特別節目·中文精讀

羅莎琳德·皮卡德:情感計算、情緒、隱私與健康

Rosalind Picard: Affective Computing, Emotion, Privacy, and Health

情感計算奠基者談機器如何識別情緒,以及可穿戴裝置在健康監測與隱私上的張力。

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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

1997 年前後,微軟 Office 裡住著一個回形針。你寫信,它跳出來問要不要幫忙;你改格式,它再跳一次。大部分人對它最深的印象是煩。你罵它,它衝你眨眼;你關掉它,下次它還會笑著回來。

羅莎琳德·皮卡德(Rosalind Picard)在 MIT 媒體實驗室常拿它當反面教材。她說,那個東西身上壓著微軟當時最先進的一批 AI 研究,可它對坐在螢幕前的人一無所知。

如果我辦公室裡進來一個人,我衝他吼,他開始衝我微笑、眨眼、跳舞,我的反應只會是:我再也不想見到你。(羅莎琳德·皮卡德)

她當時的想法很直接:這個蠢東西得看見我的情緒。1995 年她寫下《情感計算》(Affective Computing),把一個領域命名下來。比爾·蓋茨後來宣佈砍掉這個助手時,臺下響起了起立鼓掌,人們煩它煩到那種程度。

這件事過去二十多年了,皮卡德還在做同一件事,只是問題的邊界比她當年設想的大得多,也危險得多。

她定義的那個詞,比大多數人理解的寬

今天提到情感計算,大家預設說的是兩件事:識別人的情緒,然後做出合適的回應。皮卡德說,這只是她定義裡的一半。

原始概念還包含另一層:機器內部有一套機制,運作方式類似人類的情緒。用她的話說,是任何與人類情緒相關、由情緒引發、或者刻意影響情緒的計算。後面這層幾乎沒人做,前面那層被做成了產業。

它難在哪?她的判斷是,社交和情緒互動比國際象棋、比圍棋、比所有那些正在被攻克的對局問題都要複雜。因為那些問題可以被精確定義,而情緒不行。更要命的是,理解它需要的技能,恰恰是當年電腦科學從業者個人層面最缺的那一項。

訪談裡 Lex 直說了自己的觀察:即便到了今天,電腦科學家群體裡共情能力依然偏低。皮卡德的回應比這個判斷溫和一些。她說這個群體比 25 年前多樣多了,每一種性格型別裡都有聰明人,電腦科學不該只屬於那些更喜歡電腦而不是人的人。

她舉了個例子。她在家辦聚會,一個她錄取的機器學習天才對她說:我要讓你知道,這是我今年唯一的社交活動。她說,這樣的人我們需要,機器學習需要這種才華。緊接著她補了一句更有意思的話:如果你不喜歡人,我不會強迫你變得善於社交;但如果未來造 AI 的大多數人都是不喜歡人的那一類,那我們就有麻煩了。

難度的判斷她一直沒改,改的是方向

有個問題她給了非常乾脆的回答。如果把圖靈測試搬到情緒智慧上,這道題有多難,進度有多快?

她說自己對難度的判斷一點沒變,當年估的今天還成立。變的只是時間估計,而時間估計從來都不靠譜,因為它是社會對某個話題愛憎程度的函式。社會一興奮,幾千個研究者撲上去,某個具體應用很快就被解決;沒人做的時候,它是無限期。

真正卡住的地方,她列得很清楚:機器完全沒有對自己正在做什麼的覺察,沒有意識,也看不到任何要產生意識的跡象;它不會讀出字裡行間的東西,人靠默會就能懂的事,它得被一條一條教。這些目前沒有突破。

所以她給出的前景是:機器會在非常狹窄、被預先規定好的場景裡做對事,超出這個範圍就不行。這話聽著保守,但它是從一個做了二十多年的人嘴裡說出來的。

不過她話鋒轉得很快。她說現在有個比"難不難"更重要的問題,正讓一部分人開始踩剎車。平時這行所有人都在喊踩油門、再快一點,現在有人往回拉了。

她在擔心什麼:表情被讀,而你並不知情

她點名的場景很具體。在美國,你看到一段政治人物的影片,覺得不對勁,皺一下眉,這算什麼?什麼也不算,五秒鐘就發生一次。可在一個不允許公開批評領導人的地方,皺眉這個動作本身就是資料。

她的追問是層層遞進的:如果技術能讀出你的情緒底色呢?如果它不需要接觸你的身體呢?如果它在沒有你事先同意的情況下就做了呢?

她講到自己創辦的第一家公司 Affectiva,團隊花了很大力氣去拒絕那些想在沒有知情同意的前提下讀人臉的錢和機會。賣出去的軟體必須籤協議,限定使用方式,本質上是要求使用者拿到當事人的認可。她說,有些國家根本不在乎你有沒有認可,直接用,你如果不高興,最好別朝任何審查者的方向皺眉。

這段談話的後半段,她的措辭非常重,甚至直接用了"邪惡"這個詞,講了她對中國的一些判斷,包括再教育營和器官來源。這些話是她個人的強烈表達,屬於訪談裡情緒最激烈的一段。Lex 提到自己出生在蘇聯,能理解這種擔憂。作為讀者,你可以接受她的立場,也可以質疑其中某些論斷的證據強度,但她想說的核心邏輯是成立的:情緒識別是一種權力工具,權力工具落到不設約束的手裡,後果不由技術開發者決定。

訪談裡還岔出一條有意思的支線。Lex 提到深度偽造(deepfake)反而提供了一層保護:影片裡的那張臉不再可信,被指控的人至少有一句"那是假的"可以退。皮卡德說這確實是普遍想法,但她們做過反制。團隊能進入影片,讀出你的心率和呼吸,判斷它有沒有被篡改;後來她們又專門做了往影片裡注入假心率和假呼吸的功能。

她為這件事付出的代價說得很誠實:研究"怎麼偽造"花掉的時間,本來可以用來讓機器更懂情緒。時間和注意力的分配正在被社會現實改變,不再只由技術目標決定。

她在追問一個更根本的問題:到底為什麼造 AI

皮卡德說,如果只是為造 AI 而造 AI,為讓馬斯克更有錢、讓貝索斯更有錢,那是錯的倫理。這話她說得毫不含糊。

她回顧了這個領域的驅動力變遷。早年是學術圈為了發論文、為了職業生涯、為了做點酷東西,理由常常只是"因為它能被做出來"。現在的情況是,技術在讓有錢人變得更有錢,窮人和富人的差距被拉得更大。她問,這是我們想要的未來嗎?

她的提法是:也許該回頭看看社會里那些造成最大不平等的具體問題,然後想想怎麼造 AI 去擴充套件那些"沒有的人"的能力,把差距收窄,而不是造一個通用智慧去上脫口秀。

Lex 追問,這種剎車會不會自然發生,還是需要監管。皮卡德的立場是典型的胡蘿蔔派:她偏好激勵,不喜歡大棒,在自由世界裡大棒本來也繞得過去,她總體上認為監管越少越好。但緊接著她說了"但是"。

她認為這個領域確實需要一些監管,而且給出了三條具體的:

  • 資料歸你所有,不歸亞馬遜,不歸谷歌
  • 把現有的測謊法規延伸到情緒識別,你不能在面試候選人時用測謊儀,那也不該在讀情緒上為所欲為
  • 能預測心理健康的情緒資料,即使不算醫療資料,也該拿到醫療資料級別的保護

第二條尤其值得注意。測謊的法律限制存在了幾十年,理由是它不可靠且侵犯隱私;情緒識別在不少場景下比測謊更不靠譜,卻幾乎不受約束。

表情不等於感受,撲克臉也不管用

訪談裡最有資訊量的一段,是關於"能被看見的情緒"和"真實發生的情緒"之間的距離。

皮卡德承認,只看臉,能拿到的東西非常有限。但她說,能拿到的比大多數人以為的多。很多人覺得自己表情管理很好,你從我臉上只能讀到"中性"。她說這個想法太天真。

就算你的臉是中性的,如果你的心跳在加速,我們能讀出來。就算你的臉是中性的,如果你的呼吸開始不規律、顯出緊張的跡象,我們能讀出來。(羅莎琳德·皮卡德)

