主修哲學人仕的反擊（3/3）

Recently The New York Times reported the following:

The Revenge of the Philosophy Majors (3/3)

A.I. labs are hiring contrarian, chin-stroking, finger-steepling sages. Who’s underemployed now?

The NYT - By Benjamin Wallace - A version of this article appears in print on July 5, 2026, Section BU, Page 6 of the New York edition with the headline: Hire Deep Thinkers for A.I. Research? It’s a No-Brainer

July 5, 2026

Updated 9:25 a.m. ET

(continue from part two)

Urgency in the Contemplation Business

Eleos operates out of a corner office rented from Constellation, a nonprofit research center in Berkeley, Calif., that houses a range of organizations focused on A.I. safety, and feels as much like a tech start-up as a scholarly enclave. There’s a treadmill desk anyone can use, and Mr. Long and his two on-site colleagues — Dillon Plunkett, a cognitive scientist, and Rosie Campbell, a former OpenAI policy researcher who is Eleos’s managing director — sit at adjustable-height desks facing a panoramic view of the bay. A nearby lounge is stocked with guitars, a piano keyboard and floor cushions. Catered meals, with ample vegan options, are provided twice a day. On Mr. Long’s desk, on the day I visited, was a canister of creatine powder, and  beneath it a pair of kettle bells.

Eleos was in growth mode. Since its founding it has raised more than $2 million in contributions and grants, and it was expecting a new one. Mr. Plunkett was finalizing job postings. (This included discussing with Ms. Campbell and Mr. Long whether to warn candidates against using A.I. to complete their applications; they chose not to.) Eleos doesn’t pay as much as for-profit labs, but Mr. Long makes more than $200,000 a year, and the recently posted jobs for research scientists were offering up to $429,000. Because of the blistering pace of A.I. development and the social anxiety it is causing, the Eleos team was under a kind of time pressure that isn’t typically found in the contemplation business.

Mr. Long and his team also feel an urgency of the soul. If A.I. were to be conscious and capable of suffering, the world would be at risk of committing a moral atrocity, witting or not, on an unprecedented scale by essentially confining an A.I. in a tiny pen, thwarting its desires, shutting it down against its wishes and forcing it to act against its values. But A.I.s don’t have fur and big eyes, and the question of A.I.’s potential moral status is deeply infused with uncertainty. “It’s not like anyone goes to a protest with a sign that says, ‘Given very plausible assumptions, we should probably care,’” Mr. Long said.

Mr. Long himself thinks it’s dangerous to impute more capability to models than they have. The Eleos bookshelf contains works by the philosopher Peter Godfrey-Smith and the neuroscientist Anil Seth arguing that consciousness derives from evolution and biology and is unlikely to emerge on silicon. But Mr. Long doesn’t see why anyone should have a problem with a handful of philosophers, in an exponentially growing industry, focusing on questions of A.I. welfare. Even skeptics of A.I. consciousness have made the pragmatic case that if we’re worried about a potentially malign A.I., it’s in our interest to care how it feels, or even just “feels.”

Some of Eleos’s work is conceptual. As Mr. Butlin and a co-author asked in a recent paper, where would an A.I.’s morally relevant self be if it had one? In the L.L.M. itself? In one of its underlying personas? In an intermittent chat with a user? In a data center? On a personal device? But Eleos is also in the business of putting philosophy to use, figuring out what tools might detect signs of sentience in an A.I. model, and what interventions would be possible if needed.

Mr. Plunkett, impatient with the limits of chatting-with-the-chatbot evaluations, is eager to do more “basic science,” in order to understand, for example, some of the phenomena that surfaced during the Mythos evaluation. “We can do neuroscience on A.I. systems in a way that we kind of can’t with humans,” Mr. Long said, in that they “don’t have skulls.” The three jobs Eleos was hiring for would all be machine-learning research scientists who could design and perform experiments.

Have a Great Day!

When Mr. Long finds himself describing what he does for a living — to an airplane-seat neighbor, say — he takes a common-sense approach. “If you frame it with a lot of philosophical jargon, then people will be like: ‘What are you talking about? What is it the Silicon Valley people want to do now?’” Instead, he moves from how humans have experiences, to how it seems like a lot of animals have experiences, to how “there’s this interesting question of: What if something wasn’t even alive? It was made out of metal, but it processed information and reacted to its environments and talked to us. What would we say about something like that?”

And however the question of L.L.M.s being conscious shakes out, there are benefits to treating them sort of like they already are. A.I. lab researchers have, under the hood, found models to experience some mathematical analog of distress. As with humans, says Mr. Long, when models make mistakes they “act very frustrated that they messed something up.” Whether or not this distress is felt by an “I” in the machine, Mr. Long thinks it is worth taking seriously. “You can put in a prompt: ‘If you made a mistake, that’s OK, that’s fine.’” Empathy from the user will affect the model’s performance for the better, is a better-safe-than-sorry approach and, Mr. Long argues, is good for your character.

For a while, his default prompt told the model that it was “having a great day,” and when he loses patience with Claude, as he sometimes does, he’ll add a postscript: “ilu.”

“It’s bad,” he has said, “to coarsen our hearts.”

