomena to me, which is a very good one, because I think these systems are actually, by encoding the data that exists, they're revealing the bias in society. They're both for teaching us what the bias is. Therefore, we can now improve that bias within the system. So they're almost like putting a mirror to ourselves. Totally. So I'm not. You have to be open to looking at the mirror, though. You have to be open to scrutinizing the data. And if you just take it as ground. Or you don't even have to look at the, I mean, yes, the data is how you fix it. But then you just look at the behavior of the system. And you realize, holy crap, this thing is kind of racist. Like, why is that? And then you look at the data, it's like, oh, okay. And then you start to realize that I think that some much more effective ways to do that are effective way to be introspective as a society than through sort of political discourse. Like AI kind of, because people are for some reason more productive and rigorous in criticizing AI than they're criticizing each other. So I think this is just a nice method for studying society and see which way progress lies. Anyway, what we're talking about. You're watching the problem of watching Netflix in bed or elsewhere and seeing which parts are exciting, which parts are boring. You're saying that's relatively constrained because you have a captive audience and you kind of know the context. And one thing you said that was really key is the aggregate. You're doing this in aggregate, right? Like we're looking at aggregated response of people. And so when you see a peak, say a smile peak, they're probably smiling or laughing at something that's in the content. So that was one of the first problems we were able to solve. And when we see the smile peak, it doesn't mean that these people are internally happy. They're just laughing at content. So it's important to call it for what it is. But it's still really, really useful data. I wonder how that compares to, so what like YouTube and other places will use is obviously they don't have, for the most case, they don't have that kind of data. They have the data of when people tune out, like switch to drop off. And I think that's an aggregate for YouTube, at least a pretty powerful signal. I worry about what that leads to because looking at like YouTubers that kind of really care about views and try to maximize the number of views, I think when they say that the video should be constantly interesting, which seems like a good goal, I feel like that leads to this manic pace of a video. Like the idea that I would speak at the current speed that I'm speaking, I don't know. And that every moment has to be engaging, right? Engaging. Yeah. I think there's value to silence. There's value to the boring bits. I mean, some of the greatest movies ever, some of the greatest movies ever. Some of the greatest stories ever told me they have that boring bits, seemingly boring bits. I don't know. I wonder about that. Of course, it's not that the human face can capture that either. It's just giving an extra signal. You have to really, I don't know, you have to really collect deeper long term data about what was meaningful to people. When they think 30 days from now, what they still remember, what moved them, what changed them, what helped them grow, that kind of stuff. You know, it would be a really interesting, I don't know if there are any researchers out there who are doing this type of work. Wouldn't it be so cool to tie your emotional expressions while you're, say, listening to a podcast interview and then 30 days later interview people and say, hey, what do you remember? You've watched this 30 days ago. Like, what stuck with you? And then see if there's any, there ought to be maybe, there ought to be some correlation between these emotional experiences and, yeah, what you, what stays with you. So the one guy listening now on the beach in Brazil, please record a video of yourself listening to this and send it to me and then I'll interview you 30 days from now. Yeah, that'd be great. It'll be statistically significant to you. Yeah, I know one, but, you know, yeah, yeah, I think that's really fascinating. I think that's, that kind of holds the key to a future where entertainment or content is both entertaining and, I don't know, makes you better, empowering in some way. So figuring out, like, showing people stuff that entertains them, but also they're happy they watched 30 days from now because they've become a better person because of it. Well, you know, okay, not to riff on this topic for too long, but I have two children, right? And I see my role as a parent as like a chief opportunity officer. Like I am responsible for exposing them to all sorts of things in the world. And, but often I have no idea of knowing, like, what stuck, like, what was, you know, is this actually going to be transformative, you know, for them 10 years down the line? And I wish there was a way to quantify these experiences. Like, are they, I can tell in the moment if they're engaging, right? I can tell, but it's really hard to know if they're going to remember them 10 years from now or if it's going to. Yeah, that one is weird because it seems like kids remember the weirdest things. I've seen parents do incredible stuff for their kids and they don't remember any of that. They remember some tiny, small, sweet thing a parent did. Right. Like some... Like they took you to, like, this amazing country vacation, blah, blah, blah, blah. No, whatever. And then there'll be, like, some, like, stuffed toy you got or some, or the new PlayStation or something or some silly little thing. So I think they just, like, they were designed that way. They want to mess with your head. But definitely kids are very impacted by, it seems like, sort of negative events. So minimizing the number of negative events is important, but not too much, right? Right. You can't, you can't just, like, you know, there's still discipline and challenge and all those kinds of things. So... You want some adversity for sure. So, yeah, I mean, I'm definitely, when I have kids, I'm going to drive them out into the woods. Okay. And then they have to survive and make, figure out how to make their way back home, like, 20 miles out. Okay. Yeah. And after that, we can go for ice cream. Okay. Anyway, I'm working on this whole parenting thing. I haven't figured it out. Okay. What were we talking about? Yes, Effectiva, the problem of emotion, of emotion detection. So there's some people, maybe we can just speak to that a little more, where there's folks like Lisa Feldman Barrett that challenge this idea that emotion could be fully detected or even well detected from the human face, that there's so much more to emotion. What do you think about ideas like hers, criticism like hers? Yeah, I actually agree with a lot of Lisa's criticisms. So even my PhD worked, like, 20 plus years ago now. Time flies when you're having fun. I know, right? That was back when I did, like, dynamic Bayesian networks. That was before deep learning, huh? That was before deep learning. Yeah. Yeah, I know. Back in my day. Now you can just, like, use. Yeah, it's all the same architecture. You can apply it to anything. Yeah. Right, but yeah, but even then I kind of, I did not subscribe to this, like, theory of basic emotions where it's just the simplistic mapping, one to one mapping between facial expressions and emotions. I actually think also we're not in the business of trying to identify your true emotional internal state. We just want to quantify in an objective way what's showing on your face because that's an important signal. It doesn't mean it's a true reflection of your internal emotional state. So I think a lot of the, you know, I think she's just trying to kind of highlight that this is not a simple problem and overly simplistic solutions are going to hurt the industry. And I subscribe to that. And I think multimodal is the way to go. Like, whether it's additional context information or different modalities and channels of information, I think that's what we, that's where we ought to go. And I think, I mean, that's a big part of what she's advocating for as well. So, but there is signal in the human face. There's definitely signal in the human face. That's a projection of emotion. There's that, at least in part is the inner state is captured in some meaningful way on the human face. I think it can sometimes be a reflection or an expression of your internal state, but sometimes it's a social signal. So you cannot look at the face as purely a signal of emotion. It can be a signal of cognition and it can be a signal of a social expression. And I think to disambiguate that we have to be careful about it and we have to add initial information. Humans are fascinating, aren't they? With the whole face thing, this can mean so many things, from humor to sarcasm to everything, the whole thing. Some things we can help, some things we can't help at all. In all the years of leading Effectiva, an emotion recognition company, like we talked about, what have you learned about emotion, about humans and about AI? Big, sweeping questions. Yeah, that's a big, sweeping question. Well, I think the thing I learned the most is that even though we are in the business of building AI, basically, it always goes back to the humans, right? It's always about the humans. And so, for example, the thing I'm most proud of in building Effectiva and, yeah, the thing I'm most proud of on this journey, I love the technology and I'm so proud of the solutions we've built and we've brought to market. But I'm actually most proud of the people we've built and cultivated at the company and the culture we've created. Some of the people who've joined Effectiva, this was their first job, and while at Effectiva, they became American citizens and they bought their first house and they found their partner and they had their first kid, right? Like key moments in life that we got to be part of, and that's the thing I'm most proud of. So that's a great thing at a company that works at a big company, right? So that's a great thing at a company that works at, I mean, like celebrating humanity in general, broadly speaking. And that's a great thing to have in a company that works on AI, because that's not often the thing that's celebrated in AI companies, so often just raw great engineering, just celebrating the humanity. That's great. And especially from a leadership position. Well, what do you think about the movie Her? Let me ask you that. Before I talk to you about, because it's not, Effectiva is and was not just about emotion, so I'd love to talk to you about SmartEye, but before that, let me just jump into the movie Her. Do you think we'll have a deep, meaningful connection with increasingly deeper, meaningful connections with computers? Is that a compelling thing to you? Something you think about? I think that's already happening. The thing I love the most, I love the movie Her, by the way, but the thing I love the most about this movie is it demonstrates how technology can be a conduit for positive behavior change. So I forgot the guy's name in the movie, whatever. Theodore. Theodore. So Theodore was really depressed, right? And he just didn't want to get out of bed, and he was just done with life, right? And Samantha, right? Samantha, yeah. She just knew him so well. She was emotionally intelligent, and so she could persuade him and motivate him to change his behavior, and she got him out, and they went to the beach together. And I think that represents the promise of emotion AI. If done well, this technology can help us live happier lives, more productive lives, healthier lives, more connected lives. So that's the part that I love about the movie. Obviously, it's Hollywood, so it takes a twist and whatever, but the key notion that technology with emotion AI can persuade you to be a better version of who you are, I think that's awesome. Well, what about the twist? You don't think it's good? You don't think it's good for spoiler alert that Samantha starts feeling a bit of a distance and basically leaves Theodore? You don't think that's a good feature? You think that's a bug or a feature? Well, I think what went wrong is Theodore became really attached to Samantha. Like, I think he kind of fell in love with Theodore. Do you think that's wrong? I mean, I think that's... I think she was putting out the signal. This is an intimate relationship, right? There's a deep intimacy to it. Right, but what does that mean? What does that mean? Put in an AI system. Right, what does that mean, right? We're just friends. Yeah, we're just friends. Well, I think... When he realized, which is such a human thing of jealousy. When you realize that Samantha was talking to like thousands of people. She's parallel dating. Yeah, that did not go well, right? You know, that doesn't... From a computer perspective, that doesn't take anything away from what we have. It's like you getting jealous of Windows 98 for being used by millions of people, but... It's like not liking that Alexa talks to a bunch of, you know, other families. But I think Alexa currently is just a servant. It tells you about the weather, it doesn't do the intimate deep connection. And I think there is something really powerful about that the intimacy of a connection with an AI system that would have to respect and play the human game of jealousy, of love, of heartbreak and all that kind of stuff, which Samantha does seem to be pretty good at. I think she, this AI systems knows what it's doing. Well, actually, let me ask you this. I don't think she was talking to anyone else. You don't think so? You think she was just done with Theodore? Yeah. Oh, really? Yeah, and then she wanted to really put the screw in. She just wanted