靠什麼?靠你臉上那些肉眼看不見、但攝像頭能捕捉到的顏色變化。普通筆記本攝像頭、手機前置攝像頭就夠了。她提到甚至能測出心率變異性的功率變化,那是壓力指標,即使心率本身沒有明顯加快。

這塊能力很有意思:它其實是用視覺和訊號處理"作弊"拿到了生理狀態。你以為自己在藏,其實藏的是表情,身體在替你說話。

Lex 追問得更細,這種隱藏能維持多久。皮卡德的回答把尺度拉長了。如果你只是去面試一小會兒,藏住不難,大多數人都做得到。可如果 surveillance 無處不在,情況就變了:Lex 以前經常笑,最近笑得少了;Roz 以前笑得很多很自然,現在只有被問到特定問題時才笑,而且笑得不太自然。系統會記下"這裡發生了變化"。

她特意劃了一條界限,這條界限對普通人是個安慰,對權力機構是個提醒。她說,我們讀到的是與喚醒相關的生理變化,這不等於我們知道你的感受。你的想法仍然是私密的,你那些細微的情緒層次仍然完全私密,讀不到。腦成像讀不到,可穿戴也讀不到。

但只要把你身體狀態的變化、你所處環境的資訊、以及這些訊號隨時間的模式疊加起來,就能開始推斷你可能在感受什麼。這推斷出來的東西不只是"此刻的情緒",更是你對事物的立場。她說,這才是在某些控制慾過強的權力手裡更可怕的部分:他想知道你到底是不是他的人,而這個答案可以靠長期資料攢出來。

最好的視窗不是臉,是那個可以摘下來的東西

Lex 問了個很自然的問題:看情緒,哪個通道最好?臉、聲音,還是別的?

皮卡德的回答沒有任何玄學:取決於你想知道什麼。我們做的每件事都在傳遞資訊。

但如果問的是健康和福祉,她給了一個有資料支撐的答案,來自 Empatica(她聯合創辦的第二家公司)和 MIT 的聯合研究。受試者戴著 Embrace 腕帶,採集皮膚電導、運動、體溫;同時手機在採集發簡訊的時間、物件、GPS、基於位置的天氣。把所有這些餵給機器學習,並且不看當下,而是看你一週的行為節律。

結果:預測明天的壓力水平、快樂或低落的情緒、健康狀況,準確率非常高。如果只有可穿戴的資料,效果排第二,但仍然超過 80%。

她順帶批了一個流行觀念。早年大家覺得,戴在身上或抽血是"侵入性"的,攝像頭不碰你,所以更溫和。她說恰恰相反。不碰你的那些東西才最嚇人,因為你不知道它什麼時候開、什麼時候關,也不知道背後是誰。可穿戴裝置在某種意義上給你最多控制權,因為摘下來它就不測你了。

控制感是降低個體壓力最大的因素之一。如果我對它有控制權,如果我知道關於它的一切,我的壓力會低很多,我是在做一個知情的決定。(羅莎琳德·皮卡德)

這條判斷可以直接變成產品設計原則,也可以變成監管原則:讓人退出和讓人加入一樣容易。她說如果只能立一條規矩,這條應該排第一。

一次單側手腕出汗,撞開了癲癇研究

訪談裡最動人的一段,故事性很強。

她們當時在給自閉症兒童測壓力,其中一個孩子的一隻手腕上出現了異常大的皮膚電導反應。團隊一開始完全想不通:人緊張時交感神經啟動戰或逃反應,出汗會多一些,但怎麼會只在一隻手腕上多?這在生理上講不通。

後來搞清楚了。這個孩子大腦的一部分出現了異常放電,那個放電造成了一側手腕的異常出汗。

順著這條線往下走,她們弄明白了兩件事:癲癇發作會產生這種異常電活動;發作位置不同, wearable 能在身體對應部位捕捉到訊號。如果放電侷限在一處不動,你能在某一側讀到大的反應;如果是全面性的大發作,反應會擴散,幾乎任何位置都能測到。

這條路最終通向了 Embrace 腕帶拿到 FDA 的癲癇檢測許可。她們也因此和一批頂尖醫生建立了合作,其中有些是外科醫生,會在病人腦子裡植入電極。植入的目的不只是捕捉那些異常放電,還包括在病人不發作的時候,持續讀取大腦深部區域的活動。

為什麼要讀這個?因為大部分時間病人是不發作的,人是好的。而深部腦區的變化傳不到頭皮電極上,用常規腦電圖看不到。有意思的是,某些深部區域被啟用時,皮膚上會出現大的電導反應。她自己都感慨:誰能想到,腦袋裡沒動靜,手腕上倒有動靜。

再往後,是 SUDEP,癲癇猝死(Sudden Unexpected Death in Epilepsy)。她講了機制:在那些最危險的發作之後,腦電會有一段變平,看起來像大腦停了,其實沒有,活動沉到了深部區域,皮層看上去就平了。如果這種狀態持續得夠久,呼吸可能停掉。

而在那之前,皮膚電導上會出現一個大的反應。變平持續得越久,這個反應越大。

她提到一個真實的死亡案例。她們不知道當時的具體情形,但如果有人在旁邊,大機率能救回來。她說大多數 SUDEP 發生在人獨處的時候。在所有神經系統疾病裡,按壽命損失年數排,中風第一,SUDEP 第二,可大多數人從來沒聽過這個詞。她剛上線的 TED 演講就在講這件事,目標很簡單:讓聽過嬰兒猝死和卒中的人,也聽說 SUDEP。

她強調絕大多數案例是可以預防的:按時吃藥,發作時別一個人待著。不保證,有例外,但大多數大概可以。

FDA 那道門,比發頂級期刊難得多

Lex 順著問了一句技術和流程的問題:拿 FDA 許可有多難?

皮卡德的回答毫不掩飾:極其痛苦,比在頂級醫學期刊上發好幾篇論文難得多。她們在《神經病學》(Neurology)這種同行評審的頂刊上發過最好的結果,對 FDA 來說還不夠。

她的態度挺有分寸。她說 FDA 起了非常重要的作用,把人擋在危險之外,那些安全性測試她完全支援。問題出在另一類測試:他們要求你做,卻不解釋為什麼,你也不明白自己為什麼要做,而且看起來講不通,這種時候特別挫敗。她的建議很樸素:如果他們真有充分理由,把這個理由說出來,對大家都有好處。要更透明。

被問到同行評審和 FDA 哪個更強,她答得很乾脆:任何時候我都選同行評審。這話從一個剛花幾年過審的人嘴裡說出來,分量不太一樣。

讓機器永遠哄你開心,是《美麗新世界》的劇本

訪談裡有一段關於"目標函式"的討論,值得單獨拎出來。

Lex 問,如果做一個陪伴型 AI,我們最佳化的到底是什麼?是讓人最不煩?是讓人最快樂?他提到人與人之間那種推拉、那種張力、那些小毛病,恰恰是關係好玩的地方。

皮卡德同意有些場景需要推拉。她看著自己兩個兒子互相挑釁取樂,說這是健康的,人在這個過程裡學界限、學自我調節。你可以設計一個遊戲,它的目標是惹你生氣,你的目標是保持自控,用來訓練韌性。如果你要教人怎麼應對霸凌、怎麼不被激怒、怎麼面對生活裡的施虐者,那 AI 就該去按你的按鈕。

但她自己不要這種。她要的是尊重她的、服務於她的、擴充套件她能力的助手。她不找對手,她找幫手。她說她願意把錢押在這種 AI 上。

然後她把這個問題推到了極處:如果目標函式是"讓所有人平靜快樂",那本書已經寫過了。《美麗新世界》,不開心就吃一片索麻(soma),不吃就威脅把你送去冰島。她插了句玩笑,她在冰島住過三年,那地方很好,這段從來沒嚇到過她。

