特別節目·中文精讀

肖恩·卡羅爾:宇宙、生命與智慧的本質

Sean Carroll: The Nature of the Universe, Life, and Intelligence

物理學家從量子力學與熵出發,討論宇宙演化、生命起源與智慧在自然中的位置。

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按貝葉斯的方式把模擬假說推到底,會得到一個很難受的圖景:只有你一個人被完整渲染,你周圍所有人都是非玩家角色,你看到的那堵牆背後什麼都沒有。

這是肖恩·卡羅爾(Sean Carroll)在 Lex Fridman 節目裡推出來的結論。他在加州理工學院做理論物理,研究量子力學、引力和宇宙學,寫過《從永恆到此刻》《大圖景》,還有一本講量子力學的《深藏不露的東西》(Something Deeply Hidden)。他還在自己的網站 preposterousuniverse.com 上寫部落格,也主持一檔叫 Mindscape 的播客。

這期對話從一個沒法有標準答案的問題開始:理解宇宙和理解心智,哪個更重要。一路走到模擬假說、費米悖論、生命起源、人工意識,最後落在學術界一個挺難堪的現實上。卡羅爾幾乎在每個問題上都給了明確立場,而且都帶著理由。

貝葉斯賬本里的模擬世界

模擬假說在物理上可能,卡羅爾完全不否認這一點。他要問的是另一個問題:在這個假設之下,我應該看到什麼?

第一件該看到的事,是不該看到一個這麼大的宇宙。可觀測宇宙裡大約有兩萬億個星系,每個星系裡有兩千億顆恆星。為了跑一場模擬,把宇宙鋪得這麼大,怎麼看都是對資源的極大浪費。

第二件該看到的事,是不該看到這麼高的解析度。假如模擬者的算力有限,他們不會把整個宇宙都渲染出來,只會渲染你身邊這一小塊。那麼這套貝葉斯推理的自然延伸就是:只有你被完整渲染,別人都是聊天機器人。眼前的牆是存在的,牆背後則是徹底的空。

這才是一場高效模擬該有的樣子。它和人類觀測到的世界差得太遠,遠到卡羅爾不願意接受這個假設。他也承認,也許有人會說“我們又不知道一場模擬長什麼樣”,但那等於放棄了自己作為貝葉斯主義者的責任。你的任務是說清楚:如果這個理論成立,你該期待看到什麼。

還有一層更繞的論證,他在部落格裡專門寫過。假如被模擬出來的智慧體也有意識,那麼在宇宙所有意識體當中,被模擬的那些會佔絕大多數,人類只是頂層的極少數。這個論證聽起來很有力,卡羅爾卻說它一定錯了。

理由是這樣的:如果人類能模擬別人,被模擬的那些也能模擬別人,一層層往下套,鏈條總能走到最底,因為物理定律有底,人類由原子組成,再往下還有更基本的層次。於是會存在一種最便宜的模擬。按照最初的推理,人應該出現在最便宜的那一層,因為那裡的人口最多。

可人類顯然不在那一層。人類並不處在解析度的邊緣,不是那種十六位色的粗糙造物。想造出比人類更簡單的東西,容易得多。

卡羅爾對人擇原理那種“我們是宇宙中的典型觀察者”的用法本身就存疑。人可以在已知的範圍裡做選擇,判斷自己在已知事物中屬於典型,但沒法把自己放到整個宇宙裡判斷典型性。

宇宙只發生一次

Lex 丟擲的下一個問題是,宇宙是不是一臺計算裝置。

誠實的回答是:不是。宇宙確實在處理資訊,確實很像計算機,但從某個意義上說,宇宙更像一次運算,說它是一臺計算機並不準確。因為宇宙只發生一次。計算機是通用機器,你可以問它不同的問題,哪怕只是一隻口袋計算器,也是被造出來回答某類問題的。宇宙不是這樣。(肖恩·卡羅爾)

資訊處理在宇宙內部發生,但資訊處理不構成宇宙的本質。這個區別在卡羅爾看來相當重要,因為一旦把兩者混起來,後面關於智慧的推論就會一路走偏。

他的 MIT 同行塞斯·勞埃德(Seth Lloyd)持完全相反的看法。卡羅爾講過一個影片裡的場面:勞埃德在一場討論裡闡述“宇宙是計算機”,天體物理學家馬丁·里斯(Martin Rees)反問了一句:那什麼不是計算機?

勞埃德愣住了,說這是個好問題,他也不確定。因為一旦“計算機”的定義足夠寬,萬物都是計算機,這個類比也就失去了力量。一個類比有用,靠的恰恰是它把某些東西排除在外。月球繞地球轉,是在做計算嗎?你可以構造出一套定義讓答案是肯定的,但那是一場沒什麼意義的計算。

卡羅爾承認,在特定語境下把宇宙當成資訊處理裝置非常有用。他甚至寫過一篇論文叫《量子電路宇宙學》,把整個宇宙建模成一個量子電路,量子位元(qubit)在電路里越來越糾纏。

時空從糾纏裡長出來

順著這個思路,卡羅爾講了一個他認為深到幾乎沒人討論的謎題。

空間在膨脹。取空間裡的一塊區域,數一數里面有多少自由度,也就是量子場和粒子能排列組合出多少種方式。這個數目很可能是有限的。那麼問題來了:隨著宇宙膨脹,空間變大,自由度是不是變多了?

如果是無限多,問題不存在,無限乘二還是無限。可如果是有限的,空間變大就意味著自由度增加,那些多出來的自由度從哪兒來?宇宙因此成了一個不封閉的系統,有新的自由度不斷冒出來。

他和合作者給出的方案是:自由度一直都在,只是起初沒有糾纏。人類熟悉的三維空間,本身就是那些已經糾纏起來的自由度構成的時空結構。隨著宇宙膨脹,一大批處於零態的量子位元透過量子電路的作用,和其餘時空糾纏在一起。

底層的哲學是:時空本身源自某些基本量子自由度之間的糾纏。這個想法在量子引力圈子裡有它自己的譜系,卡羅爾在這裡把它講成了一條清晰的因果鏈。

大爆炸初期,幾乎所有自由度都在,但它們彼此不相干。這正是大爆炸熵極低的表現:那是一個非常小、非常簡單的地方。隨著空間膨脹,越來越多的自由度捲入同世界的糾纏,時空結構就是這樣一點點長出來的。

懂粒子物理不等於懂冰淇淋

回到最初那個問題。理解了宇宙的基本規律,是不是就能理解心智?