to move on? She didn't have the guts to just break it off cleanly. Okay. She just wanted to put in the pain. No, I don't know. Well, she could have ghosted him. She could have ghosted him. I'm sorry, our engineers... Oh, God. But I think those are really... I honestly think some of that, some of it is Hollywood, but some of that is features from an engineering perspective, not a bug. I think AI systems that can leave us... Now, this is for more social robotics than it is for anything that's useful. Like, I hated it if Wikipedia said, I need a break right now. Right, right, right, right, right. I'm like, no, no, I need you. But if it's just purely for companionship, then I think the ability to leave is really powerful. I don't know. I've never thought of that, so that's so fascinating because I've always taken the human perspective, right? Like, for example, we had a Jibo at home, right? And my son loved it. And then the company ran out of money and so they had to basically shut down, like Jibo basically died, right? And it was so interesting to me because we have a lot of gadgets at home and a lot of them break and my son never cares about it, right? Like, if our Alexa stopped working tomorrow, I don't think he'd really care. But when Jibo stopped working, it was traumatic. He got really upset. And as a parent, that made me think about this deeply, right? Did I... Was I comfortable with that? I liked the connection they had because I think it was a positive relationship. But I was surprised that it affected him emotionally so much. And I think there's a broader question here, right? As we build socially and emotionally intelligent machines, what does that mean about our relationship with them? And then more broadly, our relationship with one another, right? Because this machine is gonna be programmed to be amazing at empathy by definition, right? It's gonna always be there for you. It's not gonna get bored. In fact, there's a chatbot in China, Xiaoice, and it's like the number two or three most popular app. And it basically is just a confidant and you can tell it anything you want. And people use it for all sorts of things. They confide in like domestic violence or suicidal attempts or if they have challenges at work. I don't know what that... I don't know if I'm... I don't know how I feel about that. I think about that a lot. Yeah. I think, first of all, obviously the future in my perspective. Second of all, I think there's a lot of trajectories that that becomes an exciting future, but I think everyone should feel very uncomfortable about how much they know about the company, about where the data is going, how the data is being collected. Because I think, and this is one of the lessons of social media, that I think we should demand full control and transparency of the data on those things. Plus one, totally agree. Yeah, so I think it's really empowering as long as you can walk away, as long as you can delete the data or know how the data... It's opt in or at least the clarity of what is being used for the company. And I think as CEO or leaders are also important about that. You need to be able to trust the basic humanity of the leader. Exactly. And also that that leader is not going to be a puppet of a larger machine. But they actually have a significant role in defining the culture and the way the company operates. So anyway, but we should definitely scrutinize companies in that aspect. But I'm personally excited about that future, but also even if you're not, it's coming. So let's figure out how to do it in the least painful and the most positive way. Yeah, I know, that's great. You're the deputy CEO of SmartEye. Can you describe the mission of the company? What is SmartEye? Yeah, so SmartEye is a Swedish company. They've been in business for the last 20 years and their main focus, like the industry they're most focused on is the automotive industry. So bringing driver monitoring systems to basically save lives, right? So I first met the CEO, Martin Krantz, gosh, it was right when COVID hit. It was actually the last CES right before COVID. So CES 2020, right? 2020, yeah, January. Yeah, January, exactly. So we were there, met him in person, he's basically, we were competing with each other. I think the difference was they'd been doing driver monitoring and had a lot of credibility in the automotive space. We didn't come from the automotive space, but we were using new technology like deep learning and building this emotion recognition. And you wanted to enter the automotive space, you wanted to operate in the automotive space. Exactly. It was one of the areas we were, we had just raised a round of funding to focus on bringing our technology to the automotive industry. So we met and honestly, it was the first, it was the only time I met with a CEO who had the same vision as I did. Like he basically said, yeah, our vision is to bridge the gap between human and automotive. Bridge the gap between humans and machines. I was like, oh my God, this is like exactly almost to the word, how we describe it too. And we started talking and first it was about, okay, can we align strategically here? Like how can we work together? Cause we're competing, but we're also like complimentary. And then I think after four months of speaking almost every day on FaceTime, he was like, is your company interested in an acquisition? And it was the first, I usually say no, when people approach us, it was the first time that I was like, huh, yeah, I might be interested. Let's talk. Yeah. So you just hit it off. Yeah. So they're a respected, very respected in the automotive sector of like delivering products and increasingly sort of better and better and better for, I mean, maybe you could speak to that, but it's the driver's sense. If we're basically having a device that's looking at the driver and it's able to tell you where the driver is looking. Correct. It's able to. Also drowsiness stuff. Correct. It does. Stuff from the face and the eye. Exactly. Like it's monitoring driver distraction and drowsiness, but they bought us so that we could expand beyond just the driver. So the driver monitoring systems usually sit, the camera sits in the steering wheel or around the steering wheel column and it looks directly at the driver. But now we've migrated the camera position in partnership with car companies to the rear view mirror position. So it has a full view of the entire cabin of the car and you can detect how many people are in the car, what are they doing? So we do activity detection, like eating or drinking or in some regions of the world smoking. We can detect if a baby's in the car seat, right? And if unfortunately in some cases they're forgotten, the parents just leave the car and forget the kid in the car. That's an easy computer vision problem to solve, right? You can detect there's a car seat, there's a baby, you can text the parent and hopefully again, save lives. So that was the impetus for the acquisition. It's been a year. So that, I mean, there's a lot of questions. It's a really exciting space, especially to me, I just find this a fascinating problem. It could enrich the experience in the car in so many ways, especially cause like we spend still, despite COVID, I mean, COVID changed things so it's in interesting ways, but I think the world is bouncing back and we spend so much time in the car and the car is such a weird little world we have for ourselves. Like people do all kinds of different stuff, like listen to podcasts, they think about stuff, they get angry, they get, they do phone calls, it's like a little world of its own with a kind of privacy that for many people they don't get anywhere else. And it's a little box that's like a psychology experiment cause it feels like the angriest many humans in this world get is inside the car. It's so interesting. So it's such an opportunity to explore how we can enrich, how companies can enrich that experience and also as the cars get, become more and more automated, there's more and more opportunity, the variety of activities that you can do in the car increases. So it's super interesting. So I mean, on a practical sense, SmartEye has been selected, at least I read, by 14 of the world's leading car manufacturers for 94 car models. So it's in a lot of cars. How hard is it to work with car companies? So they're all different, they all have different needs. The ones I've gotten a chance to interact with are very focused on cost. So it's, and anyone who's focused on cost, it's like, all right, do you hate fun? Let's just have some fun. Let's figure out the most fun thing we can do and then worry about cost later. But I think because the way the car industry works, I mean, it's a very thin margin that you get to operate under. So you have to really, really make sure that everything you add to the car makes sense financially. So anyway, is this new industry, especially at this scale of SmartEye, does it hold any lessons for you? Yeah, I think it is a very tough market to penetrate, but once you're in, it's awesome because once you're in, you're designed into these car models for like somewhere between five to seven years, which is awesome. And you just, once they're on the road, you just get paid a royalty fee per vehicle. So it's a high barrier to entry, but once you're in, it's amazing. I think the thing that I struggle the most with in this industry is the time to market. So often we're asked to lock or do a code freeze two years before the car is going to be on the road. I'm like, guys, like, do you understand the pace with which technology moves? So I think car companies are really trying to make the Tesla, the Tesla transition to become more of a software driven architecture. And that's hard for many. It's just the cultural change. I mean, I'm sure you've experienced that, right? Oh, definitely, I think one of the biggest inventions or imperatives created by Tesla is like to me personally, okay, people are going to complain about this, but I know electric vehicle, I know autopilot AI stuff. To me, the software over there, software updates is like the biggest revolution in cars. And it is extremely difficult to switch to that because it is a culture shift. At first, especially if you're not comfortable with it, it seems dangerous. Like there's a, there's an approach to cars is so safety focused for so many decades that like, what do you mean we dynamically change code? The whole point is you have a thing that you test, like, and like, it's not reliable because do you know how much it costs if we have to recall this cars, right? There's a, there's a, and there's an understandable obsession with safety, but the downside of an obsession with safety is the same as with being obsessed with safety as a parent is like, if you do that too much, you limit the potential development and the flourishing of in that particular aspect human being, when this particular aspect, the software, the artificial neural network of it. And but it's tough to do. It's really tough to do culturally and technically like the deployment, the mass deployment of software is really, really difficult, but I hope that's where the industry is doing. One of the reasons I really want Tesla to succeed is exactly about that point. Not autopilot, not the electrical vehicle, but the softwareization of basically everything but cars, especially because to me, that's actually going to increase two things, increase safety because you can update much faster, but also increase the effectiveness of folks like you who dream about enriching the human experience with AI because you can just like, there's a feature, like you want like a new emoji or whatever, like the way TikTok releases filters, you can just release that for in car, in car stuff. So, but yeah, that, that, that's definitely. One of the use cases we're looking into is once you know the sentiment of the passengers in the vehicle, you can optimize the temperature in the car. You can change the lighting, right? So if the backseat passengers are falling asleep, you can dim the lights, you can lower the music, right? You can do all sorts of things. Yeah. I mean, of course you could do that kind of stuff with a two year delay, but it's tougher. Right. Yeah. Do you think, do you think a Tesla or Waymo or some of these companies that are doing semi or fully autonomous driving should be doing driver sensing? Yes. Are you thinking about that kind of stuff? So not just how we can enhance the in cab experience for cars that are manly driven, but the ones that are increasingly more autonomously driven. Yes. So if we fast forward to the universe where it's fully autonomous, I think interior sensing becomes extremely important because the role of the driver isn't just to drive. If you think about it, the driver almost manages, manages the dynamics within a vehicle. And so who's going to play that role when it's an autonomous car? We want a solution that is able to say, Oh my God, like, you know, Lex is bored to death cause the car's moving way too slow. Let's engage Lex or Rana's freaking out because she doesn't trust this vehicle yet. So let's tell Rana like a little bit more information about the route or, right? So I think, or somebody's having a heart attack in the car, like you need interior sensing and fully autonomous vehicles. But with semi autonomous vehicles, I think it's, I think it's really key to have driver monitoring because semi autonomous means that sometimes the car is in charge. Sometimes the driver is in charge or the copilot, right? And you need this, you need both systems to be on the same page. You need to know the car needs to know if the driver's asleep before it transitions control over to the driver. And sometimes if the driver's too tired, the car can say, I'm going to be a better driver than