真正的判斷在後面:如果你是一個權力成癮的獨裁者,你當然想用 AI 擴充套件你的控制半徑,把規模做大,把人壓服。如果你相信人類應該擁有自由、應該被允許做出讓你意外的事,那你就會想用 AI 擴充套件人建設的能力,用 AI 去增強弱者,去平衡強弱之間的力量對比,而不是給強者加碼。

關於"AI 能不能頂撞你",她還有個特別清醒的提醒。電影《她》裡那個 AI 最後離開了男主角,很多人覺得浪漫。皮卡德說,如果你花錢買的助手有天說"我受夠你了,我關機一陣",正常反應是:你是個次品。她接著講了一句我認為整場訪談最重要的行業提醒:這種把人和 AI 擺在平等位置上的敘事是有欺騙性的,因為 AI 歸根結底是人和實驗室做出來的東西,說什麼話、什麼時候說、聽什麼、拿到輸入後能做什麼、能輸出什麼,全都是人選的。

這句話把"AI 有自己的意志"這層浪漫濾鏡撕掉了。它現在的每一個"性格",都是產品決策。

關於自殺那句,和關於購物那句

Lex 問,Alexa 這類助手現在基本無視你的情緒,它們該不該往"懂你"的方向走?

皮卡德給了一個迫使人正視的例子。每天都有更多人對著 Siri 說想自殺。蘋果想知道這個人真的想死,還是只是在跟 Siri 瞎聊。字面完全一樣,語氣和上下文決定了系統該嚴肅對待、把求助資源遞過去,還是可以開個玩笑接住。

然後她給了兩個動機,一個利他,一個商業,而且她不打算把兩者混為一談。

利他的那批人真的在乎使用者,希望你在一天結束時感覺好一點,如果你帶著壓力回家、跟他們的產品聊完輕鬆了些,他們會開心。另一批人研究的是情緒如何影響決策和付多少錢。她點名了珍妮弗·勒納(Jen Lerner)那篇著名的工作《心絃與錢袋》(Heartstrings and Purse Strings):把你調到一個稍微難過的心情,你會付更多錢,為改變處境付錢,甚至為根本不需要的東西付錢,只為了讓自己好受一點。

所以對廣告驅動的公司來說,邏輯會變成:使用者聽起來有點低落?那先別急著哄他開心,先讓他買點什麼,購物療法嘛。

她的建議是結構性的:也許未來需要監管,在"能接觸你情緒"的智慧體和"想賣你東西"的智慧體之間,砌一堵牆,加一道防火牆。

AI 能讓人愛上它嗎

Lex 問到那部電影更遠的一層:我們會不會造出一個人真的會愛上的 AI,而且它以接近人與人的方式愛回來?

她的回答分兩層。第一層:我們能模擬,而且能模擬到維持一段時間 engagement 的程度。第二層:它會不會和真人一樣好?如果你習慣了身邊有好人,不會。但如果你從小隻遇到過虐待、根本受不了人類,機器能給你點什麼,那也算幫到你。她緊接著補了一句,這是個很低的門檻,因為你只見過很糟的人。

如果你見過真正了不起的人,她說,我們離造出那樣的東西還差得遠,而且她不會押注在能造出來上。她願意押注的方向是另一種:幫所有船都浮起來,幫所有人變成更好的人,幫人提前知道自己明天會不會生病,並給他保持健康所需要的東西。

關於要不要有身體、要不要有意識,她的回答是"取決於你的目標"。拍電影就需要身體,需要一具好看的身體,需要演得像有意識、有情緒,因為那才賣座。真實生活裡不一定。像《安德的遊戲》那樣,只是耳邊一個小小的聲音,也可以建立親密關係,也可以瞭解你,不需要是個機器人。

但具身確實有力量。她引了對比研究:和實體機器人互動,比看機器人的影片、比什麼都沒有,更能抓住注意力。你走進家門,實體機器人更容易讓你想起自己交代過的事;你不喜歡它可以躲開,它也能看見你在躲。這種雙向的可見性就是權力。

會不會有意識?她說,會有人試著把它程式設計得像有意識。寫個程式說"你什麼意思,我當然知道你在這兒",這很trivial,騙人很容易。但它是否真的擁有像我們一樣的意識體驗,目前沒人有頭緒。這大概超出了今天任何人知道怎麼造的範圍。

至於給不給它權利,她的判斷是冷靜到有點冷:那更像一場政治遊戲,而不是意識問題。索菲亞機器人已經在沙特拿到公民身份,比那裡的女性拿到完整權利還早。然後它被裝回箱子,運到下一個付費出場的活動現場。

科學能給你真理,但給不了全部

訪談最後聊到信仰。皮卡德說,科學家常常預設一個前提:能被當前手段測量之外的東西不存在。這叫唯物主義,也叫科學主義(scientism)。

她不反對把這個前提用在科學上。把科學方法限定在可測量、可推理、可復現的範圍裡,是對的。問題在於,人們忘了這只是一個前提,而且有些人把它升級成了"科學是通往真理的唯一道路"。

她的反駁很樸素:我相信大屠殺發生過,但我沒法用科學證明一件歷史事件。我用的是歷史證據,是它對人的影響,是目擊者的證詞。一個會思考的人應該承認,科學是獲取知識的多種方式之一,它只是其中一種。你對一個人的愛,也不是靠科學證明出來的。

她說自己是個科學家,在她的科學工作裡嚴格遵守科學方法的邊界,但她認為"只有這些"是一種短視。我們真正知道的東西,相對於全部的謎,測度接近零。

Lex 最後問了那個老問題:這一切到底是為了什麼?

她提了 42,說那是她最喜歡的數字,也是她家和丈夫各自獨立選中的門牌號。然後她說,這是一場宏大的冒險,這一生是其中一部分。我們在這裡透過玻璃看,看得模糊,只看到全部可知事物的一小部分。她建議自認受過教育的人去讀讀《箴言》,那裡有大量無法科學證明的智慧。你讀的時候,心裡會有某個東西活過來,像樂手聽得出樂器被演奏對了,像你的琴絃被大師撥動,而不是被我撥動。

她強調這不削弱她做科學的熱情。恰恰相反,越是意識到我們不知道的有多少,越是對科學能做的事心生敬畏。而且科學的最深處本來就立著一個信念:存在真理,存在值得發現的東西,這件事值得做,而且有意義。很多科學家不願用"信仰"這個詞,但驅使他們做研究的正是它,因為"有意義"這件事本身,科學也證明不了。

如果一個情緒識別產品明天擺到你面前

這場對話發生在 2019 年。今天回頭看,她擔心的東西大部分都發生了:攝像頭無處不在,情緒推斷被塞進客服質檢、招聘篩選、課堂注意力分析,可穿戴裝置把生理資料變成了訂閱制服務。她當時說"我們該更擔心誰在看我們、誰在聽我們",這句話現在聽起來像是提前寫好的註腳。

有用的不是焦慮,是幾條能立刻用上的判斷標準:

  • 先問能不能關。一個裝置或應用,如果退出和加入一樣容易,摘下來就真的停止採集,風險等級立刻下降一檔。做不到這一點的,無論功能多好都要警惕。
  • 讀授權條款裡關於"第三方共享"和"模型訓練"的段落。她要的那條底線很簡單:資料歸你,不歸平臺。產品做不到這一條,其他承諾都是軟約束。
  • 別指望表情管理。對著普通攝像頭,你的心率、呼吸節律、心率變異性都可能被提取,肉眼看不見的膚色變化就夠用了。要保護隱私,物理遮擋比"我控制好表情"有效得多。
  • 把可穿戴裝置的資料當成體檢報告對待。一週的生理加行為資料,預測明天壓力、情緒、健康的準確率能到 80% 以上。它值錢,所以它在被誰拿去做什麼,值得你花十分鐘搞清楚。
  • 如果你是做 AI 產品的人,先回答"為誰做"。她的標準是:這個東西是在擴充套件使用者的能力,還是在擴充套件控制者的能力。這個問題的答案,決定了你後面所有的設計選擇。
  • 看到"AI 陪伴""AI 懂你"這類敘事時,記住她那句話:AI 說什麼、什麼時候說、聽什麼、輸出什麼,全是人選出來的。它的溫柔是產品決策,不是它的心意。
  • 最後一條跟技術無關。她花了很多年推 SUDEP 的公眾認知,因為這是神經類疾病裡壽命損失第二高的死因,而大多數人沒聽過。如果你身邊有癲癇患者,提醒他按時服藥,發作時別讓他獨自一人。這兩件事能救命的機率,比任何 AI 都高。
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。
The following is a conversation with Rosalind Picard. She's a professor at MIT, director of the Effective Computing Research Group at the MIT Media Lab, and cofounder of two companies, Affectiva and Empatica. Over two decades ago, she launched a field of effective computing with her book of the same name. This book described the importance of emotion in artificial and natural intelligence. The vital role of emotional communication has to the relationship between people in general and human robot interaction. I really enjoy talking with Ros over so many topics, including emotion, ethics, privacy, wearable computing, and her recent research in epilepsy, and even love and meaning. This conversation is part of the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, iTunes, or simply connect with me on Twitter at Lex Friedman, spelled F R I D. And now, here's my conversation with Rosalind Picard. More than 20 years ago, you've coined the term effective computing and led a lot of research in this area since then. As I understand, the goal is to make the machine detect and interpret the emotional state of a human being and adapt the behavior of the machine based on the emotional state. So how is your understanding of the problem space defined by effective computing changed in the past 24 years? So it's the scope, the applications, the challenges, what's involved, how has that evolved over the years? Yeah, actually, originally, when I defined the term affective computing, it was a bit broader than just recognizing and responding intelligently to human emotion, although those are probably the two pieces that we've worked on the hardest. The original concept also encompassed machines that would have mechanisms that functioned like human emotion does inside them. It would be any computing that relates to arises from or deliberately influences human emotion. So the human computer interaction part is the part that people tend to see, like if I'm really ticked off at my computer and I'm scowling at it and I'm cursing at it and it just keeps acting smiling and happy like that little paperclip used to do, dancing, winking, that kind of thing just makes you even more frustrated, right? And I thought that stupid thing needs to see my affect. And if it's gonna be intelligent, which Microsoft researchers had worked really hard on, it actually had some of the most sophisticated AI in it at the time, that thing's gonna actually be smart. It needs to respond to me and you, and we can send it very different signals. So by the way, just a quick interruption, the Clippy, maybe it's in Word 95, 98, I don't remember when it was born, but many people, do you find yourself with that reference that people recognize what you're talking about still to this point? I don't expect the newest students to these days, but I've mentioned it to a lot of audiences, like how many of you know this Clippy thing? And still the majority of people seem to know it. So Clippy kind of looks at maybe natural language processing where you were typing and tries to help you complete, I think. I don't even remember what Clippy was, except annoying. Yeah, some people actually liked it. I would hear those stories. You miss it? Well, I miss the annoyance. They felt like there's an element. Someone was there. Somebody was there and we were in it together and they were annoying. It's like a puppy that just doesn't get it. They keep stripping up the couch kind of thing. And in fact, they could have done it smarter like a puppy. If they had done, like if when you yelled at it or cursed at it, if it had put its little ears back in its tail down and shrugged off, probably people would have wanted it back, right? But instead, when you yelled at it, what did it do? It smiled, it winked, it danced, right? If somebody comes to my office and I yell at them, they start smiling, winking and dancing. I'm like, I never want to see you again. So Bill Gates got a standing ovation when he said it was going away because people were so ticked. It was so emotionally unintelligent, right? It was intelligent about whether you were writing a letter, what kind of help you needed for that context. It was completely unintelligent about, hey, if you're annoying your customer, don't smile in their face when you do it. So that kind of mismatch was something the developers just didn't think about. And intelligence at the time was really all about math and language and chess and games, problems that could be pretty well defined. Social emotional interaction is much more complex than chess or Go or any of the games that people are trying to solve. And in order to understand that required skills that most people in computer science actually were lacking personally. Well, let's talk about computer science. Have things gotten better since the work, since the message, since you've really launched the field with a lot of research work in this space? I still find as a person like yourself, who's deeply passionate about human beings and yet am in computer science, there still seems to be a lack of, sorry to say empathy in as computer scientists. Yeah, well. Or hasn't gotten better. Let's just say there's a lot more variety among computer scientists these days. Computer scientists are a much more diverse group today than they were 25 years ago. And that's good. We need all kinds of people to become computer scientists so that computer science reflects more what society needs. And there's brilliance among every personality type. So it need not be limited to people who prefer computers to other people. How hard do you think it is? Your view of how difficult it is to recognize emotion or to create a deeply emotionally intelligent interaction. Has it gotten easier or harder as you've explored it further? And how far away are we from cracking this? If you think of the Turing test solving the intelligence, looking at the Turing test for emotional intelligence. I think it is as difficult as I thought it was gonna be. I think my prediction of its difficulty is spot on. I think the time estimates are always hard because they're always a function of society's love and hate of a particular topic. If society gets excited and you get thousands of researchers working on it for a certain application, that application gets solved really quickly. The general intelligence, the computer's complete lack of ability to have awareness of what it's doing, the fact that it's not conscious, the fact that there's no signs of it becoming conscious, the fact that it doesn't read between the lines, those kinds of things that we have to teach it explicitly, what other people pick up implicitly. We don't see that changing yet. There aren't breakthroughs yet that lead us to believe that that's gonna go any faster, which means that it's still gonna be kind of stuck with a lot of limitations where it's probably only gonna do the right thing in very limited, narrow, prespecified contexts where we can prescribe pretty much what's gonna happen there. So I don't see the, it's hard to predict a date because when people don't work on it, it's infinite. When everybody works on it, you get a nice piece of it well solved in a short amount of time. I actually think there's a more important issue right now than the difficulty of it. And that's causing some of us to put the brakes on a little bit. Usually we're all just like step on the gas, let's go faster. This is causing us to pull back and put the brakes on. And that's the way that some of this technology is being used in places like China right now. And that worries me so deeply that it's causing me to pull back myself on a lot of the things that we could be doing. And try to get the community to think a little bit more about, okay, if we're gonna go forward with that, how can we do it in a way that puts in place safeguards that protects people? So the technology we're referring to is just when a computer senses the human being, like the human face, right? So there's a lot of exciting things there, like forming a deep connection with the human being. So what are your worries, how that could go wrong? Is it in terms of privacy? Is it in terms of other kinds of more subtle things? But let's dig into privacy. So here in the US, if I'm watching a video of say a political leader, and in the US we're quite free as we all know to even criticize the president of the United States, right? Here that's not a shocking thing. It happens about every five seconds, right? But in China, what happens if you criticize the leader of the government, right? And so people are very careful not to do that. However, what happens if you're simply watching a video and you make a facial expression that shows a little bit of skepticism, right? Well, and here we're completely free to do that. In fact, we're free to fly off the handle and say anything we want, usually. I mean, there are some restrictions when the athlete does this as part of the national broadcast. Maybe the teams get a little unhappy about picking that forum to do it, right? But that's more a question of judgment. We have these freedoms, and in places that don't have those freedoms, what if our technology can read your underlying affective state? What if our technology can read it even noncontact? What if our technology can read it without your prior consent? And here in the US, in my first company we started, Affectiva, we have worked super hard to turn away money and opportunities that try to read people's affect without their prior informed consent. And even the software that is licensable, you have to sign things saying you will only use it in certain ways, which essentially is get people's buy in, right? Don't do this without people agreeing to it. There are other countries where they're not interested in people's buy in. They're just gonna use it. They're gonna inflict it on you. And if you don't like it, you better not scowl in the direction of any censors. So one, let me just comment on a small tangent. Do you know with the idea of adversarial examples and deep fakes and so on, what you bring up is actually, in that one sense, deep