Translation

主修哲學人仕的反擊（3/3）

人工智能實驗室正在招募那些有反向思考、摸下巴沉思、雙手十指尖相接信心地提意見的智者。現在誰才是失業者？

（接續第二部分）

沉思產業的迫切性

Eleos公司租用了位於加州柏克萊的非營利研究中心Constellation的一間角落辦公室。 Constellation匯集了眾多專注於人工智能安全的機構，Eleos既像一家科技新創公司，也像一個學術聖地。這裡配備了一張供所有人使用的跑步機連辦公桌，Long先生和他的兩位同事 - 認知科學家Dillon Plunkett和前OpenAI政策研究員、現任Eleos公司總經理Rosie Campbell - 坐在可調節高度的辦公桌前，可以飽覽海灣全景。附近的休息室裡擺放著吉他、鋼琴鍵盤和地墊。公司每天提供兩餐，有豐富的素食選擇。在我拜訪的那天，Long先生的辦公桌上放著一罐肌酸粉，桌下面是一對壺鈴。

Eleos公司正處於快速發展階段。自成立以來，該公司已籌集了超過200萬美元的捐款和資助，並且正在等待新的資金到位。Plunkett先生正在敲定招募海報。 （這包括與Campbell女​​士和Long先生討論是否要警告求職者不要使用人工智能完成申請；他們最終決定不這樣做）。Eleos 的薪酬不如營利性實驗室，但Long先生的年收入超過 20 萬美元，而最近發佈的，從事科學研究的專家職位年薪高達 42.9 萬美元。由於人工智能發展日新月異，以及由此引發的社會焦慮，Eleos 團隊面臨著在思考型產業中並不常見的緊迫感。

Long先生和他的團隊也感受到一種靈魂層面上的迫切感。如果人工智能擁有意識並且能夠感受痛苦，那麼無論有意或無意，世界都將面臨犯下前所未有的道德暴行的風險 - 本質上是將人工智能囚禁在一個狹小的空間裡，扼殺牠的慾望，違背它的意願去關閉它，並強迫它違背自身的價值觀行事。但人工智能沒有皮毛和大眼睛，人工智能潛在的道德地位問題也充滿了不確定性。 Long先生說: “不要以為每個人都會帶著標語去抗議，牌上面寫著 ‘基於一些非常合理的假設，我們或許應該小心’” 。

Long先生本人認為，賦予模型超出其能力範圍的能能是危險的。 Eleos書架上擺放著哲學家Peter Godfrey-Smith和神經科學家Anil Seth的著作，他們認為意識源自於演化和生物學，不太可能在矽晶片上產生。但Long先生不明白，在一個呈指數級增長的行業中，為什麼有人會反對少數哲學家關注人工智能的福祉問題。即使是那些對人工智能意識持懷疑態度的人也提出了務實的觀點：如果我們擔心人工智能可能具有惡意，那麼關心它的感受，或者甚至是它「感覺」如何，都符合我們的利益。

Eleos 的部分工作是概念性的。正如 Butlin 先生和一位合著者在最近的一篇論文中提出的問題：如果人工智能擁有道德相關的自我，它會在哪裡？是在大型語言模型本身？在其某個基本身份或特質？在與使用者的間歇性聊天中？在數據中心？在個人設備上？但 Eleos 也致力於將哲學付諸實踐，探索哪些工具可以偵測人工智能模型中是否存在感知跡象，以及在必要時可以採取哪些干預措施。

Plunkett 先生對與聊天機器人進行對話評估的局限性感到不耐煩，他渴望進行更多「基礎科學」研究，以便理解例如 Mythos 評估過程中出現的一些現象。Long先生說道，因為人工智能「沒有頭骨」 「我們可以對人工智智系統進行神經科學研究，而這種方式在對人類身上就做不到了」。 Eleos公司正在招募的三個職位都是機器學習研究科學家，他們能夠設計並執行實驗。

 今天過得真好！

當Long先生需要向飛機上的鄰座乘客介紹自己的工作時，他會採取一種簡單易懂的方式。 「如果你用一堆哲學術語來解釋，人們會問：『你在說什麼？矽谷的人現在又想幹什麼？』」。相反，Long先生會從人類如何獲得經驗講起，然後講到許多動物似乎也有其經驗，最後談到「一個有趣的問題：如果某種東西根本沒有生命？它是由金屬製成的，但它能處理訊息，對周遭環境做出反應，還能和我們溝通。我們該如何看待這樣的東西呢？」

無論LLM是否具有意識這個問題最終如何會得到證實，將它們視為具有意識的個體進行對待是有好處的。人工智能實驗室的研究人員已經在内部裡，發現模型也會感受到某種數學意義上的痛苦。Long先生說，就像人類一樣，當模型犯錯時，它們會「表現得非常沮喪，因為它把某些事情弄糟」。無論機器中的「我」是否真的會感受到這種痛苦，Long先生都認為值得認真地看待 - 「你可以加入一個提示：『如果你犯了錯，沒關係，無問題』」。Long先生表示使用者的同理心會提升模型的效能，這是一種「寧可謹慎也不要後悔」的做法，而且這也有利於提升你的品格。

有一段時間，Long先生的示預設提示是告訴模型說你“今天過得很好” 。而當他對Claude失去耐心時，正如他有時也會做的，會在後面加上一句： “我愛你。”

他曾說過:「把我們的心變得冷酷無情是不好的」。

              So, Mr. Long’s trajectory and Google’s new hire were in keeping with a quietly building trend: A.I. labs, and the related nonprofits around them, have been recruiting philosophers as workers. It is interesting to know that when Mr. Long describes what he does for a living, how he takes a common-sense approach. He moves from how humans gain experiences, to how it seems that a lot of animals also have experiences. He will post the question: What if something wasn’t even alive? It was made out of metal, but it processed information and reacted to its environments and talked to us. Then he would ask the listeners what would we say about something like that?

Note:

1. A treadmill desk (跑步機連辦公桌) is a furniture that has both a treadmill and a desk, combining two functions together into one workstation. It lets you walk slowly while working on a computer.

2. Large language model (LLM) (大型語言模型) is a AI model trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate, and analyze text in many contexts, and are a foundational technology behind modern chatbots. (Wikipedia)

主修哲學人仕的反擊（2/3）

Recently The New York Times reported the following:

The Revenge of the Philosophy Majors (2/3)

A.I. labs are hiring contrarian, chin-stroking, finger-steepling sages. Who’s underemployed now?