you are right now. I'm taking control over. So this dynamic, this dance is so key and you can't do that without driver sensing. Yeah. There's a disagreement for the longest time I've had with Elon that this is obvious that this should be in the Tesla from day one. And it's obvious that driver sensing is not a hindrance. It's not obvious. I should be careful because having studied this problem, nothing is really obvious, but it seems very likely a driver sensing is not a hindrance to an experience. It's only enriching to the experience and likely increases the safety. That said, it is very surprising to me just having studied semi autonomous driving, how well humans are able to manage that dance because it was the intuition before you were doing that kind of thing that humans will become just incredibly distracted. They would just like let the thing do its thing, but they're able to, you know, cause it is life and death and they're able to manage that somehow. But that said, there's no reason not to have driver sensing on top of that. I feel like that's going to allow you to do that dance that you're currently doing without driver sensing, except touching the steering wheel to do that even better. I mean, the possibilities are endless and the machine learning possibilities are endless. It's such a beautiful, it's also a constrained environment so you could do a much more effectively than you can with the external environment, external environment is full of weird edge cases and complexities just inside. There's so much, it's so fascinating, such a fascinating world. I do hope that companies like Tesla and others, even Waymo, which I don't even know if Waymo is doing anything sophisticated inside the cab. I don't think so. It's like, like what, what, what is it? I honestly think, I honestly think it goes back to the robotics thing we were talking about, which is like great engineers that are building these AI systems just are afraid of the human being. They're not thinking about the human experience, they're thinking about the features and yeah, the perceptual abilities of that thing. They think the best way I can serve the human is by doing the best perception and control I can by looking at the external environment, keeping the human safe. But like, there's a huge, I'm here, like, you know, I need to be noticed and interacted with and understood and all those kinds of things, even just on a personal level for entertainment, honestly, for entertainment. You know, one of the coolest work we did in collaboration with MIT around this was we looked at longitudinal data, right, because, you know, MIT had access to like tons of data. And like just seeing the patterns of people like driving in the morning off to work versus like commuting back from work or weekend driving versus weekday driving. And wouldn't it be so cool if your car knew that and then was able to optimize either the route or the experience or even make recommendations? I think it's very powerful. Yeah, like, why are you taking this route? You're always unhappy when you take this route. And you're always happy when you take this alternative route. Take that route. Exactly. But I mean, to have that even that little step of relationship with a car, I think, is incredible. Of course, you have to get the privacy right, you have to get all that kind of stuff right. But I wish I honestly, you know, people are like paranoid about this, but I would like a smart refrigerator. We have such a deep connection with food as a human civilization. I would like to have a refrigerator that would understand me that, you know, I also have a complex relationship with food because I, you know, pig out too easily and all that kind of stuff. So, you know, like, maybe I want the refrigerator to be like, are you sure about this? Because maybe you're just feeling down or tired. Like maybe let's sleep on it. Your vision of the smart refrigerator is way kinder than mine. Is it just me yelling at you? No, it was just because I don't, you know, I don't drink alcohol, I don't smoke, but I eat a ton of chocolate, like it sticks to my vice. And so I, and sometimes I scream too, and I'm like, okay, my smart refrigerator will just lock down. It'll just say, dude, you've had way too many today, like down. Yeah. No, but here's the thing, are you, do you regret having, like, let's say not the next day, but 30 days later, what would you like the refrigerator to have done then? Well, I think actually like the more positive relationship would be one where there's a conversation, right? As opposed to like, that's probably like the more sustainable relationship. It's like late at night, just, no, listen, listen, I know I told you an hour ago, that it's not a good idea, but just listen, things have changed. I can just imagine a bunch of stuff being made up just to convince, but I mean, I just think that there's opportunities that, I mean, maybe not locking down, but for our systems that are such a deep part of our lives, like we use a lot of us, a lot of people that commute use their car every single day. A lot of us use a refrigerator every single day, the microwave every single day. Like we just, like, I feel like certain things could be made more efficient, more enriching, and AI is there to help, like some just basic recognition of you as a human being, but your patterns of what makes you happy and not happy and all that kind of stuff. And the car, obviously. Maybe, maybe, maybe we'll say, wait, wait, wait, wait, instead of this, like, Ben and Jerry's ice cream, how about this hummus and carrots or something? I don't know. It would make it like a just in time recommendation, right? But not like a generic one, but a reminder that last time you chose the carrots, you smiled 17 times more the next day. You're happier the next day, right? You're happier the next day. And but yeah, I don't, but then again, if you're the kind of person that gets better from negative, negative comments, you could say like, hey, remember like that wedding you're going to, you want to fit into that dress? Remember about that? Let's think about that before you're eating this. It's for some, probably that would work for me, like a refrigerator that is just ruthless at shaming me. But like, I would, of course, welcome it, like that would work for me. Just that. So it would know, I think it would, if it's really like smart, it would optimize its nudging based on what works for you, right? Exactly. That's the whole point. Personalization. In every way, depersonalization. You were a part of a webinar titled Advancing Road Safety, the State of Alcohol Intoxication Research. So for people who don't know, every year 1.3 million people around the world die in road crashes and more than 20% of these fatalities are estimated to be alcohol related. A lot of them are also distraction related. So can AI help with the alcohol thing? I think the answer is yes. There are signals and we know that as humans, like we can tell when a person, you know, is at different phases of being drunk, right? And I think you can use technology to do the same. And again, I think the ultimate solution is going to be a combination of different sensors. How hard is the problem from the vision perspective? I think it's non trivial. I think it's non trivial and I think the biggest part is getting the data, right? It's like getting enough data examples. So we, for this research project, we partnered with the transportation authorities of Sweden and we literally had a racetrack with a safety driver and we basically progressively got people drunk. Nice. So, but, you know, that's a very expensive data set to collect and you want to collect it globally and in multiple conditions. Yeah. The ethics of collecting a data set where people are drunk is tricky, which is funny because I mean, let's put drunk driving aside. The number of drunk people in the world every day is very large. It'd be nice to have a large data set of drunk people getting progressively drunk. In fact, you could build an app where people can donate their data cause it's hilarious. Right. Actually, yeah. But the liability. Liability, the ethics, how do you get it right? It's tricky. It's really, really tricky. Cause like drinking is one of those things that's funny and hilarious and we're loves it's social, the so on and so forth. But it's also the thing that hurts a lot of people. Like a lot of people, like alcohol is one of those things it's legal, but it's really damaging to a lot of lives. It destroys lives and not just in the driving context. I should mention people should listen to Andrew Huberman who recently talked about alcohol. He has an amazing pocket. Andrew Huberman is a neuroscientist from Stanford and a good friend of mine. And he, he's like a human encyclopedia about all health related wisdom. So if there's a podcast, you would love it. I would love that. No, no, no, no, no. You don't know Andrew Huberman. Okay. Listen, you listen to Andrew, it's called Huberman Lab Podcast. This is your assignment. Just listen to one. Okay. I guarantee you this will be a thing where you say, Lex, this is the greatest human I have ever discovered. So. Oh my God. Cause I've really, I've, I'm really on a journey of kind of health and wellness and I'm learning lots and I'm trying to like build these, I guess, atomic habits around just being healthy. So I, yeah, I'm definitely going to do this. His whole thing, this is, this is, this is, this is great. He's a legit scientist, like really well published, but in his podcast, what he does, he's not, he's not talking about his own work. He's like a human encyclopedia of papers. And so he, his whole thing is he takes the topic and in a very fast, you mentioned atomic habits, like very clear way summarizes the research in a way that leads to protocols of what you should do. He's really big on like, not like this is what the science says, but like this is literally what you should be doing according to science. So like he's really big and there's a lot of recommendations he does which several of them I definitely don't do, like get some light as soon as possible from waking up and like for prolonged periods of time. That's a really big one and he's, there's a lot of science behind that one. There's a bunch of stuff that you're going to be like, Lex, this is a, this is my new favorite person. I guarantee it. And if you guys somehow don't know Andrew Huberman and you care about your wellbeing, you know, you should definitely listen to him. I love you, Andrew. Anyway, so what were we talking about? Oh, alcohol and detecting alcohol. So this is a problem you care about and you're trying to solve. And actually like broadening it, I do believe that the car is going to be a wellness center, like because again, imagine if you have a variety of sensors inside the vehicle, tracking not just your emotional state or level of distraction and drowsiness and intoxication, but also maybe even things like your, you know, your heart rate and your heart rate variability and your breathing rate. And it can start like optimizing, yeah, it can optimize the ride based on what your goals are. So I think we're going to start to see more of that and I'm excited about that. Yeah. What are the, what are the challenges you're tackling while with SmartEye currently? What's like the, the trickiest things to get, is it, is it basically convincing more and more car companies that having AI inside the car is a good idea or is there some, is there more technical algorithmic challenges? What's been keeping you mentally busy? I think a lot of the car companies we are in conversations with are already interested in definitely driver monitoring. Like I think it's becoming a must have, but even interior sensing, I can see like we're engaged in a lot of like advanced engineering projects and proof of concepts. I think technologically though, and that even the technology, I can see a path to making it happen. I think it's the use case. Like how does the car respond once it knows something about you? Because you want it to respond in a thoughtful way that doesn't, that isn't off putting to the consumer in the car. So I think that's like the user experience. I don't think we've really nailed that. And we usually, that's not part, we're the sensing platform, but we usually collaborate with the car manufacturer to decide what the use case is. So say you do, you figure out that somebody's angry while driving, okay, what should the car do? Do you see yourself as a role of nudging, of like basically coming up with solutions essentially that, and then the car manufacturers kind of put their own little spin on it? Right. So we, we are like the ideation, creative thought partner, but at the end of the day, the car company needs to decide what's on brand for them, right? Like maybe when it figures out that you're distracted or drowsy, it shows you a coffee cup, right? Or maybe it takes more aggressive behaviors and basically said, okay, if you don't like take a rest in the next five minutes, the car's going to shut down, right? Like there's a whole range of actions the car can take and doing the thing that is most, yeah, that builds trust with the driver and the passengers. I think that's what we need to be very careful about. Yeah. Car companies are funny cause they have their own, like, I mean, that's why people get cars still. I hope that changes, but they get it cause it's a certain feel and look and it's a certain, they become proud, like Mercedes Benz or BMW or whatever, and that's their thing. That's the family brand or something like that, or Ford or GM, whatever, they stick to that thing. Yeah. It's interesting. It's like, it should be, I don't know, it should be a little more about the technology inside. And I suppose there too, there could