卡羅爾的回答乾脆:當然不能。他的類比很樸素,光靠理解粒子怎麼運作,你沒法理解冰淇淋怎麼運作。他是一個堅定的湧現論者,相信談論世界的方式不止最微觀的那一層。人們說桌子、椅子、行星、人的時候,用的並不是粒子物理和宇宙學的語言。

不過他也給這個問題留了一線體面。可能存在一些關於複雜性、生物學、資訊處理、記憶、知識、創造力的普遍原理,它們超越人腦本身,理解這些原理可以算作理解宇宙的一部分。

人類大腦是目前已知宇宙中最複雜的東西。指望從粒子物理的基本定律裡直接讀出大腦怎麼工作,這個念頭本身就荒謬。卡羅爾用的詞是“absurd”,他說得非常乾脆。

費米悖論裡只有零和幾十億

宇宙裡有沒有其他智慧生命?卡羅爾的猜測是:可觀測宇宙裡沒有,除了人類。

他的推理基於一個數量上的觀察。可觀測宇宙裡其他智慧物種的數量,只有兩個合理的可能值:零,或者幾十億。如果是幾十億,人類早就該注意到了。真正奇怪的是中間值,比如銀河系裡只有一打文明,既不是零也不是幾十億,這種設定在他眼裡很彆扭。

零是容易想象的:從單細胞到多細胞,從多細胞到技術文明,中間有一個巨大的瓶頸,絕大多數生命都卡在那裡,走不過去。

幾十億也容易想象,只是那樣的話人類不可能毫無察覺。很難想象有一大堆文明存在,卻恰好全躲著人類。

Lex 順著這個話題換了個角度:如果智慧生命在尺度上就和人類截然不同呢?不只在空間大小上不同,連時間的節律都不同。卡羅爾說這個可能性他願意認真對待。

人類對“什麼是生命”都沒有共識,更別提“什麼是智慧生命”了。這種無知本身就是一個保持謙遜的理由。海豚大概是聰明的,可它們永遠發明不了太空旅行,因為它們住在海里,沒有拇指,也就不會有冶煉,不會有技術。宇宙裡可能充滿聰明的物種,它們只是從不製造技術。這和現有的觀測資料完全相容。

Lex 更進一步:人類的大腦被設計成只在這些時間尺度上運作,人類造出的探測工具也只為這些尺度而造。對其他尺度的智慧生命,人類幾乎是瞎的。

卡羅爾也願意往更遠的地方想:星際分子云裡的智慧,中子星表面的智慧,星系之間那些龐然大物裡的智慧,它們的心跳尺度可能是一億年。一邊要保持開放,一邊要記住所有生命共享同一套物理定律。這套定律裡也許有某個東西,目前還說不清是什麼,讓“米”和“年”成為智慧生命最合適的長度與時間尺度。人類由原子構成,原子有固定的大小;人類繞恆星執行,恆星有固定的壽命。智慧生命存在一個合適的區間,人類恰好落在裡面,這件事並非不可能。兩種可能他都保持開放。

找外星人的方式可能一開始就錯了

人類確實找過外星智慧,卡羅爾說,用的是最笨的辦法:把射電望遠鏡對準天空。

一個超級先進的文明,為什麼要漫無目的地向宇宙各個方向播撒無線電訊號?這說不通。而且為了真能聯絡上另一個文明,你得持續發射幾百萬年。從資源角度看,這完全不合理。

更合理的做法是:如果他們認為某個太陽系未來可能出現智慧生命,不會用無線電去打招呼,會派一艘飛船過去,停在附近,像《2001太空漫遊》裡那塊黑石碑一樣,安靜地待著,等。

反過來同樣成立。人類太陽系裡可能早就有其他技術文明留下的東西,人類最終會透過它們建立聯絡,只是還沒把太陽系探索得足夠仔細,沒找到而已。

人類不去這樣想,是因為年輕又沒耐心。把探測器送到另一個恆星系,等它到,再等訊息回來,比一個人的一生還長。可一旦把思考的尺度拉到幾十萬年、上百萬年,這顯然是該做的事。卡羅爾的措辭是“clearly the right thing to do”,說得一點不含糊。

恆星的距離取決於你活多久

說到太空探索,卡羅爾認為長期來看極其重要,哪怕目標在別的恆星系。

很多人高估了難度。他們會說,以百分之一光速飛到另一個恆星系,人在路上就死光了。這個說法背後藏著一個沒被說出來的假設:人類的壽命是現在的長度。科幻作家因此想象超光速旅行,否則故事太慢,讀者沒耐心。人類不會超光速,但可以想象壽命被延長到幾千年。

一旦壽命拉長,恆星在效果上就變近了。一百年的航程算什麼?卡羅爾一個朋友說過一句話:你和我大概會死,但我們的孫輩不好說。預測未來很難,這至少是一個可信的情景。

地球面臨已知和未知的威脅。把人類和生物圈擴散到別處,是一個重要的長期目標。卡羅爾說,這甚至是一場和時間的賽跑,跑得贏跑不贏,取決於壽命延長和災難哪一個先到。

生命起源最該砸錢

科學眼下答不了、但也許很快能答的問題,卡羅爾點了生命起源。

這裡要區分兩件事:生命本身,以及“我們所知的生命”。後者可以比較有把握地討論。它需要三樣東西:區隔化,也就是細胞外面得有一層膜;新陳代謝,攝入物質、轉化能量、驅動自身活動;複製,把關於自己是誰的資訊傳給下一代。

實驗室裡的進展是這樣的。區隔化相當容易,脂質雙分子層自發形成細胞壁,不算難題。複製已經很接近了。目前最先進的水平還造不出一個能自我複製的分子,但已經能造出兩個互相複製的分子。這個狀態離目標不遠。

最難的是新陳代謝。聽起來這是最顯而易見的一環,實際上人體內的細胞機器極其複雜,很難想象它能憑空出現。這大概花了很長時間,而且大機率走過很多彎路。

如果卡羅爾來掌管美國國家科學基金會,他會往這個領域大把投錢。原因很直接:一旦人類能在實驗室裡造出生命,並且搞明白地球上最初的生命是怎麼出現的,人類對世界的看法會被改寫。這還會帶來一連串實際效應,包括對疾病治療的理解。合成生物學是一個巨大的前沿。克雷格·文特(Craig Venter)幾年前造出過一個人造細胞,做法是把一個細胞的 DNA 全部取出,換上全新的 DNA,讓它自己啟動、運轉起來。

卡羅爾說,那是一項巨大的成就,但那一步只是把現成的啟動程式換掉了。真正的難關還在前面:從無到有地讓一套代謝系統轉起來。

意識不會在某一天突然降臨

從生命跳到智慧,Lex 問的是這一躍有多大。

卡羅爾把問題收窄到人工意識。他不認為人類正站在創造人工意識的臨界點上。理由帶著一點自嘲:人類對意識的瞭解少得可憐。連它是什麼都說不清,很難相信自己快把它造出來了。原則上沒有障礙,最終會發生,但不會很快。