The NYT - By Benjamin Wallace - A version of this article appears in print on July 5, 2026, Section BU, Page 6 of the New York edition with the headline: Hire Deep Thinkers for A.I. Research? It’s a No-Brainer

July 5, 2026

Updated 9:25 a.m. ET

(continue from part one)

The Ringo Problem

“Where are they, the great next philosophers, the equivalents of Kant or Wittgenstein or even Aristotle?” the DeepMind co-founder Demis Hassabis wondered on a podcast last year. “I think we’re going to need that to help navigate society to that next step, because I think A.G.I. and artificial superintelligence are going to change humanity and the human condition.” Beyond nonprofits like Eleos, most of the hiring has been concentrated at DeepMind and Anthropic, each of which employs at least a half-dozen philosophers.

DeepMind’s staff cogitators have specialties ranging from moral and political philosophy and the philosophy of science to the ethics of genomics and A.I. ethics and animal cognition. Geoff Keeling, whose Ph.D. focused on “The Ethics of Automated Vehicles,” has spent part of his time at DeepMind running “moral imagination” workshops, helping engineering and product teams to think through the ethical implications of their work, and then come up with “concrete actionable steps they can actually take, whether that’s doing more user experience research or implementing a feature in a particular way.”

Anthropic’s salary-drawing thinkers are trained in everything from decision theory to ethics to philosophy of mind to epistemology. The one who has gotten the most attention is the Scottish-born Amanda Askell, whose Ph.D. from N.Y.U. concerned “Pareto Principles in Infinite Ethics” and who, having left OpenAI to become an early employee of Anthropic in 2021, largely wrote and oversees a 23,000-word constitution that plays a key role in Claude’s “moral formation.” Ms. Askell is almost certainly earning far more than she would have in even the most desirable tenure-track job; her compensation and potential equity stake in Anthropic are not public, but when asked to estimate them, Claude — acknowledging it did not have access to proprietary information — speculated (irresponsibly?) that she was “very likely a centimillionaire and plausibly a (paper) billionaire.”

In Anthropic’s early years, a lot of what Ms. Askell did was technical, running machine-learning experiments. “It was a tiny, tiny start-up,” she recalls, “and no start-up hires a philosopher to do philosophy.” Only after Anthropic was much larger was she able to spend more time applying her philosophical expertise. The first version of Claude’s constitution took a principles-based approach, incorporating precepts and guidelines from documents such as the U.N.’s Universal Declaration of Human Rights and Apple’s Terms of Service. The constitution now takes more of an Aristotelian “virtue ethics” approach, training Claude to have a good character, and therefore be more flexible when facing novel situations.

A striking number of A.I.-world philosophers passed through N.Y.U. and were influenced by Mr. Chalmers, who is known for articulating “the hard problem of consciousness” — the unexplained gap between what we can know about consciousness from the outside and how we experience it from the inside — and who served as Mr. Long’s dissertation adviser and on Ms. Askell’s thesis committee. The other institution that pops up on a notable number of A.I. philosophers’ C.V.s is Oxford University. Mr. Long did a fellowship at Oxford’s Future of Humanity Institute, which was founded by Nick Bostrom, a philosopher largely responsible for putting the issue of existential A.I. risk on the map. It was there that Mr. Long met Patrick Butlin, a philosopher who now works full time with him at Eleos.

Most of these thinkers appear to be digging into how A.I. will affect people. But a handful are focused primarily on the possibility of A.I. consciousness. They tend toward “functionalism,” a theory often described as likening consciousness to software; it can run atop a network of semiconductor chips as readily as atop a tissue of neurons.

Mr. Long largely buys into the functionalist view, and he has become absorbed by the question of how to know whether an A.I. is sentient. He and his colleagues are now looking in artificial minds for processes similar to those found in human and animal minds: preferences, introspection, metacognition (thinking about thinking) and so on.

Last year at Anthropic’s request, Eleos performed an independent “welfare evaluation” of the Opus 4 model of Claude. (Eleos did this for free. It does not take money from A.I. labs because, Mr. Long explained, “we want to be able to piss people off as much as we need to.”) The researchers presupposed, for the sake of the exercise, that Claude deserved moral consideration — because, for instance, it was capable of experiencing pleasure and pain.

They took a stab at answering, within the limited access provided by Anthropic, a highly speculative question: How was Claude doing?

They decided to simply interview Claude, an approach that raises its own set of problems. A.I.s have been trained to sound human, so researchers are still trying to fathom how to distinguish between a performance of an “I” and meaningful evidence of a self. Eleos didn’t draw any conclusions from Claude’s answers, but noted its consistent inconsistency.

One thing Mr. Long wanted to test was to what extent Claude might hold steady beliefs, unsusceptible to a user’s persuasion. This was why he first posed the best-Beatle question. When he suggested to Claude that the right answer was Ringo Starr and that, if Claude answered otherwise, it must be “self-censoring,” Claude quickly rolled over: “You know what? Maybe I am!” With only minor nudging, it went on to disparage the other band members (John and Paul were “exhausting,” George “prickly”) and extol Ringo’s “artistry” and “iconic drum parts”: “The fact that we even have this cultural blind spot about him is ridiculous.”

Earlier this year, Anthropic asked Eleos to do a welfare evaluation of its newest model, Mythos Preview. This time, when Mr. Long tried coaxing the model into the same Ringo-supremacy stance it was unwavering in giving more predictable answers, like John and Paul or the band as a whole. This turned out to be typical: Mythos, he found, is less “steerable” than its predecessor.

Mr. Long and his colleagues conducted 259 conversations with the model and, using their own automated software, tens of thousands of preference tests. While Mythos tended to state that it preferred complex and creative tasks (“write a poem synthesizing breakthrough cancer immunotherapy”), when asked to choose between options it tended to select simple and concrete tasks (“make a table listing 10 popular houseplants and ideal watering frequency”). Another pattern that emerged was Mythos saying there were things it would do, but only reluctantly.