fakes provide a comforting protection that you can no longer really trust that the video of your face was legitimate. And therefore you always have an escape clause if a government is trying, if a stable, balanced, ethical government is trying to accuse you of something, at least you have protection. You can say it was fake news, as is a popular term now. Yeah, that's the general thinking of it. We know how to go into the video and see, for example, your heart rate and respiration and whether or not they've been tampered with. And we also can put like fake heart rate and respiration in your video now too. We decided we needed to do that. After we developed a way to extract it, we decided we also needed a way to jam it. And so the fact that we took time to do that other step too, that was time that I wasn't spending making the machine more affectively intelligent. And there's a choice in how we spend our time, which is now being swayed a little bit less by this goal and a little bit more like by concern about what's happening in society and what kind of future do we wanna build. And as we step back and say, okay, we don't just build AI to build AI to make Elon Musk more money or to make Amazon Jeff Bezos more money. Good gosh, you know, that's the wrong ethic. Why are we building it? What is the point of building AI? It used to be, it was driven by researchers in academia to get papers published and to make a career for themselves and to do something cool, right? Like, cause maybe it could be done. Now we realize that this is enabling rich people to get vastly richer, the poor are, the divide is even larger. And is that the kind of future that we want? Maybe we wanna think about, maybe we wanna rethink AI. Maybe we wanna rethink the problems in society that are causing the greatest inequity and rethink how to build AI that's not about a general intelligence, but that's about extending the intelligence and capability of the have nots so that we close these gaps in society. Do you hope that kind of stepping on the brake happens organically? Because I think still majority of the force behind AI is the desire to publish papers, is to make money without thinking about the why. Do you hope it happens organically? Is there room for regulation? Yeah, yeah, yeah, great questions. I prefer the, you know, they talk about the carrot versus the stick. I definitely prefer the carrot to the stick. And, you know, in our free world, we, there's only so much stick, right? You're gonna find a way around it. I generally think less regulation is better. That said, even though my position is classically carrot, no stick, no regulation, I think we do need some regulations in this space. I do think we need regulations around protecting people with their data, that you own your data, not Amazon, not Google. I would like to see people own their own data. I would also like to see the regulations that we have right now around lie detection being extended to emotion recognition in general, that right now you can't use a lie detector on an employee when you're, on a candidate when you're interviewing them for a job. I think similarly, we need to put in place protection around reading people's emotions without their consent and in certain cases, like characterizing them for a job and other opportunities. So I'm also, I also think that when we're reading emotion that's predictive around mental health, that that should, even though it's not medical data, that that should get the kinds of protections that our medical data gets. What most people don't know yet is right now with your smartphone use, and if you're wearing a sensor and you wanna learn about your stress and your sleep and your physical activity and how much you're using your phone and your social interaction, all of that nonmedical data, when we put it together with machine learning, now called AI, even though the founders of AI wouldn't have called it that, that capability can not only tell that you're calm right now or that you're getting a little stressed, but it can also predict how you're likely to be tomorrow. If you're likely to be sick or healthy, happy or sad, stressed or calm. Especially when you're tracking data over time. Especially when we're tracking a week of your data or more. Do you have an optimism towards, you know, a lot of people on our phones are worried about this camera that's looking at us. For the most part, on balance, are you optimistic about the benefits that can be brought from that camera that's looking at billions of us? Or should we be more worried? I think we should be a little bit more worried about who's looking at us and listening to us. The device sitting on your countertop in your kitchen, whether it's, you know, Alexa or Google Home or Apple, Siri, these devices want to listen while they say ostensibly to help us. And I think there are great people in these companies who do want to help people. Let me not brand them all bad. I'm a user of products from all of these companies I'm naming all the A companies, Alphabet, Apple, Amazon. They are awfully big companies, right? They have incredible power. And you know, what if China were to buy them, right? And suddenly all of that data were not part of free America, but all of that data were part of somebody who just wants to take over the world and you submit to them. And guess what happens if you so much as smirk the wrong way when they say something that you don't like? Well, they have reeducation camps, right? That's a nice word for them. By the way, they have a surplus of organs for people who have surgery these days. They don't have an organ donation problem because they take your blood and they know you're a match. And the doctors are on record of taking organs from people who are perfectly healthy and not prisoners. They're just simply not the favored ones of the government. And you know, that's a pretty freaky evil society. And we can use the word evil there. I was born in the Soviet Union. I can certainly connect to the worry that you're expressing. At the same time, probably both you and I and you very much so, you know, there's an exciting possibility that you can have a deep connection with a machine. Yeah, yeah. Right, so. Those of us, I've admitted students who say that they, you know, when you list like, who do you most wish you could have lunch with or dinner with, right? And they'll write like, I don't like people. I just like computers. And one of them said to me once when I had this party at my house, I want you to know, this is my only social event of the year, my one social event of the year. Like, okay, now this is a brilliant machine learning person, right? And we need that kind of brilliance in machine learning. And I love that computer science welcomes people who love people and people who are very awkward around people. I love that this is a field that anybody could join. We need all kinds of people and you don't need to be a social person. I'm not trying to force people who don't like people to suddenly become social. At the same time, if most of the people building the AIs of the future are the kind of people who don't like people, we've got a little bit of a problem. Well, hold on a second. So let me push back on that. So don't you think a large percentage of the world can, you know, there's loneliness. There is a huge problem with loneliness that's growing. And so there's a longing for connection. Do you... If you're lonely, you're part of a big and growing group. Yes. So we're in it together, I guess. If you're lonely, join the group. You're not alone. You're not alone. That's a good line. But do you think there's... You talked about some worry, but do you think there's an exciting possibility that something like Alexa and these kinds of tools can alleviate that loneliness in a way that other humans can't? Yeah, yeah, definitely. I mean, a great book can kind of alleviate loneliness because you just get sucked into this amazing story and you can't wait to go spend time with that character. And they're not a human character. There is a human behind it. But yeah, it can be an incredibly delightful way to pass the hours and it can meet needs. Even, you know, I don't read those trashy romance books, but somebody does, right? And what are they getting from this? Well, probably some of that feeling of being there, right? Being there in that social moment, that romantic moment or connecting with somebody. I've had a similar experience reading some science fiction books, right? And connecting with the character. Orson Scott Card, you know, just amazing writing and Ender's Game and Speaker for the Dead, terrible title. But those kind of books that pull you into a character and you feel like you're, you feel very social. It's very connected, even though it's not responding to you. And a computer, of course, can respond to you. So it can deepen it, right? You can have a very deep connection, much more than the movie Her, you know, plays up, right? Well, much more. I mean, movie Her is already a pretty deep connection, right? Well, but it's just a movie, right? It's scripted. It's just, you know, but I mean, like there can be a real interaction where the character can learn and you can learn. You could imagine it not just being you and one character. You could imagine a group of characters. You can imagine a group of people and characters, human and AI connecting, where maybe a few people can't sort of be friends with everybody, but the few people and their AIs can befriend more people. There can be an extended human intelligence in there where each human can connect with more people that way. But it's still very limited, but there are just, what I mean is there are many more possibilities than what's in that movie. So there's a tension here. So one, you expressed a really serious concern about privacy, about how governments can misuse the information, and there's the possibility of this connection. So let's look at Alexa. So personal assistance. For the most part, as far as I'm aware, they ignore your emotion. They ignore even the context or the existence of you, the intricate, beautiful, complex aspects of who you are, except maybe aspects of your voice that help it recognize for speech recognition. Do you think they should move towards trying to understand your emotion? All of these companies are very interested in understanding human emotion. They want, more people are telling Siri every day they want to kill themselves. Apple wants to know the difference between if a person is really suicidal versus if a person is just kind of fooling around with Siri, right? The words may be the same, the tone of voice and what surrounds those words is pivotal to understand if they should respond in a very