Lex 提出了一個更激進的想法:一旦造出智慧,人類會驚訝於意識原來這麼容易。因為意識在很大程度上是一件大家都在假裝的事。

卡羅爾接住了這個想法,還往裡推了一步。意識可能比想象的要不神秘,因為人們每時每刻都比自己以為的要更不意識。各種錯覺隨時都在起作用。他還補充了一條很實用的建議:給 AI 配一個機器人身體,會大大幫助這種“假裝”。

Lex 半開玩笑地說,讓一臺 Roomba 說“我有意識”,並且怎麼勸都勸不回來,這就夠了。人類彼此之間做的正是這件事。意識在很大程度上是社會建構,智慧的很多觀念也是。跨過這條線,需要的未必是對“從電子到神經元到認知”這條鏈的完整理解。

卡羅爾說這個觀察極好。他提到凱特·達林(Kate Darling),就是上過他播客的那位,做的是非常簡單的機器人實驗。這些機器人長得像小動物,會做出痛苦的樣子。人類看到它們“疼”,反應極其負面,會心疼,會不忍心。

理性的說法是:那只是機器人,那不是真正的痛,不過是些電子在跑。

然後你會想起來,你和我也只是些電子在跑,人類的痛也是這個。

卡羅爾說,他很容易想象的是在凱特那些小機器人和人之間存在一個連續譜系。譜系上有些東西,按嚴格的定義、按圖靈測試那一類標準,並不算有意識,但它們走起路來、說起話來,就像有意識一樣。Siri 已經很接近了。

未來的樣子可能不會有某一天突然宣佈“人類造出了意識”。更可能的是,人類一路往前蹭,造出越來越像的東西,越來越符合彼此對“有意識”的期待,蹭著蹭著就到了。

Lex 把這個話題拉回眼前:我們今天第一次見面,你大概預設我是一個人。

卡羅爾說,這個機率我給得很高。

但未來這個預設會開始打問號。照片早就不能信了,影片也快到這個地步。人類在這件事上正在變差,或者說,偽造的能力正在變強。剩下的防線是物理在場的活人。可偽造一個物理在場的人,到底難在哪裡?

說到這裡,卡羅爾自己都覺得有點沉重,說這場對話真讓人沮喪。Lex 說他覺得興奮。卡羅爾的回應是:人類正處在一次相變中間,而處在相變中間的人,極不擅長想象未來五十年會是什麼樣。

善惡和智商大概沒有相關性

Lex 說他不是沒有看見威脅,只是相信技術的力量能幫助人類應對不斷演化的威脅。他引用自己的觀察:見過那麼多聰明人,都是好人,所以“善的軍隊”在技術發展這一側規模龐大。

卡羅爾的回答很直接:你比我樂觀太多了。在他看來,善與惡在聰明人和不聰明人之間的分佈是均勻的,他看不到智力和善良之間有什麼相關性。

Lex 承認,兩個人都沒有證據。

卡羅爾說,對,意見是免費的。

這段對話很短,但它把兩個人處理不確定性的方式攤開了。Lex 從遇到的具體人出發外推,卡羅爾從抽象的分佈出發保持懷疑。誰都沒有資料,誰都在憑直覺下注。這兩個人坐在同一間屋子裡聊了兩個小時,對世界的基本判斷卻幾乎相反,而且都很坦然。

科學說不了該做什麼

話題轉到科學永遠答不了的問題,卡羅爾的答案很乾脆:好壞對錯。

科學告訴人類世界是什麼、世界會做什麼。它不說世界應該做什麼,也不說人應該做什麼。人也是世界的一部分,但人有能力感覺到某件事是對的、某件事是錯的。用卡羅爾那句“長話短說”的概括:道德哲學做的事情,是把人類的直覺系統化。

科學也許能提前預測人類會怎麼選,但它永遠沒法判斷人類當初該不該那樣選。

這個劃分不算新奇,好在劃得乾淨。很多關於“科學能不能解決一切”的爭吵,其實是在這個問題上沒分清楚:描述和規範之間有一條線,跨不過去。跨不過去的理由是邏輯上的,不是技術上的。

我沒法不跨學科

Lex 說他一直以為科學的意義就是跨出去,後來發現學術界是高度割裂的,感到非常幻滅。他問卡羅爾:你是怎麼準備這些跨學科對話的?怎麼讓自己足夠開放?又怎麼建議別的科學家去做這件事?

卡羅爾先講了一個人的故事。他認識一個私人教練,有人在那人的播客裡問:我們該怎麼給自己打氣去健身?怎麼培養這種自律?

你為什麼問我?我停不下來。我不需要給自己打氣。(肖恩·卡羅爾)

別人問卡羅爾怎麼做到跨學科對話,他的反應一樣:這件事本身就是驅動力,他停不下來。他在錄音這件事出現之前很久就在做這件事了。

開始錄播客的動機之一其實很實際:為了逼自己讀完那些買回來卻沒時間讀的書。如果下週要採訪帕特里夏·丘奇蘭德(Patricia Churchland),這周就一定得把她的書讀完。

然後是那個不太好聽的部分。學術界極度割裂,大家互相不說話,而且跨出去是會受懲罰的。那些成功跨界的人,通常是先在自家的小隔間裡做得很成功,然後才開始往外走。

卡羅爾帶研究生,他在這件事上說得非常坦白。大多數博士生最後不會成為教授,這條路很窄。所以,去過你想過的生活,但要睜著眼睛看清代價:你越廣博,越少把時間花在本領域的超精細分工上,你拿到教職的機會就越低。這就是學術界的現實。他覺得這很糟,他不喜歡,但現實就是這樣。

有些人對這件事並不痛苦。很多優秀科學家對跨出領域、跟外人對話零興趣,這完全沒問題,那是另一種活法,而且他們做得很好。

真正讓他失望的是另一件事。他年輕時對知識分子式學術生活有過一套浪漫想象,現實把它擊碎了。“應該走出自己的學科”這個觀念,在大學裡被承認的正面價值少到近乎不存在。他說的原話是:它罕見得就像根本不存在。

這段話的分量在於,它出自一個已經成功的人。先成功,再跨界,這個順序本身就說明系統在獎勵什麼。

對話是成本最低的入口

Lex 接話的方式是從自己身上找證據。他也有一份職業要考慮,如果沒有卡羅爾的播客,他可能根本不會開始做這些對話。這件事讓他意識到,對話在某種意義上就是科學本身在做的事。

寫論文是交流,但跨學科論文的難度高得多。對話容易得多,所以對話是一個起點。

他順手把這個邏輯推到了人工智慧領域:這個領域本來就該往外看,不能只盯著計算機視覺競賽和幾個資料集,得去碰物理學、心理學、神經科學,去想這項技術更廣泛的影響。

卡羅爾對這些話的反應是道謝,然後被 Lex 追加了一句:你永遠不知道世界是怎麼被改變的。這些東西公開出去之後,會有大量研究生說他們被它激勵,而這些人將來會成為教授,漣漪會一圈圈擴散出去。