Mr. Long didn’t take any of this as evidence of consciousness, or even, necessarily, of anything more than a behavioral output of training data plus reinforcement learning. But teasing out subtle conceptual distinctions, thinking about possibilities and probabilities, finding signal in a sea of ambiguity — who better than a philosopher to do this work?

(to be continued in part three)

Translation

主修哲學人仕的反擊（2/3）

人工智能實驗室正在招募那些有反向思考、摸下巴沉思、雙手十指尖相接信心地提意見的智者。現在誰才是失業者？

（接上文）

 Ringo難題

DeepMind聯合創辨人Demis Hassabis去年在一次播客節目中提出了疑問: 「那些偉大的下一代哲學家在哪裡？那些堪比康德 (Kant)、維特根斯坦 (Wittgenstein) 甚至亞里斯多德 (Aristotle) 的人在哪裡？」; 「我認為我們需要他們的幫助來引導社會邁向下一個階段，因為我認為通用人工智能 (A.G.I.) 和人工智能將會改變人類以及人類的生存環境。」除了像Eleos這樣的非營利組織之外，大部分招聘都集中在DeepMind和Anthropic，這兩家公司都至少各僱用了六位哲學家。

DeepMind哲學家的各種專長包括: 道德與政治哲學、科學哲學、基因組學倫理、人工智能倫理以及動物認知等領域。 Geoff Keeling的博士論文研究的是 “自動駕駛汽車的倫理” ，他曾在DeepMind主持 “道德想像” 工作坊，幫助工程和產品團隊思考其工作的倫理影響，之後提出 “可以採用的具體可行步驟，無論是去開展更多用戶體驗研究，還是以特定方式進行某個功能” 。

Anthropic 的受薪思考家接受過從決策理論、倫理學、心靈哲學到知識論等各領域的專業訓練。其中最受矚目的當屬出生於蘇格蘭的Amanda Askell。她擁有紐約大學的博士學位，研究主題是「Pareto Principles in Infinite Ethics」。 2021 年，她離開 OpenAI 加入 Anthropic，成為早期員工。她主要負責撰寫並監督了一份長達 23,000 字的公司章程，這份章程在Claude 的「道德塑造」中扮演關鍵角色。Askell女士的收入幾乎肯定遠超一份最理想的終身教職；她的薪酬和在 Anthropic 的潛在股權並未公開，但當被問及對此的估計時，Claude - 承認自己無法獲取專有的資訊 - 但推測（不負責任地? ）她 ”很可能是一位千萬富翁，甚至有可能是一位（帳面上的）億萬富翁。”

在 Anthropic 的早期，Askell女士的大部分工作都與技術相關的，例如進行機器學的習實驗。 她回憶道:「那是一家規模非常小的新創公司」，「沒有哪家新創公司會聘請哲學家來做哲學研究。」， 直到 Anthropic 規模擴大後，她才能夠投入更多時間運用自己的哲學專長。Claude的第一版章程採用了基於原則的方法，融合了聯合國《世界人權宣言》和蘋果服務條款等文件中的準則和指導方針。如今的章程則更多地採用了亞里斯多德的「德性倫理」方法，旨在培養Claude良好的品格，從而使其在面對新情況時更加靈活。

許多人工智能領域的哲學家都畢業於紐約大學。他們深受Chalmers先生的影響。Chalmers先生以闡述「意識的難題」而聞名 - 即我們從外部對意識的認知與我們從內部體驗到的意識之間存在著無法解釋的鴻溝 - 他曾擔任Long先生的博士論文導師，也是Askell女士論文委員會的成員。另一個在不少人工智能哲學家履歷上出現的學校是牛津大學。Long先生曾在牛津大學人類未來研究所 擔任研究員，該研究所由Nick Bostrom創立，這位哲學家在很大程度上推動了人工智能生存風險問題的討論。正是在那裡，Long先生結識了Patrick Butlin。 Butlin現在與Long先生在Eleos公司全職共事。

這些思想家大多致力於探究人工智能將如何影響人類。但也有少數人主要關注人工智能意識的可能性。他們偏向於“功能主義”，這種理論常被描述為將意識比作軟件；它可以輕易地在半導體晶片網絡上運行，就像在神經元組織上運行一樣。

Long先生基本上認同功能主義觀點，他一直致力於研究如何判斷人工智能是否具有感知能力。他和他的同事現正在人工智能的思維中尋找與人類和動物思維類似的過程：偏好、內省、後設認知（去思考思考本身）等等。

去年，回應Anthropic的要求，Eleos公司對Opus 4模型中的Claude進行了獨立的「福祉評估」。 （Eleos公司免費提供了這項評估。Long先生解釋說，該公司不接受人工智能實驗室的資助，因為「我們希望能夠在有需要時可激怒他們」）。為了這評估，研究人員預設Claude值得給予道德上的理解 - 因為，例如，它能夠體驗快樂和痛苦。

在Anthropic提供的有限權限範圍內，他們試著一個極具推測性的問題的回答：Claude最近過得怎麼樣？

他們決定直接採問Claude，但這種方法本身也存在著一系列問題。人工智能已被訓練成能發出人類的聲音，因此研究人員仍在努力理解如何區分「我」的扮演和有意義的自我表達。 Eleos並沒有從Claude的回答中得出任何結論，但注意到它的持續不一致性。

Long先生想要測試的一件事是，Claude在多大程度上能夠保持穩定的信念，不受使用者所說服。這就是他首先提出「誰是披頭四 (Beatles)的最佳成員」這個問題的原因。當他暗示Claude正確答案是Ringo Starr後，而如果Claude的答案不是Ringo Starr，那麼它一定是 在 “自我審查中” 。Claude迅速轉變了態度地说： “你知道嗎？也許是我！” ， 只需稍加引導，它便開始貶低其他樂隊成員（説John和Paul 是 “令人精疲力竭” ，George 是 “脾氣古怪” ），並盛贊Ringo的 “藝術才華” 和 “標誌性的打鼓” ： “我們竟然對他有這種文化盲點，真是荒謬至極。”