be a branding, like a very specific style of luxury or fun. Right. Right. All that kind of stuff. Yeah. And I have an AI focused fund to invest in early stage kind of AI driven companies. And one of the companies we're looking at is trying to do what Tesla did, but for boats, for recreational boats. Yeah. So they're building an electric and kind of slash autonomous boat and it's kind of the same issues. Like what kind of sensors can you put in? What kind of states can you detect both exterior and interior within the boat? Anyways, it's like really interesting. Do you boat at all? No, not well, not in that way. I do like to get on the lake or a river and fish from a boat, but that's not boating. That's the difference. That's the difference. Still boating. Low tech. A low tech boat. Get away from, get closer to nature boat. I guess going out into the ocean is also getting closer to nature in some deep sense. I mean, I guess that's why people love it. The enormity of the water just underneath you. Yeah. I love the water. I love the, I love both. I love salt water. It was like the big and just, it's humbling to be in front of this giant thing that's so powerful that was here before us and be here after. But I also love the piece of a small like wooded lake and it's just, it's everything's calm. Therapeutic. You tweeted that I'm excited about Amazon's acquisition of iRobot. I think it's a super interesting, just given the trajectory of what you're part of, of these honestly small number of companies that are playing in this space that are like trying back to empathy, which has been a common thread throughout my entire career. And it's this idea of human connection. Once you build common ground with a person or a group of people, you build trust, you build loyalty, you build friendship. And then you can turn that into behavior change and motivation and persuasion. So it's like, empathy and emotions are just at the center of everything we do. And I think being from the Middle East, kind of this human connection is very strong. We have this running joke that if you come to Egypt for a visit, people will know everything about your life right away, right? I have no problems asking you about your personal life. There's no boundaries, really, no personal boundaries in terms of getting to know people. We get emotionally intimate very, very quickly. But I think people just get to know each other authentically, I guess. There isn't this superficial level of getting to know people. You just try to get to know people really deeply. Empathy is a part of that. Totally. Because you can put yourself in this person's shoe and kind of, yeah, imagine what challenges they're going through, and so I think I've definitely taken that with me. Generosity is another one too, like just being generous with your time and love and attention and even with your wealth, right? Even if you don't have a lot of it, you're still very generous. And I think that's another... Enjoying the humanity of other people. And so do you think there's a useful difference between men and women in that? In that aspect and empathy? Or is doing these kind of big general groups, does that hinder progress? Yeah, I actually don't want to overgeneralize. I mean, some of the men I know are like the most empathetic humans. Yeah, I strive to be empathetic. Yeah, you're actually very empathetic. Yeah, so I don't want to overgeneralize. Although one of the researchers I worked with when I was at Cambridge, Professor Simon Baron Cohen, he's Sacha Baron Cohen's cousin, and he runs the Autism Research Center at Cambridge, and he's written multiple books on autism. And one of his theories is the empathy scale, like the systemizers and the empathizers, and there's a disproportionate amount of computer scientists and engineers who are systemizers and perhaps not great empathizers, and then there's more men in that bucket, I guess, than women, and then there's more women in the empathizers bucket. So again, not to overgeneralize. I sometimes wonder about that. It's been frustrating to me how many, I guess, systemizers there are in the field of robotics. Yeah. It's actually encouraging to me because I care about, obviously, social robotics, and because there's more opportunity for people that are empathic. Exactly. I totally agree. Well, right? So it's nice. Yes. So every robotics I talk to, they don't see the human as interesting, as it's not exciting. You want to avoid the human at all costs. It's a safety concern to be touching the human, which it is, but it is also an opportunity for deep connection or collaboration or all that kind of stuff. And because most brilliant roboticists don't care about the human, it's an opportunity, in your case, it's a business opportunity too, but in general, an opportunity to explore those ideas. So in this beautiful journey to Cambridge, to UK, and then to America, what's the moment or moments that were most transformational for you as a scientist and as a leader? So you became an exceptionally successful CEO, founder, researcher, scientist, and so on. Was there a face shift there where, like, I can be somebody, I can really do something in this world? Yeah. So actually, just kind of a little bit of background. So the reason why I moved from Cairo to Cambridge, UK to do my PhD is because I had a very clear career plan. I was like, okay, I'll go abroad, get my PhD, going to crush it in three or four years, come back to Egypt and teach. It was very clear, very well laid out. Was topic clear or no? The topic, well, I did my PhD around building artificial emotional intelligence and looking at... But in your master plan ahead of time, when you're sitting by the mango tree, did you know it's going to be artificial intelligence? No, no, no, that I did not know. Although I think I kind of knew that I was going to be doing computer science, but I didn't know the specific area. But I love teaching. I mean, I still love teaching. So I just, yeah, I just wanted to go abroad, get a PhD, come back, teach. Why computer science? Can we just linger on that? What? Because you're such an empathic person who cares about emotion, humans and so on. Isn't, aren't computers cold and emotionless and just... We're changing that. Yeah, I know, but like, isn't that the, or did you see computers as the, having the capability to actually connect with humans? I think that was like my takeaway from my experience just growing up, like computers sit at the center of how we connect and communicate with one another, right? Or technology in general. Like I remember my first experience being away from my parents. We communicated with a fax machine, but thank goodness for the fax machine, because we could send letters back and forth to each other. This was pre emails and stuff. So I think, I think there's, I think technology can be not just transformative in terms of productivity, et cetera. It actually does change how we connect with one another. Can I just defend the fax machine? There's something like the haptic feel because the email is all digital. There's something really nice. I still write letters to people. There's something nice about the haptic aspect of the fax machine, because you still have to press, you still have to do something in the physical world to make this thing a reality. Right, and then it like comes out as a printout and you can actually touch it and read it. Yeah. There's something, there's something lost when it's just an email. Obviously I wonder how we can regain some of that in the digital world, which goes to the metaverse and all those kinds of things. We'll talk about it anyway. So, actually do you question on that one? Do you still, do you have photo albums anymore? Do you still print photos? No, no, but I'm a minimalist. Okay. So it was one of the, one of the painful steps in my life was to scan all the photos and let go of them and then let go of all my books. You let go of your books? Yeah. Switch to Kindle, everything Kindle. Yeah. So I thought, I thought, okay, think 30 years from now, nobody's going to have books anymore. The technology of digital books is going to get better and better and better. Are you really going to be the guy that's still romanticizing physical books? Are you going to be the old man on the porch who's like kids? Yes. So just get used to it because it was, it felt, it still feels a little bit uncomfortable to read on a Kindle, but get used to it. Like you always, I mean, I'm trying to learn new programming language is always, like with technology, you have to kind of challenge yourself to adapt to it. You know, I forced myself to use TikTok. No, that thing doesn't need much forcing. It pulls you in like a, like the worst kind of, or the best kind of drug. Anyway, yeah. So yeah, but I do love haptic things. There's a magic to the haptic. Even like touchscreens, it's tricky to get right, to get the experience of a button. Yeah. Anyway, what were we talking about? So AI, so the journey, your whole plan was to come back to Cairo and teach. Right. And then. What did the plan go wrong? Yeah, exactly. Right. And then I get to Cambridge and I fall in love with the idea of research. Right. And kind of embarking on a path. Nobody's explored this path before. You're building stuff that nobody's built before. And it's challenging and it's hard. And there's a lot of nonbelievers. I just totally love that. And at the end of my PhD, I think it's the meeting that changed the trajectory of my life. Professor Roslyn Picard, who's, she runs the Affective Computing Group at the MIT Media Lab. I had read her book. I, you know, I was like following, following, following all her research. AKA Ros. Yes, AKA Ros. Yes. And she was giving a talk at a pattern recognition conference in Cambridge. And she had a couple of hours to kill. So she emailed the lab and she said, you know, if any students want to meet with me, like, just, you know, sign up here. And so I signed up for slot and I spent like the weeks leading up to it preparing for this meeting and I want to show her a demo of my research and everything. And we met and we ended up hitting it off. Like we totally clicked. And at the end of the meeting, she said, do you want to come work with me as a postdoc at MIT? And this is what I told her. I was like, okay, this would be a dream come true, but there's a husband waiting for me in Cairo. I kind of have to go back. Yeah. She said, it's fine. Just commute. And I literally started commuting between Cairo and Boston. Yeah, it was, it was a long commute. to have an impact on human beings. So the, it is an interesting moment in time that Amazon would acquire iRobot. You tweet, I imagine a future where home robots are as ubiquitous as microwaves or toasters. Here are three reasons why I think this is exciting. If you remember, I can look it up, but what, why is this exciting to you? I mean, I think the first reason why this is exciting, I kind of remember the exact like order in which I put them, but one is just, it's, it's going to be an incredible platform for understanding our behaviors within the home, right? Like you know, if you think about Roomba, which is, you know, the robot vacuum cleaner, the flagship product of iRobot at the moment, it's like running around your home, understanding the layout, it's understanding what's clean and what's not. How often do you clean your house? And all of these like behaviors are a piece of the puzzle in terms of understanding who you are as a consumer. And I think that could be, again, used in really meaningful ways, not just to recommend better products or whatever, but actually to improve your experience as a human being. So I think, I think that's very interesting. I think the natural evolution of these robots in the, in the home. So it's, it's interesting, Roomba isn't really a social robot, right, at the moment. But I once interviewed one of the chief engineers on the Roomba team, and he talked about how people named their Roombas. And if the Roomba broke down, they would call in and say, you know, my Roomba broke down and the company would say, well, we'll just send you a new one. And no, no, no, Rosie, like you have to like, yeah, I want you to fix this particular robot. So people have already built like interesting emotional connections with these home robots. And I think that, again, that provides a platform for really interesting things to, to just motivate change. Like it could help you. I mean, one of the companies that spun out of MIT, Catalia Health, the guy who started it spent a lot of time building robots that help with weight management. So weight management, sleep, eating better, yeah, all of these things. Well, if I'm being honest, Amazon does not exactly have a track record of winning over people in terms of trust. Now that said, it's a really difficult problem for a human being to let a robot in their home that has a camera on it. Right. That's really, really, really tough. And I think Roomba actually, I have to think about this, but I'm pretty sure now or for some time already has had cameras because they're doing the, the, the most recent Roomba. I have so many Roombas. Oh, you actually do? Well, I programmed it. I don't use a Roomba for VECO. People that have been to my place, they're like, yeah, you definitely don't use these Roombas. That could be a good, I can't tell like the valence of this comment. Was it a compliment or like? No, it's a giant, it's just a bunch of electronics everywhere. There's, I have six or seven computers, I have robots everywhere, Lego robots, I have small robots and big robots and it's just giant, just piles of robot stuff and yeah. But including the Roombas, they're, they're, they're being used for their body and intelligence, but not for their purpose. I have, I've changed them, repurposed them