這大概也是卡羅爾那套“先成功再跨界”建議的另一種解法。系統短期內不會變,但被它篩掉或者繞開的人,可以自己搭一條路出來。播客、部落格、公開對話,本質上都是在系統外面重建一個更寬的交流場。

丟掉的那一小時

這期節目還有個細節。Lex 在開頭說,這是他做播客以來第一次錄音裝置在對話中途死掉,因為幻象電源的技術問題,他花了一小時才發現並修好。

他的比喻是:宇宙裡百分之六十八是暗能量,這場對話裡差不多同樣的比例丟了,只留在兩個人的記憶和他的筆記裡。

一個物理學家的對話,丟了一多半,剩下的是三條線:宇宙的底層結構能不能推出心智,智慧和意識到底是什麼,以及一個人在一個不獎勵廣博的系統裡該怎麼活。這三條線扣得挺緊,因為卡羅爾的立場是前後一致的。

他相信湧現。粒子物理給不了冰淇淋的解釋,也給不了大腦的解釋,所以他不指望還原論能解決智慧問題。他用貝葉斯的方式衡量假說,所以他不買模擬假說的賬,因為觀測資料和那個假設對不上。他對“什麼是生命、什麼是意識”保持謙遜,因為人類連定義都給不出來。同時他又在具體事情上有明確判斷:生命起源快要做到了,值得大把投錢;人工意識還差得遠;跨星際旅行該按百萬年尺度去規劃。

謙遜和明確並不矛盾,分界線在於你手上有沒有東西。有資料的地方就下判斷,沒定義的地方就先承認沒定義。卡羅爾在整場對話裡反覆做的就是這個動作。

至於那個最不舒服的問題,智慧和善良到底有沒有相關性,兩個人都承認自己沒證據。卡羅爾選擇不相信有相關性,Lex 選擇相信自己所見。這個分歧沒辦法靠這期對話解決,它更像是一個提醒:人對世界的整體判斷,往往建立在自己見過的那幾個人身上。