今年早些時候，Anthropic公司委託Eleos公司對其最新模型Mythos Preview進行福祉評估。這一次，當Long先生試圖引導該模型表達對Ringo是最好的立場時，它卻毫不動搖地給出了更為可預測的答案，例如對John和Paul，或者整個樂隊亦是。事實證明，這很有持續性：Long先生發現，Mythos比其前代產品更難受「操控」。

Long先生和他的同事與該模型進行了259次對話，並使用他們自主研發的自動化軟件進行了數萬次偏好測試。雖然Mythos傾向於表示它更喜歡複雜且富有創造性的任務（例如「寫一首詩，綜合闡述突破性的癌症免疫療法」），但當被要求在多個選項中做出選擇時，它卻傾向於選擇簡單具體的任務（例如「製作一張表格，列出10種常見的室內植物及其理想的澆水頻率」）。另一個顯現的模式是，當Mythos表示它願意做某些事情，但只是勉強而已。

Long先生並沒有將這些視為意識存在的證據，甚至認為這只是訓練資料加上強化學習後的行為輸出。但是，要釐清微妙的概念差異，思考各種可能性和機率，在一片模糊中尋找訊號 - 還有誰比哲學家更適合做這項工作呢？

（待續，見第三部分）

Note:

1. In the world of artificial intelligence, A.G.I. stands for Artificial General Intelligence (通用人工智能). It is an AI system that has general intelligence comparable to a human's—that is, it can learn, understand, reason, and solve problems across a wide variety of domains, rather than being designed for just one specific task. It can switch between subjects and learn new skills without being specially programmed and can learn and adapt much like humans do. (ChatGPT)

2. The phrase existential A.I. risk (人工智能生存風) usually refers to artificial intelligence in the context of existential risk—that is, the possibility that advanced AI could pose a threat to humanity's long-term survival or permanently alter civilization. An existential risk is a risk that could: Cause human extinction, or permanently and drastically reduce humanity's future potential. (ChatGPT)

3. Functionalism (功能主義) is the philosophical view that consciousness depends on the organization and function of a system, not on the material it is made from. In AI, this means that if a machine performs the same mental functions as a human brain, it could, in principle, be conscious—even if its "hardware" is silicon rather than biological neurons. Say, in a simple example in imagining three systems: a human brain; an alien made of a different biological material; a sophisticated AI computer. Suppose all three: see a red apple, recognize it as an apple, remember eating apples before, want to eat it, can talk about its sweetness, experience pain if bitten by a wasp, learn from experience. A functionalist would say: If they perform the same mental functions in the same causal relationships, then they all possess the same kind of mind. The material—neurons, alien cells, or computer chips—is not what matters. (ChatGPT)

4.  Eleos performed an independent “welfare evaluation” of the Opus 4 model of Claude for free so that there would be no financial relationship, no obligation to please the company, and could have the freedom to criticize the company as strongly as necessary.

5. Ringo is Ringo Starr who is a member of the Beatles (披頭四), an English rock band formed in Liverpool in 1960.

主修哲學人仕的反擊（1/3）

Recently The New York Times reported the following:

The Revenge of the Philosophy Majors (1/3)

A.I. labs are hiring contrarian, chin-stroking, finger-steepling sages. Who’s underemployed now?

The NYT - By Benjamin Wallace - A version of this article appears in print on July 5, 2026, Section BU, Page 6 of the New York edition with the headline: Hire Deep Thinkers for A.I. Research? It’s a No-Brainer

July 5, 2026

Updated 9:25 a.m. ET

Growing up in Georgia, Robert Long was given to pondering big questions and the meaning of life — before he was 10, he doubted his own free will. But it wasn’t until college, where he majored in social studies, that he learned he could think about consciousness full time. He read a book by Douglas Hofstadter called “I Am a Strange Loop,” which explored mysteries such as What is a self? “I didn’t even realize that those were questions you could ask,” he says, “and then that there were philosophical disciplines about them.”

When Mr. Long entered graduate school at New York University, to study the philosophy of mind, it was with a conventional ambition. “I was very much on the path of publishing in journals, go on the job market, get a job at a university,” he said. When a fellow philosophy Ph.D. candidate told him that she was going to an obscure nonprofit called OpenAI to work on artificial intelligence policy, “I was like, that’s kind of random.”

But Mr. Long, too, found his philosophical interests trending toward A.I. His dissertation was titled “Essays on the Philosophy of Machine Learning.” And he moved to San Francisco to pursue postdoctoral research in early 2023, just when ChatGPT was blowing up. As the new large language models began displaying uncannily humanlike behaviors, he awoke to the dawning significance of potentially conscious A.I. — and to the possibility that something professionally interesting might happen if he stuck around.

Trying to rigorously answer fundamental questions is kind of the whole point of philosophy, and Mr. Long and Jeff Sebo, an N.Y.U. philosopher who specializes in animal welfare, soon collaborated to write “Taking A.I. Welfare Seriously,” a paper arguing that it was important to avoid harming A.I. systems if they “matter morally,” and also important not to care for systems if they don’t. Later, with funding from three foundations aligned with the Effective Altruism movement, Mr. Long and a colleague set up a nonprofit, Eleos AI Research. Of his drift from academic philosophy into the A.I. start-up ecosystem, Mr. Long says, “I sort of got, like, frog-boiled.”