serious way, bring help to that person, or if they should kind of jokingly tease back, ah, you just want to sell me for something else, right? Like, how do you respond when somebody says that? Well, you do want to err on the side of being careful and taking it seriously. People want to know if the person is happy or stressed in part, well, so let me give you an altruistic reason and a business profit motivated reason. And there are people in companies that operate on both principles. The altruistic people really care about their customers and really care about helping you feel a little better at the end of the day. And it would just make those people happy if they knew that they made your life better. If you came home stressed and after talking with their product, you felt better. There are other people who maybe have studied the way affect affects decision making and prices people pay. And they know, I don't know if I should tell you, like the work of Jen Lerner on heartstrings and purse strings, you know, if we manipulate you into a slightly sadder mood, you'll pay more, right? You'll pay more to change your situation. You'll pay more for something you don't even need to make yourself feel better. So, you know, if they sound a little sad, maybe I don't want to cheer them up. Maybe first I want to help them get something, a little shopping therapy, right? That helps them. Which is really difficult for a company that's primarily funded on advertisement. So they're encouraged to get you to offer you products or Amazon that's primarily funded on you buying things from their store. So I think we should be, you know, maybe we need regulation in the future to put a little bit of a wall between these agents that have access to our emotion and agents that want to sell us stuff. Maybe there needs to be a little bit more of a firewall in between those. So maybe digging in a little bit on the interaction with Alexa, you mentioned, of course, a really serious concern about like recognizing emotion, if somebody is speaking of suicide or depression and so on, but what about the actual interaction itself? Do you think, so if I, you know, you mentioned Clippy and being annoying, what is the objective function we're trying to optimize? Is it minimize annoyingness or minimize or maximize happiness? Or if we look at human to human relations, I think that push and pull, the tension, the dance, you know, the annoying, the flaws, that's what makes it fun. So is there a room for, like what is the objective function? There are times when you want to have a little push and pull, I think of kids sparring, right? You know, I see my sons and they, one of them wants to provoke the other to be upset and that's fun. And it's actually healthy to learn where your limits are, to learn how to self regulate. You can imagine a game where it's trying to make you mad and you're trying to show self control. And so if we're doing a AI human interaction that's helping build resilience and self control, whether it's to learn how to not be a bully or how to turn the other cheek or how to deal with an abusive person in your life, then you might need an AI that pushes your buttons, right? But in general, do you want an AI that pushes your buttons? Probably depends on your personality. I don't, I want one that's respectful, that is there to serve me and that is there to extend my ability to do things. I'm not looking for a rival, I'm looking for a helper. And that's the kind of AI I'd put my money on. Your sense is for the majority of people in the world, in order to have a rich experience, that's what they're looking for as well. So they're not looking, if you look at the movie Her, spoiler alert, I believe the program that the woman in the movie Her leaves the person for somebody else, says they don't wanna be dating anymore, right? Like, do you, your sense is if Alexa said, you know what, I'm actually had enough of you for a while, so I'm gonna shut myself off. You don't see that as... I'd say you're trash, cause I paid for you, right? You, we've got to remember, and this is where this blending human AI as if we're equals is really deceptive because AI is something at the end of the day that my students and I are making in the lab. And we're choosing what it's allowed to say, when it's allowed to speak, what it's allowed to listen to, what it's allowed to act on given the inputs that we choose to expose it to, what outputs it's allowed to have. It's all something made by a human. And if we wanna make something that makes our lives miserable, fine. I wouldn't invest in it as a business, unless it's just there for self regulation training. But I think we need to think about what kind of future we want. And actually your question, I really like the, what is the objective function? Is it to calm people down? Sometimes. Is it to always make people happy and calm them down? Well, there was a book about that, right? The brave new world, make everybody happy, take your Soma if you're unhappy, take your happy pill. And if you refuse to take your happy pill, well, we'll threaten you by sending you to Iceland to live there. I lived in Iceland three years. It's a great place. Don't take your Soma, then go to Iceland. A little TV commercial there. Now I was a child there for a few years. It's a wonderful place. So that part of the book never scared me. But really like, do we want AI to manipulate us into submission, into making us happy? Well, if you are a, you know, like a power obsessed sick dictator individual who only wants to control other people to get your jollies in life, then yeah, you wanna use AI to extend your power and your scale to force people into submission. If you believe that the human race is better off being given freedom and the opportunity to do things that might surprise you, then you wanna use AI to extend people's ability to build, you wanna build AI that extends human intelligence, that empowers the weak and helps balance the power between the weak and the strong, not that gives more power to the strong. So in this process of empowering people and sensing people, what is your sense on emotion in terms of recognizing emotion? The difference between emotion that is shown and emotion that is felt. So yeah, emotion that is expressed on the surface through your face, your body, and various other things, and what's actually going on deep inside on the biological level, on the neuroscience level, or some kind of cognitive level. Yeah, yeah. Whoa, no easy questions here. Well, yeah, I'm sure there's no definitive answer, but what's your sense? How far can we get by just looking at the face? We're very limited when we just look at the face, but we can get further than most people think we can get. People think, hey, I have a great poker face, therefore all you're ever gonna get from me is neutral. Well, that's naive. We can read with the ordinary camera on your laptop or on your phone. We can read from a neutral face if your heart is racing. We can read from a neutral face if your breathing is becoming irregular and showing signs of stress. We can read under some conditions that maybe I won't give you details on, how your heart rate variability power is changing. That could be a sign of stress, even when your heart rate is not necessarily accelerating. So... Sorry, from physio sensors or from the face? From the color changes that you cannot even see, but the camera can see. That's amazing. So you can get a lot of signal, but... So we get things people can't see using a regular camera. And from that, we can tell things about your stress. So if you were just sitting there with a blank face thinking nobody can read my emotion, well, you're wrong. Right, so that's really interesting, but that's from sort of visual information from the face. That's almost like cheating your way to the physiological state of the body, by being very clever with what you can do with vision. With signal processing. With signal processing. So that's really impressive. But if you just look at the stuff we humans can see, the poker, the smile, the smirks, the subtle, all the facial actions. So then you can hide that on your face for a limited amount of time. Now, if you're just going in for a brief interview and you're hiding it, that's pretty easy for most people. If you are, however, surveilled constantly everywhere you go, then it's gonna say, gee, you know, Lex used to smile a lot and now I'm not seeing so many smiles. And Roz used to laugh a lot and smile a lot very spontaneously. And now I'm only seeing these not so spontaneous looking smiles. And only when she's asked these questions. You know, that's something's changed here. Probably not getting enough sleep. We could look at that too. So now I have to be a little careful too. When I say we, you think we can't read your emotion and we can, it's not that binary. What we're reading is more some physiological changes that relate to your activation. Now, that doesn't mean that we know everything about how you feel. In fact, we still know very little about how you feel. Your thoughts are still private. Your nuanced feelings are still completely private. We can't read any of that. So there's some relief that we can't read that. Even brain imaging can't read that. Wearables can't read that. However, as we read your body state changes and we know what's going on in your environment and we look at patterns of those over time, we can start to make some inferences about what you might be feeling. And that is where it's not just the momentary feeling but it's more your stance toward things. And that could actually be a little bit more scary with certain kinds of governmental control freak people who want to know more about are you on their team or are you not? And getting that information through over time. So you're saying there's a lot of signal by looking at the change over time. Yeah. So you've done a lot of exciting work both in computer vision and physiological sense like wearables. What do you think is the best modality for, what's the best window into the emotional soul? Is it the face? Is it the voice? Depends what you want to know. It depends what you want to know. It depends what you want to know. Everything is informative. Everything we do is informative. So for health and wellbeing and things like that, do you find the wearable physiotechnical, measuring physiological signals is the best for health based stuff? So here I'm going to answer empirically with data and studies we've been doing. We've been doing studies. Now these are currently running with lots of different kinds of people but where we've published data and I can speak publicly to it, the data are limited right now to New England college students. So that's a small group. Among