  • 遇到“某個假說在物理上可能”這種說法,先別急著接受。問一句:如果這個假說成立,我應該看到什麼?我看到的東西和它一致嗎。這一步比討論可能性本身有用得多。
  • 判斷一個類比有沒有價值,看它排除了什麼。一個什麼都能解釋的模型,比如把一切都叫“計算機”,等於什麼都沒解釋。能說出“這個不算”的類比才站得住。
  • 如果打算做跨學科的工作,先把代價算清楚。學術界會懲罰廣博,這個懲罰是真實的。想清楚你願意付多少,再決定走多遠,別一邊走一邊覺得自己被辜負。
  • 用對話代替論文去做跨領域的第一次接觸。成本低,反饋快,而且能逼你把本行的黑話翻譯成人話,這個過程本身會暴露你沒想清楚的地方。
  • 判斷一個 AI 系統有沒有“意識”,別隻看它說的話,去看它有沒有身體、有沒有連續的行為歷史、有沒有會被傷害的處境。人類真正把什麼東西當成主體,靠的是這些,不只是語言。
  • 要對一個大問題下整體判斷時,先問問自己的樣本是什麼。見過十個好人,和相信人類總體向善,中間隔著好幾步推理,別把後者當成前者的結論。
文稿來自 Lex Fridman 官網公開發布的官方 Transcript(含說話人與時間戳)。
Lex Fridman (00:00:00): The following is a conversation with Sean Carroll. He’s a theoretical physicist at Caltech, specializing in quantum mechanics, gravity, and cosmology. He’s the author of several popular books, one on the arrow of time called From Eternity to Here, one on the Higgs boson called Particle at the End of the Universe, and one on science and philosophy called The Big Picture: On the Origins of Life, Meaning, and the Universe Itself. He has an upcoming book on quantum mechanics that you can pre-order now called Something Deeply Hidden. He writes one of my favorite blogs on his website, preposterousuniverse.com. Lex Fridman (00:00:38): I recommend clicking on the Greatest Hits link that lists accessible, interesting posts on the arrow of time, dark matter, dark energy, the Big Bang, general relativity, string theory, quantum mechanics, and the big meta questions about the philosophy of science, God, ethics, politics, academia, and much, much more. Finally, and perhaps most famously, he’s the host of a podcast called Mindscape that you should subscribe to and support on Patreon. Along with The Joe Rogan Experience, Sam Harris’s Making Sense, and Dan Carlin’s Hardcore History, Sean’s Mindscape podcast is one of my favorite ways to learn new ideas or explore different perspectives on ideas that I thought I understood. It was truly an honor to meet and spend a couple hours with Sean. Lex Fridman (00:01:27): It’s a bit heartbreaking to say that for the first time ever, the audio recorder for this podcast died in the middle of our conversation. There are technical reasons for this, having to do with phantom power, that I now understand and will avoid. It took me one hour to notice and fix the problem. So, much like the universe is 68% dark energy, roughly the same amount from this conversation was lost, except in the memories of the two people involved and in my notes. I’m sure we’ll talk again and continue this conversation on this podcast or on Sean’s, and of course, I look forward to it. This is The Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, iTunes, support it on Patreon, or simply connect with me on Twitter at lexfridman. Lex Fridman (00:02:16): And now, here’s my conversation with Sean Carroll. Lex Fridman (00:02:21): What do you think is more interesting and impactful, understanding how the universe works at a fundamental level or understanding how the human mind works? Sean Carroll (00:02:29): You know of course, this is a crazy, meaningless, unanswerable question in some sense- … because they’re both very interesting and there’s no absolute scale of interestingness that we can rate them on. There’s the glib answer that says the human brain is part of the universe, right? And therefore, understanding the universe is more fundamental than understanding the human brain. Lex Fridman (00:02:47): But do you really believe that once we understand the fundamental way the universe works at the particle level, the forces, we would be able to understand how the mind works? Sean Carroll (00:02:55): No, certainly not. Lex Fridman (00:02:56): All right. Sean Carroll (00:02:56): We cannot understand how ice cream works just from understanding- … how particles work, right? So I’m a big believer in emergence. I’m a big believer that- … there are different ways of talking about the world beyond just the most fundamental microscopic one. You know, when we talk about tables and chairs and planets and people, we’re not talking the language of particle physics and cosmology. So, but understanding the universe, you didn’t say just at the most fundamental level, right? So understanding the universe at all levels is part of that. I do think, you know, to be a little bit more fair to the question, there probably are general principles of complexity, biology, information processing, memory, knowledge, creativity that go beyond just the human brain, right? Sean Carroll (00:03:45): And maybe one could count understanding those as part of understanding the universe. The human brain, as far as we know, is the most complex thing in the universe. So it’s certainly absurd to think that by understanding the fundamental laws of particle physics, you get any direct insight on how the brain works. Lex Fridman (00:04:02): But then there’s this step from the fundamentals of particle physics to information processing- … which a lot of physicists and philosophers maybe a little bit carelessly take when they talk about artificial intelligence. Do you think of the universe as a kind of a computational device? Sean Carroll (00:04:21): No. To be, like, the honest answer there is no. There’s a sense in which the universe processes information, clearly. There’s a sense in which the universe is like a computer, clearly. But in some sense, I think I tried to say this once on my blog and no one agreed with me, but the universe is more like a computation than a computer because the universe happens once. A computer is a general purpose machine, right? That you can ask it different questions, even a pocket calculator, right? And it’s set up to answer certain kinds of questions. The universe isn’t that. So information processing happens in the universe, but it’s not what the universe is. Lex Fridman (00:04:59): Because- Sean Carroll (00:04:59): And I know your MIT colleague, Seth Lloyd, feels very differently about this, right? Lex Fridman (00:05:03): Well, you’re thinking of the universe as a closed system. Sean Carroll (00:05:07): I am. Lex Fridman (00:05:07): So, so, so what, what makes a computer more like a, like a PC like a computing machine is that there’s a human that every once c- comes up to it and moves the mouse around. So input- Sean Carroll (00:05:19): Gives it input. Lex Fridman (00:05:20): … gives it input. And that’s why you’re saying it’s just a computation, a deterministic thing that’s just unrolling. But the immense complexity of it is nevertheless like processing. There’s a state, and then it changes with rules, and there’s a sense for a lot of people that if the brain operates, the human brain operates within that world, then it’s simply just a small subset of that. And so there’s no reason we can’t build arbitrarily great intelligences. Do you think of intelligence in this way? Sean Carroll (00:05:58): Intelligence is tricky. I don’t have a definition of it offhand. So I remember this panel discussion that I saw on YouTube. I wasn’t there, but Seth Lloyd was on the panel, and so was Martin Rees, the famous astrophysicist, and Seth gave his shtick for why the universe is a computer, and he explained this, and Martin Rees said, “So what is not a computer?” And Seth was like, “Uh, that’s a good question. I’m not sure,” because if you have a sufficiently broad definition of what a computer is, then everything is, right? And the simile or the analogy gains force when it excludes some things. You know, is the moon going around the Earth performing a computation? Sean Carroll (00:06:38): I can come up with definitions in which the answer is yes, but it’s not a very useful computation. I think that it’s absolutely helpful to think about the universe in certain situations, certain contexts as an information processing device. I’m even guilty of writing a paper called Quantum Circuit Cosmology, where we modeled the whole universe as a quantum circuit. Lex Fridman (00:06:59): As a circuit. Sean Carroll (00:07:00): As a circuit, yeah. And– Lex Fridman (00:07:01): With qubits kind of thing? Sean Carroll (00:07:02): With qubits, basically, right, yeah. So, and qubits becoming more and more entangled. So do we wanna, do you wanna digress a little bit? ‘Cause this is– Lex Fridman (00:07:09): Let’s do it. Sean Carroll (00:07:10): … kind of fun. So here’s a mystery about the universe that is so deep and profound that nobody talks about it. Space expands, right? And we talk about in a certain region of space, a certain number of degrees of freedom, a certain number of ways that the quantum fields and the particles in that region can arrange themselves, that that number of degrees of freedom in a region of space is arguably finite. We actually don’t know- Sean Carroll (00:07:35): … how many there are, but there’s a very good argument that says it’s a finite number. So as the universe expands and space gets bigger, are there more degrees of freedom? If it’s an infinite number, it doesn’t really matter. Infinity times two is still infinity, but if it’s a finite number, then there’s more space, so there’s more degrees of freedom. So where did they come from? That would mean the universe is not a closed system. There’s more degrees of freedom popping into existence. Sean Carroll (00:08:01): So what we suggested was that there are more degrees of freedom, and it’s not that they’re not there to start, but they’re not entangled to start. So the universe that you and I know of, the three dimensions around us that we