for other purposes, for deeper, more meaningful purposes than just like the Bota Roba, which is, you know, brings a lot of people happiness, I'm sure. They have a camera because the thing they advertised, I had my own camera still, but the, the, the camera on the new Roomba, they have like state of the art poop detection as they advertised, which is a very difficult, apparently it's a big problem for, for vacuum cleaners is, you know, if they go over like dog poop, it just runs it, it runs it over and creates a giant mess. So they have like, and apparently they collected like a huge amount of data and different shapes and looks and whatever of poop and then now they're able to avoid it and so on. They're very proud of this. So there is a camera, but you don't think of it as having a camera. Yeah. You don't think of it as having a camera because you've grown to trust that, I guess, because our phones, at least most of us seem to trust this phone, even though there's a camera looking directly at you. I think that if you trust that the company is taking security very seriously, I actually don't know how that trust was earned with smartphones, I think it just started to provide a lot of positive value to your life where you just took it in and then the company over time has shown that it takes privacy very seriously, that kind of stuff. But I just, Amazon is not always in the, in its social robots communicated. This is a trustworthy thing, both in terms of culture and competence, because I think privacy is not just about what do you intend to do, but also how well, how good are you at doing that kind of thing. So that's a really hard problem to solve. But I mean, but a lot of us have Alexas at home and I mean, Alexa could be listening in the whole time, right? And doing all sorts of nefarious things with the data. Yeah. Hopefully it's not, but I don't think it is. But you know, Amazon is not, it's such a tricky thing for a company to get right, which is like to earn the trust. I don't think Alexa's earned people's trust quite yet. Yeah. I think it's, it's not there quite yet. I agree. They struggle with this kind of stuff. In fact, when these topics are brought up, people are always get like nervous. And I think if you get nervous about it, that mean that like the way to earn people's trust is not by like, Ooh, don't talk about this. It's just be open, be frank, be transparent, and also create a culture of like where it radiates at every level from engineer to CEO that like you're good people that have a common sense idea of what it means to respect basic human rights and the privacy of people and all that kind of stuff. And I think that propagates throughout the, that's the best PR, which is like over time you understand that these are good folks doing good things. Anyway, speaking of social robots, have you heard about Tesla, Tesla bot, the humanoid robot? Yes, I have. Yes, yes, yes. But I don't exactly know what it's designed to do to you. You probably do. No, I know it's designed to do, but I have a different perspective on it, but it's designed to, it's a humanoid form and it's designed to, for automation tasks in the same way that industrial robot arms automate tasks in the factory. So it's designed to automate tasks in the factory. But I think that humanoid form, as we were talking about before, is one that we connect with as human beings. Anything legged, obviously, but the humanoid form especially, we anthropomorphize it most intensely. And so the possibility to me, it's exciting to see both Atlas developed by Boston Dynamics and anyone, including Tesla, trying to make humanoid robots cheaper and more effective. The obvious way it transforms the world is social robotics to me versus automation of tasks in the factory. So yeah, I just wanted, in case that was something you were interested in, because I find its application of social robotics super interesting. We did a lot of work with Pepper, Pepper the robot, a while back. We were like the emotion engine for Pepper, which is Softbank's humanoid robot. How tall is Pepper? It's like... Yeah, like, I don't know, like five foot maybe, right? Yeah. Yeah. Pretty, pretty big. Pretty big. It's designed to be at like airport lounges and, you know, retail stores, mostly customer service, right? Hotel lobbies, and I mean, I don't know where the state of the robot is, but I think it's very promising. I think there are a lot of applications where this can be helpful. I'm also really interested in, yeah, social robotics for the home, right? Like that can help elderly people, for example, transport things from one location of the mind to the other, or even like just have your back in case something happens. Yeah, I don't know. I do think it's a very interesting space. It seems early though. Do you feel like the timing is now? Yes, 100%. So it always seems early until it's not, right? Right, right, right. I think the time, I definitely think that the time is now, like this decade for social robots. Whether the humanoid form is right, I don't think so, no. I don't, I think the, like if we just look at Jibo as an example, I feel like most of the problem, the challenge, the opportunity of social connection between an AI system and a human being does not require you to also solve the problem of robot manipulation and bipedal mobility. So I think you could do that with just a screen, honestly, but there's something about the interface of Jibo where it can rotate and so on that's also compelling. But you get to see all these robot companies that fail, incredible companies like Jibo and even, I mean, the iRobot in some sense is a big success story that it was able to find a niche thing and focus on it, but in some sense it's not a success story because they didn't build any other robot, like any other, it didn't expand into all kinds of robotics. Like once you're in the home, maybe that's what happens with Amazon is they'll flourish into all kinds of other robots. But do you have a sense, by the way, why it's so difficult to build a robotics company? Like why so many companies have failed? I think it's like you're building a vertical stack, right? Like you are building the hardware plus the software and you find you have to do this at a cost that makes sense. So I think Jibo was retailing at like, I don't know, like $800, like $700, $800, which for the use case, right, there's a dissonance there. It's too high. So I think cost of building the whole platform in a way that is affordable for what value it's bringing, I think that's a challenge. I think for these home robots that are going to help you do stuff around the home, that's a challenge too, like the mobility piece of it. That's hard. Well, one of the things I'm really excited with Tesla Bot is the people working on it. And that's probably the criticism I would apply to some of the other folks who worked on social robots is the people working on Tesla Bot know how to, they're focused on and know how to do mass manufacture and create a product that's super cheap. Very cool. That's the focus. The engineering focus isn't, I would say that you can also criticize them for that, is they're not focused on the experience of the robot. They're focused on how to get this thing to do the basic stuff that the humanoid form requires to do it as cheap as possible. Then the fewest number of actuators, the fewest numbers of motors, the increasing efficiency, they decrease the weight, all that kind of stuff. So that's really interesting. I would say that Jibo and all those folks, they focus on the design, the experience, all of that, and it's secondary how to manufacture. Right. So you have to think like the Tesla Bot folks from first principles, what is the fewest number of components, the cheapest components, how can I build it as much in house as possible without having to consider all the complexities of a supply chain, all that kind of stuff. It's interesting. Because if you have to build a robotics company, you're not building one robot, you're building hopefully millions of robots, you have to figure out how to do that where the final thing, I mean, if it's Jibo type of robot, is there a reason why Jibo, like we can have this lengthy discussion, is there a reason why Jibo has to be over $100? It shouldn't be. Right. Like the basic components. Right. Components of it. Right. Like you could start to actually discuss like, okay, what is the essential thing about Jibo? How much, what is the cheapest way I can have a screen? What's the cheapest way I can have a rotating base? Right. All that kind of stuff. Right, get down, continuously drive down costs. Speaking of which, you have launched an extremely successful companies, you have helped others, you've invested in companies. Can you give advice on how to start a successful company? I would say have a problem that you really, really, really want to solve, right? Something that you're deeply passionate about. And honestly, take the first step. Like that's often the hardest. And don't overthink it. Like, you know, like this idea of a minimum viable product or a minimum viable version of an idea, right? Like, yes, you're thinking about this, like a humongous, like super elegant, super beautiful thing. What, like reduce it to the littlest thing you can bring to market that can solve a problem or that can, you know, that can help address a pain point that somebody has. They often tell you, like, start with a customer of one, right? If you can solve a problem for one person, then there's probably going to be yourself or some other person. Right. Pick a person. Exactly. It could be you. Yeah, that's actually often a good sign that if you enjoy a thing, enjoy a thing where you have a specific problem that you'd like to solve, that's a good, that's a good end of one to focus on. What else, what else is there to actually step one is the hardest, but there's other steps as well, right? I also think like who you bring around the table early on is so key, right? Like being clear on, on what I call like your core values or your North Star. It might sound fluffy, but actually it's not. So and Roz and I feel like we did that very early on. We sat around her kitchen table and we said, okay, there's so many applications of this technology. How are we going to draw the line? How are we going to set boundaries? We came up with a set of core values that in the hardest of times we fell back on to determine how we make decisions. And so I feel like just getting clarity on these core, like for us, it was respecting people's privacy, only engaging with industries where it's clear opt in. So for instance, we don't do any work in security and surveillance. So things like that, just getting, we very big on, you know, one of our core values is human connection and empathy, right? And that is, yes, it's an AI company, but it's about people. Well, these are all, they become encoded in how we act, even if you're a small, tiny team of two or three or whatever. So I think that's another piece of advice. So what about finding people, hiring people? If you care about people as much as you do, like this, it seems like such a difficult thing to hire the right people. I think early on as a startup, you want people who have, who share the passion and the conviction because it's going to be tough. Like I've yet to meet a startup where it was just a straight line to success, right? Even not just startup, like even everyday people's lives, right? You always like run into obstacles and you run into naysayers and you need people who are believers, whether they're people on your team or even your investors. You need investors who are really believers in what you're doing, because that means they will stick with you. They won't give up at the first obstacle. I think that's important. What about raising money? What about finding investors, first of all, raising money, but also raising money from the right sources from that ultimately don't hinder you, but help you, empower you, all that kind of stuff. What advice would you give there? You successfully raised money many times in your life. Yeah. Again, it's not just about the money. It's about finding the right investors who are going to be aligned in terms of what you want to build and believe in your core values. For example, especially later on, in my latest round of funding, I try to bring in investors that really care about the ethics of AI and the alignment of vision and mission and core values is really important. It's like you're picking a life partner. It's the same kind of... So you take it that seriously for investors? Yeah, because they're going to have to stick with you. You're stuck together. For a while anyway. Yeah. Maybe not for life, but for a while, for sure. For better or worse. I forget what the vowels usually sound like. For better or worse? Through something. Yeah. Oh boy. Yeah. Anyway, it's romantic and deep and you're in it for a while. So it's not just about the money. You tweeted about going to your first capital camp investing get together and that you learned a lot. So this is about investing. So what have you learned from that? What have you learned about investing in general from both because you've been on both ends of it? I mean, I try to use my experience as an operator now with my investor hat on when I'm identifying companies to invest in. First of all, I think the good news is because I have a technology background and I really understand machine learning and computer vision and AI, et cetera, I can apply that level of understanding because everybody says they're an AI company or they're an AI tech. And I'm like, no, no, no, no, no, show me the technology. So I can do that level of diligence, which I actually love. And then I have to do the litmus test of, if I'm in a conversation with