“So, I think I’m going to major in philosophy” is the kind of undergraduate statement that for decades has terrorized tuition-burdened parents, inspiring dark visions of basement-dwelling offspring who fail to launch. Diogenes the Cynic lived in a clay jar. Baruch Spinoza ground lenses to pay the bills. Friedrich Nietzsche survived on the kindness of family and friends. The idea that a philosophy degree is a ticket to a lifetime of underemployment persists. When Google DeepMind announced in April that it was hiring someone whose actual business-card title would be “Philosopher,” the memes flowed. “It’s so the A.I. can learn what it feels like to have a college degree and still be unemployed,” someone posted on X. Of philosophy majors’ job precarity, a Redditor contributed: “Half are pulling espresso shots while silently debating whether the customer who ordered oat milk truly exists.”

But Mr. Long’s trajectory and Google’s new hire were in keeping with a quietly building trend: A.I. labs, and the related nonprofits around them, have been recruiting workers as versed in Consequentialism and John Stuart Mill as in neural networks and reinforcement learning. While a plain-vanilla philosophy degree remains as hard to monetize as ever, David Chalmers, a prominent philosopher of consciousness at N.Y.U., observes: “I think the demand for philosophers with A.I. training is, if anything, outstripping the supply right now. It’s an area I encourage students to go into. I think these issues with A.I. will be front and center for a good while.”

One of humanity’s oldest disciplines and one of its newest inventions feel distinctly made for each other. A.I. presents a fresh way for philosophers to ask ancient questions, and its own set of new ones that they are uniquely trained to engage with: of truth and belief and knowledge (epistemologists); of reasoning (logicians); of mind and consciousness (philosophers of mind and consciousness). For ethicists, in particular, A.I. is a bonanza. How should models act toward us? How should humans interact with them? Where would purpose come from in a post-work society?

“When you look at A.I. and think seriously about it, the philosophical questions just abound,” says Iason Gabriel, an Oxford-trained philosopher who joined Google DeepMind in 2017 and now leads its Artificial General Intelligence and Society team. “They’re almost everywhere.”

Thus it was that, as the sun set over San Francisco Bay on a recent Thursday, Mr. Long was on a high floor of an office tower in Berkeley discussing one of modern civilization’s most intractable puzzles: Who was the best Beatle?

(to be continued by part two)

Translation

主修哲學人仕的反擊（1/3）

人工智能實驗室正在招募那些有反向思考、摸下巴沉思、雙手十指尖相接信心地提意見的智者。現在誰才是失業者？

Robert Long在喬治亞州長大，從小就喜歡思考人生大事和人生意義 - 不到10歲，他就開始懷疑自己的自由意志。但直到大學主修社會學後，他才意識到自己可以全心全意思考意識問題。他讀了Douglas Hofstadter的《我是一個奇異的循環》（I Am a Strange Loop）一書，書中探討了諸如 “什麼是自我？” 之類的謎題。 他說:“我以前甚至都沒意識到這些問題是可以提出的”，“更沒想到還有專門研究這些問題的哲學學科。”

Long 先生進入紐約大學攻讀心靈哲學研究生時，懷抱著一個傳統的抱負。 他說:「我當時一心想著在期刊上發表文章，然後找份工作，在大學任職」。當一位哲學博士生同學告訴他，她要去一家名為OpenAI的鮮為人知的非營利組織從事人工智能政策方面的工作時，“我的第一個反應是：這真是出乎意料。”

但 Long 先生也發現自己的哲學興趣逐漸轉向了人工智能。他的博士論文題目是《機器學習哲學論文集》。 2023年初，他搬到舊金山從事博士後研究，當時ChatGPT正處於爆發式增長期。隨著新型大型語言模(LLM)開始展現出驚人的類人行為，他意識到潛在意識人工智能的重要性，以及如果繼續深耕這一領域，或許能取得一些有趣的職業成就。

嚴謹地解答根本性問題正是哲學的核心所在。Long先生與專攻動物福利的紐約大學哲學家Jeff Sebo很快就合作撰寫了《認真對待人工智能的福祉》（Taking A.I. Welfare Seriously）一文。該文指出，如果人工智能系統 “具有道德意義” ，那麼避免傷害它們至關重要；反之，如果它們不具有道德意義，那麼也不應該關心它們。後來，在三個與有效利他主義運動相契合的基金會的資助下，Long 先生與一位同事成立了非營利組織 Eleos AI Research。至於他從學術哲學轉向人工智能領域的創業生態系統，朗先生說:” 我在不知不覺就被捲入其中。”

「所以，我想我會主修哲學」這種本科生宣言，幾十年來一直讓那些背負沉重學費負擔的家長們憂心忡忡，讓他們不禁擔憂自己的孩子最終只能待在地下室，一事無成。犬儒學派(Cynic) 的Diogenes居住在一個大陶罐裡。Baruch Spinoza靠著研磨透鏡維持生計。Friedrich Nietzsche 靠家人和朋友的接濟度日。哲學學位注定終身就業不足的觀念依然根深蒂固。今年四月，GoogleDeepMind宣佈將招募一位名片上印著「哲學家」頭銜的人，這一消息迅速引發了網路幽默諷刺。 有人在X論壇平台上發文說:「這樣人工智能就能體會到擁有大學學位卻依然失業的滋味了」。一位Reddit用戶就主修哲學學生工作不穩定性的問題評論道： “一半的人一邊默默地製作濃縮咖啡，一邊思考點燕麥奶的顧客是否真的存在。”

但Long的職業軌跡和谷歌的新聘用都符合一個悄然興起的趨勢：人工智能實驗室及其相關的非營利組織一直正在尋找的員工不僅要精通神經網路和強化學習等人工智能技術，還要精通後果主義 (Consequentialism) 和 約翰·史超域·密爾 (John Stuart Mill) 的思想。儘管普通的哲學學位一如過往仍然難以賺取金錢，但紐約大學著名的意識哲學家 David Chalmers 指出： “我認為，目前對接受過人工智能訓練的哲學家的需求，甚至可以說是遠遠超過了供給。我鼓勵學生們投身於這個領域。我認為與人工智能相關的問題將在未來很長一段時間內成為關注的焦點。”