see, we said those are the entangled degrees of freedom making up spacetime. And as the universe expands, there are a whole bunch of qubits in their zero state that become entangled with the rest of spacetime through the action of these quantum circuits. Lex Fridman (00:08:31): So what does it mean that there’s now more degrees of freedom as they become more entangled? Sean Carroll (00:08:39): Yeah. So the- Lex Fridman (00:08:40): As the universe expands? Sean Carroll (00:08:41): That’s right. So there’s more and more degrees of freedom that are entangled, that are playing part– playing the role or part of the entangled spacetime structure. So the basic– the underlying philosophy is that spacetime itself arises from the entanglement of some fundamental quantum degrees of freedom. Lex Fridman (00:08:57): Wow. Okay. So- … At which point is most of the entanglement happening? Are we talking about close to the Big Bang? Are we talking about throughout the time of the life of the- Sean Carroll (00:09:11): Throughout history. Yeah. So the idea is that at the Big Bang, almost all the degrees of freedom that the universe could have were there, but they were unentangled with anything else. And that’s a reflection of the fact that the Big Bang had a low entropy. It was a very simple, very small place, and as space expands, more and more degrees of freedom become entangled with the rest of the world. Lex Fridman (00:09:34): Well, I have to ask, Sean Carroll, what do you think of the thought experiment from Nick Bostrom that we’re living in a simulation? So I think– let me contextualize that a little bit more. I think people don’t actually take this thought experiment … I think it’s quite interesting. It’s not very useful, but it’s quite interesting from the perspective of AI, a lot of the learning that can be done usually happens in simulation- … from artificial examples. And so it’s a constructive question to ask how difficult is our real world to simulate? Which is kind of a dual part of if we’re living in a simulation and somebody built that simulation, how hard– if you were to try to do it yourself, how hard would it be? Sean Carroll (00:10:18): So obviously we could be living in a simulation. If you just want the physical possibility, then I completely agree that it’s physically possible. I don’t think that we actually are. So take this one piece of data into consideration. You know, we live in a big universe. Sean Carroll (00:10:33): Okay? There’s two trillion galaxies in our observable universe with two hundred billion stars in each galaxy, et cetera. It would seem to be a waste of resources to have a universe that big going on just to do a simulation. So in other words, I wanna be a good Bayesian. I wanna ask, under this hypothesis, what do I expect to see? So the first thing I would say is I wouldn’t expect to see a universe that was that big. Okay? The second thing is I wouldn’t expect the resolution of the universe to be as good as it is. So it’s always possible that if our superhuman simulators only have finite resources, that they don’t render the entire universe, right? That the part that is out there, the two trillion galaxies isn’t actually being simulated fully. Okay. Sean Carroll (00:11:19): But then the obvious extrapolation of that is that only I am being simulated fully, like the rest of you are just non-player characters, right? I’m the only thing that is real. The rest of you are just chatbots. Beyond this wall, I see the wall, but there is literally nothing on the other side of the wall. That is sort of the Bayesian prediction. That’s what it would be like to do an efficient simulation of me. So, like, none of that seems quite realistic. The– I don’t see… I hear the argument that it’s just possible and easy to simulate lots of things. I don’t see any evidence from what we know about our universe that we look like a simulated universe. Now, maybe you can say, “Well, we don’t know what it would look like,” but that’s just abandoning your Bayesian responsibilities. Sean Carroll (00:12:04): Like, your job is to say, “Under this theory, here’s what you would expect to see.” Lex Fridman (00:12:09): Yeah. So certainly if you think about simulation as a thing that’s like a video game where only a small subset is being rendered, but say the entire, all the laws of physics it- the entire closed system of the, quote-unquote, “universe”- … it had a creator. Sean Carroll (00:12:27): Yeah. It’s always possible. Lex Fridman (00:12:29): Right. So that’s not useful to think about when you’re thinking about physics the way Nick Bostrom phrases it. If, is it, if it’s possible to simulate a universe, eventually we’ll do it. You can use that, by the way, for a lot of things. But I guess the question is how hard is it to create a universe? Sean Carroll (00:12:52): I wrote a little blog post about this, and maybe I’m missing something, but there’s an argument that says not only that it might be possible to simulate a universe, but probably if you imagine that you actually attribute consciousness and agency to the little things that we’re simulating, to our little artificial beings, there’s probably a lot more of them than there are ordinary organic beings in the universe, or there will be in the future, right? So there’s an argument that not only is being a simulation possible, it’s probable- Sean Carroll (00:13:22): because in the space of all living consciousnesses, most of them are being simulated, right? Most of them are not at the top level. I think that argument must be wrong because it follows from that argument that, you know, if we’re simulated, but we can also simulate other things, well, but if we can simulate other things, they can simulate other things, right? If we give them enough power and resolution, and ultimately we’ll reach a bottom because the laws of physics in our universe have a bottom. We’re made of atoms and so forth. So there will be the cheapest possible simulations, and if you believe the original argument, you should conclude that we should be in the cheapest possible simulation ’cause that’s where most people are, but we don’t look like that. Sean Carroll (00:14:03): It doesn’t look at all like we’re at the edge of resolution, you know, we’re, that we’re 16-bit, you know, things. But it seems much easier to make much lower level things than we are. So, and also I question the whole approach to the anthropic principle that says we are typical observers in the universe. I think that that’s not actually… I think that there’s a lot of selection that we can do that we’re typical within things we already know, but not typical within all the universe. Lex Fridman (00:14:32): So do you think there’s intelligent life, however you would like to define intelligent life, out there in the universe? Sean Carroll (00:14:39): My guess is that there is not intelligent life in the observable universe other than us, simply on the basis of the fact that the likely number of other intelligent species in the observable universe, there’s two likely numbers, zero or billions. And if there had been billions, you would have noticed already. To, for there to be literally like a small number, like, you know, Star Trek, there’s, you know, a dozen intelligent civilizations in our galaxy, but not a billion, that, that’s weird. That’s sort of bizarre to me. It’s easy for me to imagine that there are zero others because there’s just a big bottleneck to making multicellular life or technological life or whatever. It’s very hard for me to imagine that there’s a whole bunch out there that have somehow been hidden from us. Lex Fridman (00:15:32): The question I’d like to ask is what would intelligent life look like? What I mean by that question and where it’s going is what if intelligent life is in some very big ways different than our, the one that has on- … is on Earth. That there’s all kinds of intelligent life that operates in different scales of both size and temporal. Sean Carroll (00:15:57): Right. That’s a great possibility because I think we should be humble about what intelligence is, what life is. We don’t even agree on what life is, much less- … what intelligent life is, right? So that’s an argument for humility saying there could be intelligent life of a very different character, right? Like you could imagine that dolphins are intelligent but never invent space travel ’cause they live in the ocean and they don’t have thumbs, right? So they never invent technology, they never invent smelting. Maybe the universe is full of intelligent species that just don’t make technology, right? That’s compatible with the data, I think. And I think maybe what you’re pointing at is even more out there versions of intelligence. Sean Carroll (00:16:43): You know, intelligence in intermolecular clouds or on the surface of a neutron star or in between the galaxies in giant things where the equivalent of a heartbeat is a hundred million years. On the one hand, yes, we should be very open-minded about those things. On the other hand, we all, all of us share the same laws of physics. There might be something about the laws of physics, even though we don’t currently know exactly what that thing would be, that makes meters and years the right length and timescales for intelligent life. Maybe not- Sean Carroll (00:17:20): … but, you know, we’re made of atoms. Atoms have a certain size. We orbit stars. Stars have