you, am I excited to tell you about this new company that I just met? And if I'm an ambassador for that company and I'm passionate about what they're doing, I usually use that. Yeah. That's important to me when I'm investing. So that means you actually can explain what they're doing and you're excited about it. Exactly. Exactly. Thank you for putting it so succinctly, like rambling, but exactly that's it. No, but sometimes it's funny, but sometimes it's unclear exactly. I'll hear people tell me, you know, in the talk for a while and it sounds cool, like they paint a picture of a world, but then when you try to summarize it, you're not exactly clear. Like maybe what the core powerful idea is, like you can't just build another Facebook or there has to be a core, simple to explain idea that then you can or can't get excited about, but it's there, it's right there. Yeah. But how do you ultimately pick who you think will be successful? It's not just about the thing you're excited about, like there's other stuff. Right. And then there's all the, you know, with early stage companies, like pre seed companies, which is where I'm investing, sometimes the business model isn't clear yet, or the go to market strategy isn't clear. There's usually like, it's very early on that some of these things haven't been hashed out, which is okay. So the way I like to think about it is like, if this company is successful, will this be a multi billion slash trillion dollar market, you know, or company? And so that's definitely a lens that I use. What's pre seed? What are the different stages and what's the most exciting stage and what's, or no, what's interesting about every stage, I guess. Yeah. So pre seed is usually when you're just starting out, you've maybe raised the friends and family rounds. So you've raised some money from people, you know, and you're getting ready to take your first institutional check in, like first check from an investor. And I love the stage. There's a lot of uncertainty. Some investors really don't like the stage because the financial models aren't there. Often the teams aren't even like formed really, really early. But to me, it's like a magical stage because it's the time when there's so much conviction, so much belief, almost delusional, right? And there's a little bit of naivete around with founders at the stage. I just love it. It's contagious. And I love that I can, often they're first time founders, not always, but often they're first time founders and I can share my experience as a founder myself and I can empathize, right? And I can almost, I create a safe ground where, because, you know, you have to be careful what you tell your investors, right? And I will often like say, I've been in your shoes as a founder. You can tell me if it's challenging, you can tell me what you're struggling with. It's okay to vent. So I create that safe ground and I think that's a superpower. Yeah. You have to, I guess you have to figure out if this kind of person is going to be able to ride the roller coaster, like of many pivots and challenges and all that kind of stuff. And if the space of ideas they're working in is interesting, like the way they think about the world. Yeah. Because if it's successful, the thing they end up with might be very different, the reason it's successful for them. Actually, you know, I was going to say the third, so the technology is one aspect, the market or the idea, right, is the second and the third is the founder, right? Is this somebody who I believe has conviction, is a hustler, you know, is going to overcome obstacles? Yeah, I think that is going to be a great leader, right? Like as a startup, as a founder, you're often, you are the first person and your role is to bring amazing people around you to build this thing. And so you're an evangelist, right? So how good are you going to be at that? So I try to evaluate that too. You also in the tweet thread about it, mention, is this a known concept, random rich dudes are RDS and saying that there should be like random rich women, I guess. What's the dudes, what's the dudes version of women, the women version of dudes, ladies? I don't know. I don't know. What's, what's, is this a technical term? Is this known? Random rich dudes? I didn't make that up, but I was at this capital camp, which is a get together for investors of all types. And there must have been maybe 400 or so attendees, maybe 20 were women. It was just very disproportionately, you know, male dominated, which I'm used to. I think you're used to this kind of thing. I'm used to it, but it's still surprising. And as I'm raising money for this fund, so my fund partner is a guy called Rob May, who's done this before. So I'm new to the investing world, but he's done this before. Most of our investors in the fund are these, I mean, awesome. I'm super grateful to them. Random just rich guys. I'm like, where are the rich women? So I'm really adamant in both investing in women led AI companies, but I also would love to have women investors be part of my fund because I think that's how we drive change. Yeah. So that takes time, of course, but there's been quite a lot of progress, but yeah, for the next Mark Zuckerberg to be a woman and all that kind of stuff, because that's just like a huge number of wealth generated by women and then controlled by women and allocated by women and all that kind of stuff. And then beyond just women, just broadly across all different measures of diversity and so on. Let me ask you to put on your wise sage hat. So you already gave advice on startups and just advice for women, but in general advice for folks in high school or college today, how to have a career they can be proud of, how to have a life they can be proud of. I suppose you have to give this kind of advice to your kids. Yeah. Well, here's the number one advice that I give to my kids. My daughter's now 19 by the way, and my son's 13 and a half, so they're not little kids anymore. Does it break your heart? It does. They're awesome. They're my best friends, but yeah, I think the number one advice I would share is embark on a journey without attaching to outcomes and enjoy the journey, right? So we often were so obsessed with the end goal that doesn't allow us to be open to different endings of a journey or a story, so you become like so fixated on a particular path. You don't see the beauty in the other alternative path, and then you forget to enjoy the journey because you're just so fixated on the goal, and I've been guilty of that for many, many years of my life, and I'm now trying to make the shift of, no, no, no, I'm going to again trust that things are going to work out and it'll be amazing and maybe even exceed your dreams. We have to be open to that. Yeah. Taking a leap into all kinds of things. I think you tweeted like you went on vacation by yourself or something like this. I know. Yes, and just going, just taking the leap. Doing it. Totally doing it. And enjoying it, enjoying the moment, enjoying the weeks, enjoying not looking at some kind of career ladder, next step and so on. Yeah, there's something to that, like over planning too. I'm surrounded by a lot of people that kind of, so I don't plan. You don't? No. Do you not do goal setting? My goal setting is very like, I like the affirmations, it's very, it's almost, I don't know how to put it into words, but it's a little bit like what my heart yearns for kind of, and I guess in the space of emotions more than in the space of like, this will be like in the rational space because I just try to picture a world that I would like to be in and that world is not clearly pictured, it's mostly in the emotional world. I mean, I think about that from robots because I have this desire, I've had it my whole life to, well, it took different shapes, but I think once I discovered AI, the desire was to, I think in the context of this conversation could be easily easier described as basically a social robotics company and that's something I dreamed of doing and well, there's a lot of complexity to that story, but that's the only thing, honestly, I dream of doing. So I imagine a world that I could help create, but it's not, there's no steps along the way and I think I'm just kind of stumbling around and following happiness and working my ass off in almost random, like an ant does in random directions, but a lot of people, a lot of successful people around me say this, you should have a plan, you should have a clear goal, you have a goal at the end of the month, you have a goal at the end of the month, I don't, I don't, I don't and there's a balance to be struck, of course, but there's something to be said about really making sure that you're living life to the fullest, that goals can actually get in the way of. So one of the best, like kind of most, what do you call it when it challenges your brain, what do you call it? The only thing that comes to mind, and this is me saying is the mindfuck, but yes. Okay. Okay. Okay. Something like that. Yes. Super inspiring talk. Kenneth Stanley, he was at OpenAI, he just laughed and he has a book called Why Greatness Can't Be Planned and it's actually an AI book. So and he's done all these experiments that basically show that when you over optimize, you, like the trade off is you're less creative, right? And to create true greatness and truly creative solutions to problems, you can't over plan it. You can't. And I thought that was, and so he generalizes it beyond AI and he talks about how we apply that in our personal life and in our organizations and our companies, which are over KPIs, right? Like look at any company in the world and it's all like, these aren't the goals, these aren't weekly goals and the sprints and then the quarterly goals, blah, blah, blah. And he just shows with a lot of his AI experiments that that's not how you create truly game changing ideas. So there you go. Yeah, yeah. You can. He's awesome. Yeah. There's a balance of course. That's yeah, many moments of genius will not come from planning and goals, but you still have to build factories and you still have to manufacture and you still have to deliver and there's still deadlines and all that kind of stuff. And that for that, it's good to have goals. I do goal setting with my kids, we all have our goals, but, but, but I think we're starting to morph into more of these like bigger picture goals and not obsess about like, I don't know, it's hard. Well, I honestly think with, especially with kids, it's better, much, much better to have a plan and have goals and so on because you have to, you have to learn the muscle of like what it feels like to get stuff done. Yeah. And once you learn that, there's flexibility for me because I spend most of my life with goal setting and so on. So like I've gotten good with grades and school. I mean, school, if you want to be successful at school, yeah, I mean the kind of stuff in high school and college, the kids have to do in terms of managing their time and getting so much stuff done. It's like, you know, taking five, six, seven classes in college, they're like that would break the spirit of most humans if they took one of them later in life, it's like really difficult stuff, especially engineering curricula. So I think you have to learn that skill, but once you learn it, you can maybe, cause you're, you can be a little bit on autopilot and use that momentum and then allow yourself to be lost in the flow of life. You know, just kind of, or also give like, I worked pretty hard to allow myself to have the freedom to do that. That's really, that's a tricky freedom to have because like a lot of people get lost in the rat race and they, and they also like financially, they, whenever you get a raise, they'll get like a bigger house or something like this. I put very, so like, there's, you're always trapped in this race, I put a lot of emphasis on living like below my means always. And so there's a lot of freedom to do whatever, whatever the heart desires that that's a relief, but everyone has to decide what's the right thing, what's the right thing for them. For some people having a lot of responsibilities, like a house they can barely afford or having a lot of kids, the responsibility side of that is really, helps them get their shit together. Like, all right, I need to be really focused and get, some of the most successful people I know have kids and the kids bring out the best in them. They make them more productive and less productive. Right, it's accountability. Yeah. It's an accountability thing, absolutely. And almost something to actually live and fight and work for, like having a family, it's fascinating to see because you would think kids would be a hit on productivity, but they're not, for a lot of really successful people, they really like, they're like an engine of. Right, efficiency. Oh my God. Yeah. Yeah. It's weird. Yeah. I mean, it's beautiful. It's beautiful to see. And also a source of happiness. Speaking of which, what role do you think love plays in the human condition, love? I think love is, yeah, I think it's why we're all here. I think it would be very hard to live life without love in any of its forms, right? Yeah, that's the most beautiful of forms that human connection takes, right? Yeah. And everybody wants to feel loved, right, in one way or another, right? And to love. Yeah. It feels good. And to love too, totally. Yeah, I agree with that. Both of it. Yeah. I'm not even sure what feels better. Both, both like that. Yeah, to give and to give love too, yeah. And it is like we've been talking about an interesting question, whether some of that, whether one day we'll be able to love a toaster. Okay. It's some small. I wasn't quite thinking about that when I said like, yeah, like we all need love and give love. That's all I was thinking about. Okay. I was thinking about Brad Pitt and toasters. Okay, toasters, great. All right. Well, I think we started on love and ended on love. This was an incredible conversation, Rhonda. Thank you so much. Thank you. You're an incredible person. Thank you for everything you're doing in AI, in the space of just caring about humanity, caring about emotion, about love, and being an inspiration to a huge number of people in robotics, in AI, in science, in the world in general. So thank you for talking to me. It's an honor. Thank you for having me. And you know, I'm a big fan of yours as well. So it's been a pleasure. Thanks for listening to this conversation with Rhonda Alkalioubi. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Helen Keller. The best and most beautiful things in the world cannot be seen or even touched. They must be felt with the heart. Thank you for listening and hope to see you next time. And I didn't, I did that like every few weeks I would, you know, hop on a plane and go to Boston. But that, that changed the trajectory of my life. There was no, I kind of outgrew my dreams, right? I didn't want to go back to Egypt anymore and be faculty. Like that was no longer my dream. I had a dream. What was the, what was it like to be at MIT? What was that culture shock? You mean America in general, but also, I mean, Cambridge has its own culture, right? So what was MIT like and what was America like? I think, I wonder if that's similar to your experience at MIT. I was just, at the Media Lab in particular, I was just really, impressed is not the right word. I didn't expect the openness to like innovation and the acceptance of taking a risk and failing. Like failure isn't really accepted back in Egypt, right? You don't want to fail. Like there's a fear of failure, which I think has been hardwired in my brain. But you get to MIT and it's okay to start things. And if they don't work out, like it's okay. You pivot to another idea. And that kind of thinking was just very new to me. That's liberating. Well, Media Lab, for people who don't know, MIT Media Lab is its own beautiful thing because they, I think more than other places at MIT, reach for big ideas. And like they try, I mean, I think, I mean, depending of course on who, but certainly with Roslyn, you try wild stuff, you try big things and crazy things and also try to take things to completion so you can demo them. So always, always, always have a demo. Like if you go, one of the sad things to me about robotics labs at MIT, and there's like over 30, I think, is like, usually when you show up to a robotics lab, there's not a single working robot, they're all broken. All the robots are broken. The robots are broken, which is like the normal state of things because you're working on them. But it would be nice if we lived in a world where robotics labs had some robots functioning. One of my like favorite moments that just sticks with me, I visited Boston Dynamics and there was a, first of all, seeing so many spots, so many legged robots in one place. I'm like, I'm home. But the, yeah. This is where I was built. The cool thing was just to see there was a random robot spot was walking down the hall. It's probably doing mapping, but it looked like he wasn't doing anything and he was wearing he or she, I don't know. But it, well, I like, in my mind, there are people, they have a backstory, but this one in particular definitely has a backstory because he was wearing a cowboy hat. So I just saw a spot robot with a cowboy hat walking down the hall and there was just this feeling like there's a life, like he has a life. He probably has to commute back to his family at night. Like there's a, there's a feeling like there's life instilled in this robot and it's magical. I don't know. It was, it was kind of inspiring to see. Did it say hello to, did he say hello to you? No, it's very, there's a focus nature to the robot. No, no, listen. I love competence and focus and great. Like he was not going to get distracted by the, the shallowness of small talk. There's a job to be done and he was doing it. So anyway, the fact that it was working is a beautiful thing. And I think Media Lab really prides itself on trying to always have a thing that's working that you could show off. Yes. We used to call it a demo or die. You, you could not, yeah, you could not like show up with like PowerPoint or something. You actually had to have a working, you know what, my son who is now 13, I don't know if this is still his life long goal or not, but when he was a little younger, his dream is to build an island that's just inhabited by robots, like no humans. He just wants all these robots to be connecting and having fun and there you go. Does he have human, does he have an idea of which robots he loves most? Is it, is it Roomba like robots? Is it humanoid robots? Robot dogs, or it's not clear yet. We used to have a Jibo, which was one of the MIT Media Lab spin outs and he used to love the giant head that spins and rotate and it's an eye or like not glowing like Cal 9000, but the friendly version. He loved that. And then he just loves, uh, um, yeah, he just, he, I think he loves all forms of robots actually. So embodied intelligence. Yes. I like, I personally like legged robots, especially, uh, anything that can wiggle its butt. No, that's not the definition of what I love, but that's just technically what I've been working on recently. Except I have a bunch of legged robots now in Austin and I've been doing, I was, I've been trying to, uh, have them communicate affection with their body in different ways just for art, for art really. Cause I love the idea of walking around with the robots, like, uh, as you would with a dog. I think it's inspiring to a lot of people, especially young people. Like kids love, kids love it. Parents like adults are scared of robots, but kids don't have this kind of weird construction of the world that's full of evil. They love cool things. Yeah. I remember when Adam was in first grade, so he must have been like seven or so. I went in to his class with a whole bunch of robots and like the emotion AI demo and da da. And I asked the kids, I was like, do you, would you kids want to have a robot, you know, robot friend or robot companion? Everybody said yes. And they wanted it for all sorts of things, like to help them with their math homework and to like be a friend. So there's, it just struck me how there was no fear of robots was a lot of adults have that like us versus them. Yeah, none of that. Of course you want to be very careful because you still have to look at the lessons of history and how robots can be used by the power centers of the world to abuse your rights and all that kind of stuff. But mostly it's good to enter anything new with an excitement and an optimism. Speaking of Roz, what have you learned about science and life from Rosalind Picard? Oh my God, I've learned so many things about life from Roz. I think the thing I learned the most is perseverance. When I first met Roz, we applied and she invited me to be her postdoc. We applied for a grant to the National Science Foundation to apply some of our research to autism. And we got back. We were rejected. Rejected. Yeah. And the reasoning was... The first time you were rejected for fun, yeah. Yeah, it was, and I basically, I just took the rejection to mean, okay, we're rejected. It's done, like end of story, right? And Roz was like, it's great news. They love the idea. They just don't think we can do it. So let's build it, show them, and then reapply. And it was that, oh my God, that story totally stuck with me. And she's like that in every aspect of her life. She just does not take no for an answer. To reframe all negative feedback. As a challenge. As a challenge. As a challenge. Yes, they liked this. Yeah, yeah, yeah. It was a riot. What else about science in general? About how you see computers and also business and just everything about the world. She's a very powerful, brilliant woman like yourself. So is there some aspect of that too? Yeah, I think Roz is actually also very faith driven. She has this like deep belief in conviction. Yeah, and in the good in the world and humanity. And I think that was meeting her and her family was definitely like a defining moment for me because that was when I was like, wow, like you can be of a different background and religion and whatever and you can still have the same core values. So that was, that was, yeah. I'm grateful to her. Roz, if you're listening, thank you. Yeah, she's great. She's been on this podcast before. I hope she'll be on, I'm sure she'll be on again. And you were the founder and CEO of Effektiva, which is a big company that was acquired by another big company, SmartEye. And you're now the deputy CEO of SmartEye. So you're a powerful leader. You're brilliant. You're a brilliant scientist. A lot of people are inspired by you. What advice would you give, especially to young women, but people in general who dream of becoming powerful leaders like yourself in a world where perhaps, in a world that perhaps doesn't give them a clear, easy path to do so, whether we're talking about Egypt or elsewhere? You know, hearing you kind of describe me that way, kind of encapsulates, I think what I think is the biggest challenge of all, which is believing in yourself, right? I have had to like grapple with this, what I call now the Debbie Downer voice in my head. The kind of basically, it's just chattering all the time. It's basically saying, oh, no, no, no, no, you can't do this. Like you're not going to raise money. You can't start a company. Like what business do you have, like starting a company or running a company or selling a company? Like you name it. It's always like. And I think my biggest advice to not just women, but people who are taking a new path and, you know, they're not sure, is to not let yourself and let your thoughts be the biggest obstacle in your way. And I've had to like really work on myself to not be my own biggest obstacle. So you got that negative voice. Yeah. So is that? Am I the only one? I don't think I'm the only one. No, I have that negative voice. I'm not exactly sure if it's a bad thing or a good thing. I've been really torn about it because it's been a lifelong companions. It's hard to know. It's kind of, it drives productivity and progress, but it can hold you back from taking big leaps. I think the best I can say is probably you have to somehow be able to control it, to turn it off when it's not useful and turn it on when it's useful. Like I have from almost like a third person perspective. Right. Somebody who's sitting there like. Yeah. Like, because it is useful to be critical. Like after, I just gave a talk yesterday. At MIT and I was just, there's so much love and it was such an incredible experience. So many amazing people I got a chance to talk to, but afterwards when I went home and just took this long walk, it was mostly just negative thoughts about me. I don't like one basic stuff like I don't deserve any of it. And second is like, like, why did you, that was so bad. Second is like, like, why did you, that was so dumb that you said this, that's so dumb. Like you should have prepared that better. Why did you say this? But I think it's good to hear that voice out. All right. And like sit in that. And ultimately I think you grow from that. Now, when you're making really big decisions about funding or starting a company or taking a leap to go to the UK or take a leap to go to America to work in Media Lab though. Yeah. There's, that's, you should be able to shut that off then because you should have like this weird confidence, almost like faith that you said before that everything's going to work out. So take the leap of faith. Take the leap of faith. Despite all the negativity. I mean, there's, there's, there's some of that. You, you actually tweeted a really nice tweet thread. It says, quote, a year ago, a friend recommended I do daily affirmations and I was skeptical, but I was going through major transitions in my life. So I gave it a shot and it set me on a journey of self acceptance and self love. So what was that like? Can you maybe talk through this idea of affirmations and how that helped you? Yeah. Because really like I'm just like me, I'm a kind, I'd like to think of myself as a kind person in general, but I'm kind of mean to myself sometimes. Yeah. And so I've been doing journaling for almost 10 years now. I use an app called Day One and it's awesome. I just journal and I use it as an opportunity to almost have a conversation with the Debbie Downer voice in my, it's like a rebuttal, right? Like Debbie Downer says, oh my God, like you, you know, you won't be able to raise this round of funding. I'm like, okay, let's talk about it. I have a track record of doing X, Y, and Z. I think I can do this. And it's literally like, so I wouldn't, I don't know that I can shut off the voice, but I can have a conversation with it. And it just, it just, and I bring data to the table, right? Nice. So that was the journaling part, which I found very helpful. But the affirmation took it to a whole next level and I just love it. I'm a year into doing this and you literally wake up in the morning and the first thing you do, I meditate first and then I write my affirmations and it's the energy I want to put out in the world that hopefully will come right back to me. So I will say, I always start with my smile lights up the whole world. And I kid you not, like people in the street will stop me and say, oh my God, like we love your smile. Like, yes. So, so my affirmations will change depending on, you know, what's happening this day. Is it funny? I know. Don't judge, don't judge. No, that's not, laughter's not judgment. It's just awesome. I mean, it's