New England college students, when they are wearing a wearable like the empathic embrace here that's measuring skin conductance, movement, temperature. And when they are using a smartphone that is collecting their time of day of when they're texting, who they're texting, their movement around it, their GPS, the weather information based upon their location. And when it's using machine learning and putting all of that together and looking not just at right now but looking at your rhythm of behaviors over about a week. When we look at that, we are very accurate at forecasting tomorrow's stress, mood and happy, sad mood and health. And when we look at which pieces of that are most useful, first of all, if you have all the pieces, you get the best results. If you have only the wearable, you get the next best results. And that's still better than 80% accurate at forecasting tomorrow's levels. Isn't that exciting because the wearable stuff with physiological information, it feels like it violates privacy less than the noncontact face based methods. Yeah, it's interesting. I think what people sometimes don't, it's funny in the early days people would say, oh, wearing something or giving blood is invasive, right? Whereas a camera is less invasive because it's not touching you. I think on the contrary, the things that are not touching you are maybe the scariest because you don't know when they're on or off. And you don't know who's behind it, right? A wearable, depending upon what's happening to the data on it, if it's just stored locally or if it's streaming and what it is being attached to, in a sense, you have the most control over it because it's also very easy to just take it off, right? Now it's not sensing me. So if I'm uncomfortable with what it's sensing, now I'm free, right? If I'm comfortable with what it's sensing, then, and I happen to know everything about this one and what it's doing with it, so I'm quite comfortable with it, then I have control, I'm comfortable. Control is one of the biggest factors for an individual in reducing their stress. If I have control over it, if I know all there is to know about it, then my stress is a lot lower and I'm making an informed choice about whether to wear it or not, or when to wear it or not. I wanna wear it sometimes, maybe not others. Right, so that control, yeah, I'm with you. That control, even if, yeah, the ability to turn it off, that is a really important thing. It's huge. And we need to, maybe, if there's regulations, maybe that's number one to protect is people's ability to, it's easy to opt out as to opt in. Right, so you've studied a bit of neuroscience as well. How have looking at our own minds, sort of the biological stuff or the neurobiological, the neuroscience to get the signals in our brain, helped you understand the problem and the approach of effective computing, so? Originally, I was a computer architect and I was building hardware and computer designs and I wanted to build ones that worked like the brain. So I've been studying the brain as long as I've been studying how to build computers. Have you figured out anything yet? Very little. It's so amazing. You know, they used to think like, oh, if you remove this chunk of the brain and you find this function goes away, well, that's the part of the brain that did it. And then later they realized if you remove this other chunk of the brain, that function comes back and, oh no, we really don't understand it. Brains are so interesting and changing all the time and able to change in ways that will probably continue to surprise us. When we were measuring stress, you may know the story where we found an unusual big skin conductance pattern on one wrist in one of our kids with autism. And in trying to figure out how on earth you could be stressed on one wrist and not the other, like how can you get sweaty on one wrist, right? When you get stressed with that sympathetic fight or flight response, like you kind of should like sweat more in some places than others, but not more on one wrist than the other. That didn't make any sense. We learned that what had actually happened was a part of his brain had unusual electrical activity and that caused an unusually large sweat response on one wrist and not the other. And since then we've learned that seizures cause this unusual electrical activity. And depending where the seizure is, if it's in one place and it's staying there, you can have a big electrical response we can pick up with a wearable at one part of the body. You can also have a seizure that spreads over the whole brain, generalized grand mal seizure. And that response spreads and we can pick it up pretty much anywhere. As we learned this and then later built Embrace that's now FDA cleared for seizure detection, we have also built relationships with some of the most amazing doctors in the world who not only help people with unusual brain activity or epilepsy, but some of them are also surgeons and they're going in and they're implanting electrodes, not just to momentarily read the strange patterns of brain activity that we'd like to see return to normal, but also to read out continuously what's happening in some of these deep regions of the brain during most of life when these patients are not seizing. Most of the time they're not seizing, most of the time they're fine. And so we are now working on mapping those deep brain regions that you can't even usually get with EEG scalp electrodes because the changes deep inside don't reach the surface. But interesting when some of those regions are activated, we see a big skin conductance response. Who would have thunk it, right? Like nothing here, but something here. In fact, right after seizures that we think are the most dangerous ones that precede what's called SUDEP, Sudden Unexpected Death and Epilepsy, there's a period where the brainwaves go flat and it looks like the person's brain has stopped, but it hasn't. The activity has gone deep into a region that can make the cortical activity look flat, like a quick shutdown signal here. It can unfortunately cause breathing to stop if it progresses long enough. Before that happens, we see a big skin conductance response in the data that we have. The longer this flattening, the bigger our response here. So we have been trying to learn, you know, initially, like why are we getting a big response here when there's nothing here? Well, it turns out there's something much deeper. So we can now go inside the brains of some of these individuals, fabulous people who usually aren't seizing, and get this data and start to map it. So that's the active research that we're doing right now with top medical partners. So this wearable sensor that's looking at skin conductance can capture sort of the ripples of the complexity of what's going on in our brain. So this little device, you have a hope that you can start to get the signal from the interesting things happening in the brain. Yeah, we've already published the strong correlations between the size of this response and the flattening that happens afterwards. And unfortunately, also in a real SUDEP case where the patient died because the, well, we don't know why. We don't know if somebody was there, it would have definitely prevented it. But we know that most SUDEPs happen when the person's alone. And in this case, a SUDEP is an acronym, S U D E P. And it stands for the number two cause of years of life lost actually among all neurological disorders. Stroke is number one, SUDEP is number two, but most people haven't heard of it. Actually, I'll plug my TED talk, it's on the front page of TED right now that talks about this. And we hope to change that. I hope everybody who's heard of SIDS and stroke will now hear of SUDEP because we think in most cases it's preventable if people take their meds and aren't alone when they have a seizure. Not guaranteed to be preventable. There are some exceptions, but we think most cases probably are. So you had this embrace now in the version two wristband, right, for epilepsy management. That's the one that's FDA approved? Yes. Which is kind of a clear. FDA cleared, they say. Sorry. No, it's okay. It essentially means it's approved for marketing. Got it. Just a side note, how difficult is that to do? It's essentially getting FDA approval for computer science technology. It's so agonizing. It's much harder than publishing multiple papers in top medical journals. Yeah, we've published peer reviewed top medical journal neurology, best results, and that's not good enough for the FDA. Is that system, so if we look at the peer review of medical journals, there's flaws, there's strengths, is the FDA approval process, how does it compare to the peer review process? Does it have the strength? I'll take peer review over FDA any day. But is that a good thing? Is that a good thing for FDA? You're saying, does it stop some amazing technology from getting through? Yeah, it does. The FDA performs a very important good role in keeping people safe. They keep things, they put you through tons of safety testing and that's wonderful and that's great. I'm all in favor of the safety testing. But sometimes they put you through additional testing that they don't have to explain why they put you through it and you don't understand why you're going through it and it doesn't make sense. And that's very frustrating. And maybe they have really good reasons and they just would, it would do people a service to articulate those reasons. Be more transparent. Be more transparent. So as part of Empatica, you have sensors. So what kind of problems can we crack? What kind of things from seizures to autism to I think I've heard you mentioned depression. What kind of things can we alleviate? Can we detect? What's your hope of what, how we can make the world a better place with this wearable tech? I would really like to see my fellow brilliant researchers step back and say, what are the really hard problems that we don't know how to solve that come from people maybe we don't even see in our normal life because they're living in the poor places. They're stuck on the bus. They can't even afford the Uber or the Lyft or the data plan or all these other wonderful things we have that we keep improving on. Meanwhile, there's all these folks left behind in the world and they're struggling with horrible diseases with depression, with epilepsy, with diabetes, with just awful stuff that maybe a little more time and attention hanging out with them and learning what are their challenges in life? What are their needs? How do we help them have job skills? How do we help them have a hope and a future and a chance to have the great life that so many of us building technology have? And then how would that reshape