a certain lifetime. It’s not impossible to me that there’s a sweet spot for intelligent life that we find ourselves in. So I’m open-minded either way. I’m open-minded either being humble and there’s all sorts of different kinds of life, or no, there’s a reason we just don’t know it yet why life like ours is the kind of life that’s out there. Lex Fridman (00:17:42): Yeah, I’m of two minds too, but I often wonder if our brain is just designed to quite obviously operate and see the world on these timescales and we’re almost blind and the tools we’ve created for detecting things are blind- … to the kind of observation needed to see intelligent life at other scales. Sean Carroll (00:18:04): Well, I’m totally open to that, but so here’s another argument I would make. You know, we have looked for intelligent life, but we’ve looked for it in the dumbest way we can- … by turning radio telescopes to the sky. Why in the world would a super advanced civilization randomly beam out radio signals wastefully in all directions into the universe? That just doesn’t make any sense, especially because in order to think that you would actually contact another civilization, you would have to do it forever. You would have to keep doing it for millions of years. That sounds like a waste of resources. If you thought that there were other solar systems with planets around them where maybe intelligent life didn’t yet exist, but might someday- Sean Carroll (00:18:48): … you wouldn’t try to talk to it with radio waves. You would send a spacecraft out there, and you would park it around there, and it would be like, from our point of view, it’d be like “2001,” where there’s, you know, a monolith. Lex Fridman (00:19:00): Monolith. Sean Carroll (00:19:01): So there could be an artifact. In fact, the other way works also, right? There could be artifacts in our solar system that have been put there by other technologically advanced civilizations, and that’s how we will eventually contact them. And we just haven’t explored the solar system well enough yet to find them. The reason why we don’t think about that is ’cause we’re young and impatient, right? Like, it would take more than my lifetime to actually send something to another star system and wait for it and then come back. So but if we start thinking on hundreds of thousands of years or million-year timescales, that’s clearly the right thing to do. Lex Fridman (00:19:34): Are you excited by the thing that Elon Musk is doing with SpaceX in general with the idea of space exploration, even though your or your species is young and impatient? Sean Carroll (00:19:45): Yeah. No, I do think that space travel is crucially important long term, even to other star systems. And I think that many people overestimate the difficulty because they say, “Look, if you travel one percent the speed of light to another star system, we’ll be dead before you get there,” right? And I think that it’s much easier, and therefore, when they write their science fiction stories, they imagine we can go faster than the speed of light, ’cause otherwise they’re too impatient, right? We’re not gonna go faster than the speed of light, but we could easily imagine that the human lifespan gets extended to thousands of years. Sean Carroll (00:20:18): And once you do that, then the stars are much closer effectively, right? I mean, what’s a hundred-year trip, right? So I think that that’s gonna be the future, the far future, not my lifetime, once again, but baby steps and- Lex Fridman (00:20:30): Unless your lifetime gets extended. Sean Carroll (00:20:32): Well, it’s in a race against time, right? A friend of mine who actually thinks about these things said, “You know you and I are gonna die, but I don’t know about our grandchildren.” That’s, I don’t know, predicting the future is hard, but that’s at least a plausible scenario. And so, yeah, no, I think that as we discussed earlier, there are threats to the Earth, known and unknown, right? Having spread humanity and biology elsewhere is a really important long-term goal. Lex Fridman (00:21:05): What kind of questions can science not currently answer but might soon? When you– when you think about the problems and the mysteries before us- … that may be within reach of science. Sean Carroll (00:21:17): I think an obvious one is the origin of life. We don’t know how that happened. There’s a difficulty in knowing how it happened historically, actually, you know, literally on Earth, but starting life from non-life is something I kinda think we’re close to, right? We’re really- Lex Fridman (00:21:33): You really think so? How– like, how difficult is it to start life? Sean Carroll (00:21:35): I do. I do. Well, I’ve talked to people, including on the podcast, about this. You know, life requires three things, life as we know it. So there’s a difference between life, which who knows what it is, and life as we know it, which we can talk about with some intelligence. So life as we know it requires compartmentalization. You need, like, a little membrane around your cell. Metabolism, you take in food and eat it and let that make you do things. And then replication, okay? So you need to have some information about who you are that you pass down to future generations. In the lab, compartmentalization seems pretty easy, not hard to make lipid bilayers that come into little cellular walls pretty easily. Metabolism and replication are hard, but replication we’re close to. Sean Carroll (00:22:21): People have made RNA-like molecules in the lab that I think the state-of-the-art is they’re not able to make one molecule that reproduces itself, but they’re able to make two molecules that reproduce each other. So that’s okay. That’s pretty close. Sean Carroll (00:22:38): Metabolism is harder, believe it or not, even though it’s sort of the most obvious thing, but you want some sort of controlled metabolism, and the actual cellular machinery in our bodies is quite complicated. It’s hard to see it just popping into existence all by itself. It probably took a while. But we’re making progress. And in fact, I don’t think we’re spending nearly enough money on it. If I were the NSF, I would flood this area with money ’cause it would change our view of the world if we could actually make life in the lab and understand how it was made originally here on Earth. Lex Fridman (00:23:09): And I’m sure it would have some ripple effects that help cure disease and so on. I mean just that understanding- Sean Carroll (00:23:14): Well, that’s right. So synthetic biology is a wonderful big frontier where we’re making cells. Right now, the best way to do that is to borrow heavily from existing biology, right? Craig Venter several years ago created an artificial cell, but all he did was– not all he did, it was a tremendous accomplishment, but all he did was take out the DNA from a cell and put in entirely new DNA and let it boot up and go. Lex Fridman (00:23:36): Mm-hmm. What about the leap to creating intelligent life on Earth? However, again, we define intelligence, of course, but let’s just even say Homo sapiens, the modern, the modern intelligence in our human brain. Do you have a sense of what’s involved in that leap and how big of a leap that is? Sean Carroll (00:24:00): So AI would count in this, or you really want life? You want really an organism in some sense. Lex Fridman (00:24:06): Uh, AI would count, I think. If, if– Yeah, of course. Of course, AI would count, but- Sean Carroll (00:24:11): Well, let’s say artificial consciousness, right? So I do not think we are on the threshold of creating artificial consciousness. I think it’s possible. I’m not, again, very educated about how close we are, but my impression is not that we’re really close because we understand how little we understand of consciousness and what it is. So if we don’t have any idea what it is, it’s hard to imagine we’re on the threshold of making it… ourselves but it’s doable. It’s possible. I don’t see any obstacles in principle, so yeah, I would hold out some interest in that happening eventually. Lex Fridman (00:24:40): I think in general, consciousness I think we’ll be just surprised how easy consciousness is once we create intelligence. I think consciousness is a thing that’s just something we all fake. Sean Carroll (00:24:55): Well, good. No, actually, I like this idea that in fact consciousness is way less mysterious than we think- … because we’re all at every time, at every moment less conscious than we think we are, right? We can fool things, and I think that plus the idea that you not only have artificial intelligent systems, but you put them in a body, right? Give them a robot body. That will help the faking a lot. Lex Fridman (00:25:18): Yeah, I think creating consciousness in artificial consciousness is as simple as asking a Roomba to say, “I’m conscious”… and refusing to be talked out of it. Sean Carroll (00:25:32): Could be. It could be. Lex Fridman (00:25:33): And I mean that – I’m almost being silly, but that’s what we do. … That’s what we do with each other. This, the kind of consciousness is also a social construct, and a lot of our ideas of intelligence is a social construct, and so reaching that bar involves something that’s beyond, that doesn’t necessarily involve the fundamental understanding of how you go from electrons to neurons to cognition. Sean Carroll (00:26:02): No, actually, I think that is a