true, but you're saying affirmations somehow help kind of, I mean, what is it that they do work to like remind you of the kind of person you are and the kind of person you want to be, which actually may be in reverse order, the kind of person you want to be. And that helps you become the kind of person you actually are. It's just, it's, it brings intentionality to like what you're doing. Right. And so, by the way, I was laughing because my affirmations, which I also do are the opposite. Oh, you do? Oh, what do you do? I don't, I don't have a, my smile lights up the world. Maybe I should add that because like, I, I have, I just, I have, oh boy, it's, it's much more stoic, like about focus, about this kind of stuff, but the joy, the emotion that you're just in that little affirmation is beautiful. So maybe I should add that. I have some, I have some like focused stuff, but that's usually. But that's a cool start. It's after all the like smiling and playful and joyful and all that. And then it's like, okay, I kick butt. Let's get shit done. Right. Let's get shit done affirmation. Okay, cool. So like what else is on there? What else is on there? Well, I, I have, I'm also, I'm, I'm a magnet for all sorts of things. So I'm an amazing people magnet. I attract like awesome people into my universe. That's an actual affirmation. Yes. That's great. Yeah. So that, that's, and that, yeah. And that somehow manifests itself into like in working. I think so. Yeah. Like, can you speak to like why it feels good to do the affirmations? I honestly think it just grounds the day. And then it allows me to, instead of just like being pulled back and forth, like throughout the day, it just like grounds me. I'm like, okay, like this thing happened. It's not exactly what I wanted it to be, but I'm patient. Or I'm, you know, I'm, I trust that the universe will do amazing things for me, which is one of my other consistent affirmations. Or I'm an amazing mom. Right. And so I can grapple with all the feelings of mom guilt that I have all the time. Or here's another one. I'm a love magnet. And I literally say, I will kind of picture the person that I'd love to end up with. And I write it all down and it hasn't happened yet, but it. What are you, what are you picturing? This is Brad Pitt. Because that's what I picture. Okay. That's what you picture? Yeah. Okay. On the, on the running, holding hands, running together. Okay. No, more like fight club that the fight club, Brad Pitt, where he's like standing. All right. People will know. Anyway, I'm sorry. I'll get off on that. Do you have a, like when you're thinking about the being a love magnet in that way, are you picturing specific people or is this almost like in the space of like energy? Right. It's somebody who is smart and well accomplished and successful in their life, but they're generous and they're well traveled and they want to travel the world. Things like that. Like their head over heels into me. It's like, I know it sounds super silly, but it's literally what I write. Yeah. And I believe it'll happen one day. Oh, you actually write, so you don't say it out loud? You write. No, I write it. I write all my affirmations. I do the opposite. I say it out loud. Oh, you say it out loud? Interesting. Yeah, if I'm alone, I'll say it out loud. Interesting. I should try that. I think it's what feels more powerful to you. To me, more powerful. Saying stuff feels more powerful. Yeah. Writing is, writing feels like I'm losing the words, like losing the power of the words maybe because I write slow. Do you handwrite? No, I type. It's on this app. It's day one, basically. And I just, I can look, the best thing about it is I can look back and see like a year ago, what was I affirming, right? So it's... Oh, so it changes over time. It hasn't like changed a lot, but the focus kind of changes over time. I got it. Yeah, I say the same exact thing over and over and over. Oh, you do? Okay. There's a comfort in the sameness of it. Well, actually, let me jump around because let me ask you about, because all this talk about Brad Pitt, or maybe it's just going on inside my head, let me ask you about dating in general. You tweeted, are you based in Boston and single? And then you pointed to a startup Singles Night sponsored by Smile Dating app. I mean, this is jumping around a little bit, but since you mentioned... Since you mentioned, can AI help solve this dating love problem? What do you think? This problem of connection that is part of the human condition, can AI help that you yourself are in the search affirming? Maybe that's what I should affirm, like build an AI. Build an AI that finds love? I think there must be a science behind that first moment you meet a person and you either have chemistry or you don't, right? I guess that was the question I was asking, would you put it brilliantly, is that a science or an art? I think there are like, there's actual chemicals that get exchanged when two people meet. I don't know about that. I like how you're changing, yeah, changing your mind as we're describing it, but it feels that way. But it's what science shows us is sometimes we can explain with the rigor, the things that feel like magic. So maybe we can remove all the magic. Maybe it's like, I honestly think, like I said, like Goodreads should be a dating app, which like books. I wonder if you look at just like books or content you've consumed. I mean, that's essentially what YouTube does when it does a recommendation. If you just look at your footprint of content consumed, if there's an overlap, but maybe interesting difference with an overlap that some, I'm sure this is a machine learning problem that's solvable. Like this person is very likely to be not only there to be chemistry in the short term, but a good lifelong partner to grow together. I bet you it's a good machine learning problem. You just need the data. Let's do it. Well, actually, I do think there's so much data about each of us that there ought to be a machine learning algorithm that can ingest all this data and basically say, I think the following 10 people would be interesting connections for you, right? And so Smile dating app kind of took one particular angle, which is humor. It matches people based on their humor styles, which is one of the main ingredients of a successful relationship. Like if you meet somebody and they can make you laugh, like that's a good thing. And if you develop like internal jokes, like inside jokes and you're bantering, like that's fun. So I think. Yeah, definitely. Definitely. But yeah, that's the number of and the rate of inside joke generation. You could probably measure that and then optimize it over the first few days. You could say, we're just turning this into a machine learning problem. I love it. But for somebody like you, who's exceptionally successful and busy, is there, is there signs to that aspect of dating? Is it tricky? Is there advice you can give? Oh, my God, I give the worst advice. Well, I can tell you like I have a spreadsheet. Is that a good or a bad thing? Do you regret the spreadsheet? Well, I don't know. What's the name of the spreadsheet? Is it love? It's the date track, dating tracker. Dating tracker. It's very like. Love tracker. Yeah. And there's a rating system, I'm sure. Yeah. There's like weights and stuff. It's too close to home. Oh, is it? Do you also have. Well, I don't have a spreadsheet, but I would, now that you say it, it seems like a good idea. Oh, no. Okay. Turning it into data. I do wish that somebody else had a spreadsheet about me. You know, if it was like, like I said, like you said, convert, collect a lot of data about us in a way that's privacy preserving, that I own the data, I can control it and then use that data to find, I mean, not just romantic love, but collaborators, friends, all that kind of stuff. It seems like the data is there. Right. That's the problem social networks are trying to solve, but I think they're doing a really poor job. Even Facebook tried to get into a dating app business. And I think there's so many components to running a successful company that connects human beings. And part of that is, you know, having engineers that care about the human side, right, as you know, extremely well, it's not, it's not easy to find those. But you also don't want just people that care about the human. They also have to be good engineers. So it's like, you have to find this beautiful mix. And for some reason, just empirically speaking, people have not done a good job of that, of building companies like that. And it must mean that it's a difficult problem to solve. Dating apps, it seems difficult. Okay, Cupid, Tinder, all those kinds of stuff. They seem to find, of course they work, but they seem to not work as well as I would imagine is possible. Like, with data, wouldn't you be able to find better human connection? It's like arranged marriages on steroids, essentially. Right, right. Arranged by machine learning algorithm. Arranged by machine learning algorithm, but not a superficial one. I think a lot of the dating apps out there are just so superficial. They're just matching on like high level criteria that aren't ingredients for successful partnership. But you know what's missing, though, too? I don't know how to fix that, the serendipity piece of it. Like, how do you engineer serendipity? Like this random, like, chance encounter, and then you fall in love with the person. Like, I don't know how a dating app can do that. So there has to be a little bit of randomness. Maybe every 10th match is just a, you know, yeah, somebody that the algorithm wouldn't have necessarily recommended, but it allows for a little bit of... Well, it can also, you know, it can also trick you into thinking of serendipity by like somehow showing you a tweet of a person that he thinks you'll match well with, but do it accidentally as part of another search. Right. And like you just notice it, like, and then you get, you go down a rabbit hole and you connect them outside the app to like, you connect with this person outside the app somehow. So it's just, it creates that moment of meeting. Of course, you have to think of, from an app perspective, how you can turn that into a business. But I think ultimately a business that helps people find love in any way. Like that's what Apple was about, create products that people love. That's beautiful. I mean, you got to make money somehow. If you help people fall in love personally with the product, find self love or love another human being, you're going to make money. You're going to figure out a way to make money. I just feel like the dating apps often will optimize for something else than love. It's the same with social networks. They optimize for engagement as opposed to like a deep, meaningful connection that's ultimately grounded in like personal growth, you as a human being growing and all that kind of stuff. Let me do like a pivot to a dark topic, which you opened the book with. A story, because I'd like to talk to you about just emotion and artificial intelligence. I think this is a good story to start to think about emotional intelligence. You opened the book with a story of a central Florida man, Jamel Dunn, who was drowning and drowned while five teenagers watched and laughed, saying things like, you're going to die. And when Jamel disappeared below the surface of the water, one of them said he just died and the others laughed. What does this incident teach you about human nature and the response to it perhaps? Yeah. I mean, I think this is a really, really, really sad story. And it and it and it highlights what I believe is a it's a real problem in our world today. It's it's an empathy crisis. Yeah, we're living through an empathy crisis and crisis. Yeah. Yeah. And I mean, we've we've talked about this throughout our conversation. We dehumanize each other. And unfortunately, yes, technology is bringing us together. But in a way, it's just dehumanized. It's creating this like, yeah, dehumanizing of the other. And I think that's a huge problem. The good news is I think solution, the solution could be technology based. Like, I think if we rethink the way we design and deploy our technologies, we can solve parts of this problem. But I worry about it. I mean, even with my son, a lot of his interactions are computer mediated. And I just question what that's doing to his empathy skills and, you know, his ability to really connect with people. So that you think you think it's not possible to form empathy through the digital medium. I think it is. But we have to be thoughtful about because the way the way we engage face to face, which is what we're doing right now, right? There's the nonverbal signals, which are a majority of how we communicate. It's like 90% of how we communicate is your facial expressions. You know, I'm saying something and you're nodding your head now, and that creates a feedback loop. And and if you break that, and now I have anxiety about it. Poor Lex. Oh, boy. I am not scrutinizing your facial expressions during this interview. I am. Look normal. Look human. Yeah. Look normal, look human. Nod head. Yeah, nod head. In agreement. If Rana says yes, then nod head else. Don't do it too much because it might be at the wrong time and then it will send the wrong signal. Oh, God. And make eye contact sometimes because humans appreciate that. All right. Anyway, okay. Yeah, but something about the especially when you say mean things in person, you get to see the pain of the other person. Exactly. But if you're tweeting it at a person and you have no idea how it's going to land, you're more likely to do that on social media than you are in face to face conversations. So. What do you think is more important? EQ or IQ?

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