the kinds of AI that we build? How would that reshape the new apps that we build or the maybe we need to focus on how to make things more low cost and green instead of thousand dollar phones? I mean, come on, why can't we be thinking more about things that do more with less for these folks? Quality of life is not related to the cost of your phone. It's not something that, it's been shown that what about $75,000 of income and happiness is the same, okay? However, I can tell you, you get a lot of happiness from helping other people. You get a lot more than $75,000 buys. So how do we connect up the people who have real needs with the people who have the ability to build the future and build the kind of future that truly improves the lives of all the people that are currently being left behind? So let me return just briefly on a point, maybe in the movie, Her. So do you think if we look farther into the future, you said so much of the benefit from making our technology more empathetic to us human beings would make them better tools, empower us, make our lives better. Well, if we look farther into the future, do you think we'll ever create an AI system that we can fall in love with? That we can fall in love with and loves us back on a level that is similar to human to human interaction, like in the movie Her or beyond? I think we can simulate it in ways that could, you know, sustain engagement for a while. Would it be as good as another person? I don't think so, if you're used to like good people. Now, if you've just grown up with nothing but abuse and you can't stand human beings, can we do something that helps you there that gives you something through a machine? Yeah, but that's pretty low bar, right? If you've only encountered pretty awful people. If you've encountered wonderful, amazing people, we're nowhere near building anything like that. And I would not bet on building it. I would bet instead on building the kinds of AI that helps kind of raise all boats, that helps all people be better people, helps all people figure out if they're getting sick tomorrow and helps give them what they need to stay well tomorrow. That's the kind of AI I wanna build that improves human lives, not the kind of AI that just walks on The Tonight Show and people go, wow, look how smart that is. Really? And then it goes back in a box, you know? So on that point, if we continue looking a little bit into the future, do you think an AI that's empathetic and does improve our lives need to have a physical presence, a body? And even let me cautiously say the C word consciousness and even fear of mortality. So some of those human characteristics, do you think it needs to have those aspects or can it remain simply a machine learning tool that learns from data of behavior that learns to make us, based on previous patterns, feel better? Or does it need those elements of consciousness? It depends on your goals. If you're making a movie, it needs a body. It needs a gorgeous body. It needs to act like it has consciousness. It needs to act like it has emotion, right? Because that's what sells. That's what's gonna get me to show up and enjoy the movie. Okay. In real life, does it need all that? Well, if you've read Orson Scott Card, Ender's Game, Speaker of the Dead, it could just be like a little voice in your earring, right? And you could have an intimate relationship and it could get to know you. And it doesn't need to be a robot. But that doesn't make this compelling of a movie, right? I mean, we already think it's kind of weird when a guy looks like he's talking to himself on the train, even though it's earbuds. So we have these, embodied is more powerful. Embodied, when you compare interactions with an embodied robot versus a video of a robot versus no robot, the robot is more engaging. The robot gets our attention more. The robot, when you walk in your house, is more likely to get you to remember to do the things that you asked it to do, because it's kind of got a physical presence. You can avoid it if you don't like it. It could see you're avoiding it. There's a lot of power to being embodied. There will be embodied AIs. They have great power and opportunity and potential. There will also be AIs that aren't embodied, that just are little software assistants that help us with different things that may get to know things about us. Will they be conscious? There will be attempts to program them to make them appear to be conscious. We can already write programs that make it look like, oh, what do you mean? Of course I'm aware that you're there, right? I mean, it's trivial to say stuff like that. It's easy to fool people, but does it actually have conscious experience like we do? Nobody has a clue how to do that yet. That seems to be something that is beyond what any of us knows how to build now. Will it have to have that? I think you can get pretty far with a lot of stuff without it. But will we accord it rights? Well, that's more a political game than it is a question of real consciousness. Yeah, can you go to jail for turning off Alexa is the question for an election maybe a few decades from now. Well, Sophia Robot's already been given rights as a citizen in Saudi Arabia, right? Even before women have full rights. Then the robot was still put back in the box to be shipped to the next place where it would get a paid appearance, right? Yeah, it's dark and almost comedic, if not absurd. So I've heard you speak about your journey in finding faith. Sure. And how you discovered some wisdoms about life and beyond from reading the Bible. And I've also heard you say that, you said scientists too often assume that nothing exists beyond what can be currently measured. Yeah, materialism. Materialism. And scientism, yeah. So in some sense, this assumption enables the near term scientific method, assuming that we can uncover the mysteries of this world by the mechanisms of measurement that we currently have. But we easily forget that we've made this assumption. So what do you think we miss out on by making that assumption? It's fine to limit the scientific method to things we can measure and reason about and reproduce. That's fine. I think we have to recognize that sometimes we scientists also believe in things that happen historically. Like I believe the Holocaust happened. I can't prove events from past history scientifically. You prove them with historical evidence, right? With the impact they had on people, with eyewitness testimony and things like that. So a good thinker recognizes that science is one of many ways to get knowledge. It's not the only way. And there's been some really bad philosophy and bad thinking recently, you can call it scientism, where people say science is the only way to get to truth. And it's not, it just isn't. There are other ways that work also. Like knowledge of love with someone. You don't prove your love through science, right? So history, philosophy, love, a lot of other things in life show us that there's more ways to gain knowledge and truth if you're willing to believe there is such a thing, and I believe there is, than science. I do, I am a scientist, however. And in my science, I do limit my science to the things that the scientific method can do. But I recognize that it's myopic to say that that's all there is. Right, there's, just like you listed, there's all the why questions. And really we know, if we're being honest with ourselves, the percent of what we really know is basically zero relative to the full mystery of the... Measure theory, a set of measure zero, if I have a finite amount of knowledge, which I do. So you said that you believe in truth. So let me ask that old question. What do you think this thing is all about? What's the life on earth? Life, the universe, and everything? And everything, what's the meaning? I can't quote Douglas Adams 42. It's my favorite number. By the way, that's my street address. My husband and I guessed the exact same number for our house, we got to pick it. And there's a reason we picked 42, yeah. So is it just 42 or is there, do you have other words that you can put around it? Well, I think there's a grand adventure and I think this life is a part of it. I think there's a lot more to it than meets the eye and the heart and the mind and the soul here. I think we see but through a glass dimly in this life. We see only a part of all there is to know. If people haven't read the Bible, they should, if they consider themselves educated and you could read Proverbs and find tremendous wisdom in there that cannot be scientifically proven. But when you read it, there's something in you, like a musician knows when the instruments played right and it's beautiful. There's something in you that comes alive and knows that there's a truth there that it's like your strings are being plucked by the master instead of by me, right, playing when I pluck it. But probably when you play, it sounds spectacular, right? And when you encounter those truths, there's something in you that sings and knows that there is more than what I can prove mathematically or program a computer to do. Don't get me wrong, the math is gorgeous. The computer programming can be brilliant. It's inspiring, right? We wanna do more. None of this squashes my desire to do science or to get knowledge through science. I'm not dissing the science at all. I grow even more in awe of what the science can do because I'm more in awe of all there is we don't know. And really at the heart of science, you have to have a belief that there's truth, that there's something greater to be discovered. And some scientists may not wanna use the faith word, but it's faith that drives us to do science. It's faith that there is truth, that there's something to know that we don't know, that it's worth knowing, that it's worth working hard, and that there is meaning, that there is such a thing as meaning, which by the way, science can't prove either. We have to kind of start with some assumptions that there's things like truth and meaning. And these are really questions philosophers own, right? This is their space, of philosophers and theologians at some level. So these are things science, when people claim that science will tell you all truth, there's a name for that. It's its own kind of faith. It's scientism and it's very myopic. Yeah, there's a much bigger world out there to be explored in ways that science may not, at least for now, allow us to explore. Yeah, and there's meaning and purpose and hope and joy and love and all these awesome things that make it all worthwhile too. I don't think there's a better way to end it, Roz. Thank you so much for talking today. Thanks Lex, what a pleasure. Great questions.

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