extremely good point, and in fact, what it suggests is, you know, so yeah, you referred to Kate, Kate Darling, who I had on the podcast – … and who does these experiments with very simple robots, but they look like animals, and they can look like they’re experiencing pain, and we human beings react very negatively to these little robots looking like they’re experiencing pain. And what you wanna say is, “Yeah, but they’re just robots. It’s not really pain,” right? It’s just some electrons going around. But then you realize, you know, you and I are just electrons going around, and that’s what pain is also. Sean Carroll (00:26:38): And so what I would have an easy time imagining is that there is a spectrum between these simple little robots that Kate works with and a human being, where there are things that sort of by some strict definition, Turing test level thing, are not conscious, but nevertheless walk and talk like they’re conscious, and it could be that the future is… I mean, Siri is close, right? And so it might be the future has a lot more agents like that, and in fact, rather than someday going, “Aha, we have consciousness,” we’ll just creep up on it with more and more accurate reflections of what we expect. Lex Fridman (00:27:15): And in the future, maybe the present, for example, we haven’t met before, and you’re may- basically assuming that I’m human as it’s- Sean Carroll (00:27:24): I give it a high probability. Lex Fridman (00:27:26): At this time because yeah, but in the future, there might be question marks around that, right? Sean Carroll (00:27:32): Yeah, no, absolutely. Certainly videos are almost to the point where you shouldn’t trust them already. Photos you can’t trust, right? Videos is easier to trust, but we’re getting worse at, you know – We’re getting better at faking them, right? Lex Fridman (00:27:45): Yeah, we’re getting better at faking them. Sean Carroll (00:27:46): Yeah, so physical embodied people, what’s so hard about faking that? Lex Fridman (00:27:51): So- Sean Carroll (00:27:51): This is very depressing, this conversation we’re having right now. So I mean- Lex Fridman (00:27:53): No, to me it’s exciting. Sean Carroll (00:27:55): To me – You’re doing it… so it’s exciting to you, but it’s a sobering thought. We’re very bad, right, at imagining what the next fifty years are gonna be like when we’re in the middle of a phase transition as we are right now. Lex Fridman (00:28:05): Yeah, and in general, I’m not blind to all the threats. I am excited by the power of technology to solve, to protect us against the threats- … as they evolve. I’m not as much as Steven Pinker optimistic about the world, but in everything I’ve seen, all of the brilliant people in the world that I’ve met are good people. So the army of the good, in terms of the development of technology, is large. Sean Carroll (00:28:33): Okay. You’re way more optimistic than I am. I think that goodness and badness are equally distributed among intelligent and unintelligent people. I don’t see much of a correlation there. Lex Fridman (00:28:44): Interesting. Neither of us have proof. Sean Carroll (00:28:47): Yeah, exactly, as you… Again, opinions are free, right? Lex Fridman (00:28:50): Nor definitions of good and evil. We come- Sean Carroll (00:28:53): Also Lex Fridman (00:28:53): … without definitions or without data- … Opinions. So what kind of questions can science not currently answer or may never be able to answer in your view? Sean Carroll (00:29:04): Well, the obvious one is what is good and bad? You know, what is right and wrong? I think that there are questions that, you know, science tells us what happens, what the world is and what it does. It doesn’t say what the world should do or what we should do ’cause we’re part of the world. But we are part of the world, and we have the ability to feel like something’s right, something’s wrong, and to make a very long story very short, I think that the idea of moral philosophy is systematizing our intuitions of what is right and what is wrong. And science might be able to predict ahead of time what we will do, but it won’t ever be able to judge whether we should have done it or not. Lex Fridman (00:29:39): So, you know, you’re kind of unique in terms of scientists. Listen, it doesn’t have to do with podcasts, but even just reaching out, I think you referred to as sort of doing interdisciplinary science. So you reach out and talk to people that are outside of your discipline, which I always hope that’s what science was for. In fact, I was a little disillusioned when I realized that academia is very siloed. Lex Fridman (00:30:07): And so the question is: How, well, at your own level, how do you prepare for these conversations? How do you think about these conversations? How do you open your mind enough to have these conversations? And then maybe a little bit broader, how can you advise other scientists to have these kinds of conversations? Not at the podcast. The fact that you’re doing a podcast is awesome, other people get to hear them. Sean Carroll (00:30:30): Oh, no, I mean, yeah. Lex Fridman (00:30:31): But it’s also good to have it without mics- … in general. Sean Carroll (00:30:34): It’s a good question, but a tough one to answer. I think about, you know, a guy I know who’s a personal trainer, and he was asked on a podcast, “How do we, you know, psych ourselves up to do a workout? How do we make that discipline to go and work out?” And he’s like, “Why are you asking me? Like, I can’t stop working out.” Sean Carroll (00:30:51): “Like, I don’t need to psych myself up.” So, and likewise, you know, you ask me, like, how do you get to, like, have interdisciplinary conversations and all sorts of different things with all sorts of different people? I’m like, that’s, that’s what makes me go, right? Like, that’s– I, I couldn’t stop doing that. I did that long before any of them were recorded. In fact, a lot of the motivation for starting recording it was making sure I would read all these books that I had purchased, right? Like I- … had all these books I wanted to read. Not enough time to read them, and now if I have the motivation, ’cause I’m gonna, you know, interview Pat Churchland, I’m gonna finally read her book, you know? Sean Carroll (00:31:27): And it’s absolutely true that academia is extraordinarily siloed, right? We don’t talk to people. We rarely do, and in fact, when we do, it’s punished, you know? Like- … the people who do it successfully generally first became very successful within their little silo- Sean Carroll (00:31:42): of discipline, and only then did they start expanding out. If you’re a young person, you know, I have graduate students, and I try to be very, very candid with them about this, that it’s– You know, most graduate students are to not become faculty members, right? It’s a tough road. And so live the life you wanna live, but do it with your eyes open about what it does to your job chances. And the more broad you are and the less time you spend hyper-specializing in your field, the lower your job chances are. That’s just an academic reality. It’s terrible, and I don’t like it- Sean Carroll (00:32:18): … but it’s a reality. And for some people, that’s fine. Like, there’s plenty of people who are wonderful scientists who have zero interest in branching out and talking to things, to anyone outside their field. But it, it is disillusioning to me. Some of the, you know, romantic notion I had of the intellectual academic life is belied by the reality of it. The idea that we should reach out beyond our discipline, and that is a positive good, is just so rare in universities that it may as well not exist at all. Lex Fridman (00:32:53): But that said, even though you’re saying you’re doing it like the personal trainer because you just can’t help it, you’re also an inspiration to others. Like, I can speak for myself. You know, I also have a career I’m thinking about, right? And without your podcast, I may have not have been doing this at all, right? So it makes me realize that these kinds of conversations is kind of what science is about in many ways. Like, the reason we write papers, this exchange of ideas is much harder to do interdisciplinary papers, I would say. Sean Carroll (00:33:31): Yeah. That’s correct. Lex Fridman (00:33:32): And conversations are easier, so conversations are a beginning. And in the field of AI, that’s inter– it’s obvious that we should think outside of pure computer vision competitions and particular data sets. We should think about the broader impact of how this can be, you know, reaching out to physics, to psychology, to neuroscience, and having these conversations. So you’re an inspiration, and so- Sean Carroll (00:34:01): Well, thank you very much. Lex Fridman (00:34:02): Never- Sean Carroll (00:34:02): That’s very sweet, but- Lex Fridman (00:34:03): Never know how the world changes. I mean, the fact that this stuff is out there, and I’ve– a huge number of people come up to me, grad students really loving the podcast, inspired by it, and they will probably have that– There’ll be ripple effects when they become faculty and so on, so on. We can end on a balance between pessimism … and optimism. And Sean, thank you so much for talking today. It was awesome. Sean Carroll (00:34:27): No, Lex, thank you very much for this conversation. It was great.

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