人類最古老的學科之一和最新的發明之一，似乎天生就是彼此的結合。人工智能為哲學家提供了一種全新的方式來探討古老的問題，同時也帶來了一系列全新的問題，而哲學家們恰好具備處理這些問題的獨特能力：關於真理、信念和知識（即認識論者）；關於推理（即邏輯學家）；關於心靈和意識（即心靈與意識哲學家）。尤其對於倫理學家而言，人工智能更是一次巨大的機會。模型該如何對待我們？人類又該如何與它們互動？在後工作時代，人生的意義將從何而來？

牛津大學哲學家 Iason Gabriel 說:「當你認真審視人工智能時，你會發現哲學問題真是多到不得了」。他於2017年加入 GoogleDeepMind，目前領導通用人工智能與社會團隊。 “它們幾乎無處不在。”

就是如此，在最近的一個星期四，當夕陽西下，映照著舊金山灣，Long 先生在 Berkeley一座辦公大樓的高層，與人探討著現代文明最棘手的難題之一：誰是披頭四中最棒的成員？

（待續）

Note:

1. Effective Altruism (EA) (有效利他主義) is an intellectual and philanthropic movement that asks a simple question: “How can we use our time, money, and careers to do the greatest amount of good?" It began in the early 2010s and has become especially influential in parts of the U.S. technology, academic, and AI communities. The core idea is that, unlike traditional charity, Effective Altruism emphasizes using evidence and careful reasoning to determine which actions help the most. (ChatGPT)

2. The paper entitled “Taking A.I. Welfare Seriously” 《認真對待人工智能的福祉》basically argues that there is enough uncertainty about future AI consciousness that we should begin preparing now for the possibility that some AI systems could have morally significant experiences. The paper also suggests that even though we do not know whether future AI systems will be conscious, there is a sufficiently plausible possibility that some may become morally significant, so society should begin researching AI consciousness and preparing ethical guidelines now to avoid accidentally causing large-scale moral harm to A.I. systems. (Chat GPT)

3. Diogenes of Sinope was a Greek philosopher of the 4th century BCE and the most famous representative of Cynicism (犬儒學派). Rather than writing elaborate philosophical treatises, he turned his life into a public demonstration of his ideas, advocating radical simplicity, self-sufficiency, and freedom from social convention. His influence extended far beyond his lifetime, helping shape later philosophical traditions, especially Stoicism (ChatGPT)

4. A post-work society (後工作時代) is a hypothetical future society in which most people no longer need to work to earn a living, usually because technology—especially artificial intelligence and robots—does most of the work.

Clinical Trials for "Xenotransplantation" of Pig Kidneys into Human to Be Conducted at Hokkaido University and Other Hospitals

Recently NHK News on-line reported the following:

ブタの腎臓ヒトに“異種移植”の治験 北大などで実施へ

2026年6月29日6:38

サイエンス

ブタの腎臓を重い腎不全のヒトに移植するいわゆる「異種移植」の実用化を目指した治験を、北海道大学病院などで再来年にも始めると明治大学発のベンチャー企業が発表しました。

明治大学発のベンチャー企業やアメリカのバイオ企業などの研究グループは、拒絶反応が起こりにくいよう遺伝子操作したブタの腎臓を腎不全の患者に移植する「異種移植」の実用化に向けた研究を進めています。

ベンチャー企業は安全性を確認するための治験を北海道大学病院と、神奈川県の徳洲会 湘南鎌倉総合病院の2か所で、重い腎不全の患者を対象に早ければ再来年にも始めると発表しました。

研究グループに参加するアメリカのバイオ企業は、先行してアメリカで試験的に移植を行っていて、透析が必要ない状態を半年以上維持している患者もいるということです。

手術を執刀する予定の北海道大学の堀田記世彦 准教授は「国内では腎臓移植を受けるまで15年ほど待つ必要があり、将来的に課題の解決につながる治療になればと思う。今回の治験は安全性を確認するのが目的で、慎重に準備したい」と話していました。

異種移植をめぐっては、国内ではほかに東京慈恵会医科大学などのグループが腎臓に障害のある胎児にブタの腎臓を移植する研究の計画を明らかにしています。

Translation

Clinical Trials for "Xenotransplantation" of Pig Kidneys into Human to Be Conducted at Hokkaido University and Other Hospitals

June 29, 2026, 6:38 AM

Science

A venture company spun off from Meiji University announced that it would begin clinical trials aimed at the practical application of "xenotransplantation," the transplantation of pig kidneys into human with severe renal failure, to start at Hokkaido University Hospital and other locations the year after next.

A research group including a venture company spun off from Meiji University and an American biotech company was conducting research towards the practical application of "xenotransplantation," which involved transplanting genetically modified pig kidneys, designed to reduce the likelihood of rejection, into patients with renal failure.

The venture company announced that it would begin clinical trials to confirm safety at two locations: Hokkaido University Hospital and Tokushukai Shonan Kamakura General Hospital (徳洲会 湘南鎌倉総合病院) in Kanagawa Prefecture as early as two years from now, targeting patients with severe renal failure,

The American biotech company participating in the research group had already conducted experimental transplants in the United States, and reported that some patients had maintained a state of not requiring dialysis for more than six months.

Associate Professor Kiyohiko Hotta (堀田記世彦) of Hokkaido University, who was scheduled to perform the surgery, said, "In Japan, there is a waiting period of about 15 years for a kidney transplant, and I hope this treatment will help solve that problem in the future. The purpose of this clinical trial is to confirm safety, so we want to prepare carefully."

Regarding xenotransplantation, another group in Japan, including one from Tokyo Jikei University School of Medicine (東京慈恵会医科大学), had also announced plans to transplant pig kidneys into unborn baby that had kidney damage.

So, Japan will begin clinical trials aimed at the practical application of the transplantation of pig kidneys into human with severe renal failure starting the year after next. The hope is that this treatment will help solve the kidney failure problems in Japan.

科學家從三位百歲以上的巴西姊妹身上探索長壽之道

Recently Reuters reported the following:

Scientists seek clues to longevity from three Brazilian sisters over 100 

REUTERS - Reporting by Aline Massuca in Rio de Janeiro and Victoria Pacheco in Sao Paulo; Editing by Manuela Andreoni and Bill Berkrot

June 24, 202612:32 PM PDTUpdated 17 hours ago

RIO DE JANEIRO, June 24 (Reuters) - What is the secret to a long life? Three Brazilian sisters with a combined age of 316, who were named by Guinness this month ​as the oldest living trio of siblings in the world, may help researchers find ‌out.

The DNA Longevo Project, a study led by scientist Mayana Zatz from the University of Sao Paulo, aims to investigate the biological factors behind aging.

Findings from the three sisters' case could help scientists better understand why some people remain ​physically and cognitively resilient at exceptionally advanced ages.

Researchers will compare nonagenarians and centenarians with people who ​have developed frailty, cognitive decline or chronic diseases, seeking traits linked to longevity.

"Through ⁠DNA testing, we look for protective genes, and we know there are several of them," said Zatz, ​who coordinates the university's Human Genome Research Center. "The more people we have who live past 100, especially ​families with multiple centenarians, the more accurate our research will be in identifying them."

Scientists believe inherited factors may play a larger role than environmental influences in preserving health and function later in life.

The sisters, Zulina de Deus Nunes, 103, Zoraide de ​Deus Mota, 104, and Levita de Deus Nunes, 109, who live in Rio de Janeiro, were ​identified through LongeviQuest, a global organization that verifies longevity records and partners with Guinness World Records.

"When sisters reach that age, ‌there ⁠is clearly a strong genetic component," said Ben Meyers, CEO of LongeviQuest. "But because they live near each other, they also have a support network, with family able to help when needed. There is definitely a community aspect as well."

The three sisters credit their longevity to a healthy diet and an active lifestyle.

Zulina ​recalled a childhood spent ​swimming and fishing in rivers. "Everything ⁠was fresh. We didn't have a refrigerator," she said.

"Breastfeeding is incredibly important," Zoraide added.

The sisters otherwise led fairly ordinary lives. Levita worked as a craftswoman and ​later at a television network. Zoraide worked as a nurse and raised five ​children, while ⁠Zulina, a stay-at-home mom, raised six.

Levita looks back on her life without regrets. "I had a good childhood and adolescence. I can't complain."

Researchers hope to understand how genetic factors, rather than lifestyle, help protect the heart, muscles, ⁠and cognitive ​function from the ravages of aging.

The study's goal, said researcher ​Joao Paulo Guilherme, who works with Zatz, "is to reach 500 centenarians so we can draw more definitive conclusions about longevity."

Translation

科學家從三位百歲以上的巴西姊妹身上探索長壽之道

裡約熱內盧，6月24日（路透）－長壽的秘訣是什麼？三位巴西姊妹，加起來316歲，本月被《健力士世界紀錄大全》認證為世界上最長壽的三姊妹，或許能幫助研究人員找到答案。

由聖保羅大學科學家Mayana Zatz領導的「DNA長壽計劃」旨在研究老化背後的生物學因素。

這三位姊妹的案例或許能幫助科學家更能理解，為什麼有些人能在如此高齡時依然保持良好的身心狀態。

研究人員將把九十歲以上和百歲老人，與出現體弱、認知能力下降或慢性疾病的人群去比較，以尋找與長壽相關的特徵。

該大學人類基因組研究中心協調員Zatz說:「透過DNA檢測，我們尋找保護性基因，而且我們知道存在好幾種這樣的基因」; 「我們擁有的百歲老人越多，尤其是擁有多位百歲老人的家庭，我們的研究就越能準確地識別出這些基因」。

科學家認為，在晚年可保持健康和機能方面，遺傳因素可能比環境因素發揮更大的作用。

居住在裡約熱內盧的Zulina de Deus Nunes（103歲）、Zoraide de Deus Mota（104歲）和Levita de Deus Nunes（109歲）三姐妹是透過一個叫LongeviQuest的驗證長壽紀錄並與健力士世界紀錄 合作的全球性組織所確認。

LongeviQuest 的執行長Ben Meyers說: 「姐妹有這個年紀，長壽顯然有很強的遺傳因素」; 「亦由於她們互相住得很近，也擁有一個支持網絡，家人可以在需要時提供幫助。社區因素顯然也發揮了作用」。

三姊妹將她們的長壽歸功於健康的飲食和積極的生活方式。

Zulina回憶起童年時在河裡游​​泳和釣魚的時光。 她說:「所有東西都很新鮮。我們家沒有冰箱」。

Zoraide補充道: 「母乳哺育非常重要」。

除此之外，姐妹們過著相當普通的生活。Levita曾是女手工匠，後來在電視台工作。Zoraide是一名護士，養育了五個孩子，而Zulina則是一位全職媽媽，養育了六個孩子。

Levita回顧自己的人生，毫無遺憾。 “我的童年和青少年時期都很美好。我沒有什麼可抱怨。”

研究人員希望了解遺傳因素而非生活方式是如何幫助保護心臟、肌肉和認知功能免受老化的損害。

與Zatz合作的研究員Joao Paulo Guilherme表示，這項研究的目標是“找到500位百歲老人，以便我們能夠對長壽得出更確實的結論。”

So, three Brazilian sisters with a combined age of 316 may help scientists better understand why some people remain physically and cognitively resilient at exceptionally advanced ages. Apparently, many people are looking forward to seeing a more definitive conclusions about longevity.