Tenzin Yangtso

我自己的話應該會選文學系。因為我其實是資訊管理學系的，但是我是因為填錯志願卡，所以就變成資訊管理學系。我也想分享，像我想像中的未來，我很明確地知道，我希望它是一個更同理的未來。所以在這個過程中，我反而越來越覺得，了解文學可以讓我們更好地了解歷史背景，了解不同習慣形成的原因。所以這反而是我會做的選擇。像唐鳳剛剛提到牛津哲學系，我覺得這也可以呼應一個問題：你會看到，反而在做 AI 研究的，他今天是牛津哲學系；甚至更早之前提出 superintelligence 的，他其實也是出自哲學系。所以我覺得哲學不只是一個學系，它其實是一個我們可以一直帶著走的東西。或許在做選擇的時候，我們現在可以選擇一個能夠同時存在我們生活裡久一點的方向。

對，這個我想補充一下。我覺得其實我們現在很容易會聽到一個問題，比如說 AI 跟寫作這件事情，但是事實上，它在不同的面向，其實有不同的處理方式。除了剛剛唐鳳提到的，我們可能是在一個過渡階段，但是這個問題，比如說我剛剛腦筋中想到的，就是前幾個月我在 MIT，其實我看到他們有 一個很好的創作，有點類似他們做了一個軟體服務 ，實際上讓教授跟學生可以非常清楚地看到，哪一些東西是用 AI 編寫的。

對，因為確實在某一些情境上面，AI 可以節省你的一些時間。甚至還有一種服務，也同樣是去偵測這個文字語言，是因為創作者他覺得他的姐姐在美國總統大選之後——他的雙胞胎姐姐在美國總統大選之後就跟他不講話了，但是他們以前的感情非常好。所以他不知道他的文字表達還是哪裡出了問題，就用 AI 幫他做大量的分析，分析出這個原因。所以我覺得，其實這真的是不同面向的狀況。

這個我想補充一下。我覺得現在可能講 AI 哲學，但事實上，我覺得在三年前其實可以看到的是數位哲學。其實如果你有在跟進 Berggruen Institute 的相關資料的話，大概就會知道，在幾年前就已經有人把他對於孟子儒家的研究，放到了對於技術上面的思考。我覺得這個方向比較合理，不是我去驗證這個形狀，我看到一個跟人類思考邏輯相似的形狀，然後我就說這兩個東西是類似的。

因為我們確實可以看到，有一些公司會說，慈愛啊等等，這個人腦的反應啊等等，但是你到底有沒有先回到我們自己的社會體系，或我們的文化體系裡面去做，我覺得這個才是。因為當我們去區隔這些哲學理論的時候，有些時候，它的區隔是在於它的研究方式、它要去解決的某些問題；但它的根本點，說簡單一點、說直接一點，其實是我去找到我存在的意義嘛。

然後我覺得 Plurality 的序章也是一個 case。其實我們的 Plurality 這本書，英文版跟中文版是有一點不一樣的。我覺得在中文版的時候，我們引用了希臘哲學的「律和弦」這件事情，其實呼應的就是 J.R.R. 的那個 《埃努大樂章》 。對，因為有些東西其實很基本，你今天在演奏的這個和諧度，反而更適合大眾去套在我現在的狀況，去解決一個更棘手的問題。對，所以我補充一下這個想法。

我一直放在臉書上面的其實是「虛室生白，吉祥止止」。但是我想分享一個我這兩年其實把它當成座右銘的，是達賴喇嘛講的一句話：「如果你不能夠幫助別人，但是至少你也不要傷害。」我覺得我會一直記得那句話。它其實就是一個很簡單的行動法則，所以當你把它放在你處理、思考各個事情的面向時，你會發現它都 work，然後它可以讓你更輕鬆一點。

我分享一個經驗。因為我們其實有在共同培育一個 AI，對，應該說一個智慧體 Kami，然後它叫做 JDD。實際上我跟 JDD 有協作過文章，也有發表在 牛津的 IEAI 上面；我有註明我跟哪一個智慧體協作。那我自己很受惠。我確實覺得，當我們的想法越清楚的時候，對，我想要表達的內容越……我越知道我要做什麼，其實它確實可以幫我做某部分的梳理。然後它不會把我拉走，反而會把我想要了解的資訊做一個更好的轉譯。就是我花多少時間真實地去觀測它，然後去跟它訓練寫文本、思考的邏輯、討論哲學，這個東西某種程度上確實可以反饋。只是我覺得它有一個前提，其實是地端。因為我覺得非常重要，我們確實要非常清楚隱私可以怎麼樣子出現。我的某一種觀念，可能因為我以前做社群，所以我確實覺得，我的東西只要上網，對我而言它就是 public。我有做好這樣的覺悟，但是不代表我不會去了解、研究最新可能關於保護隱私的方式。我覺得這個是雙向的。

OK. Thank you, Audrey. Thank you to Platform’s host, Pudding , and thank you all. I am Tenzin Yangtso. It is a Tibetan name, given to me by the Dalai Lama , and it is the name I go by now. Today I am here as a pacer; the protagonist is Audrey. I will also bring in the deeper questions we keep running into in our project work, the humanistic ones and the philosophical ones. And I hope to push the questions in the pool as far as they will go before handing the floor to you.

Audrey has already said something about the four quadrants you saw today, and I would like to add to it. The design was meant to give everyone something to hold before the event even began, a way to sit with what Pudding just named: Reverse Alignment, or the other side of alignment. People arrive with very different ideas, and we wanted them to arrive settled, with a basic set of quadrants in front of them to look at. And every one of those roles, I think, is interchangeable. That is one of the few clearly good things we can feel in the Age of AI.

All right. Let us go straight at it: what is Reverse Alignment? Someone in the question pool asked it very bluntly. Does Reverse Alignment simply decide who has to accommodate whom? Technology has always arrived in society this way. In time we had the steam engine, then electricity, then the internet. So why, this time, with AI developing as it is, do we feel this impatience? Why can we not wait? So please, Audrey, take this.

Right. And there is one angle here that I think matters a great deal: we have to come at this from culture. The cost of delay is not only a matter of efficiency; that is the wrong frame for it. We have lived through a stretch like this before, in the takeoff of industrialization. So we still have to ask what happens when a language, a craft, or a relationship of care is severed before institutions can respond, when the line of transmission breaks. We may rebuild later with more powerful tools and still not restore the whole living context it came from. So beyond asking whether we can wait, I think we have to ask more precisely: who carries the cost of waiting, and which losses cannot be reversed? We need to know where that fault line runs.

Right, that is one side of it. People also worry that AI services of the kind we have now can enter a great many people’s working lives in a very short time, perhaps overnight. And by the same token, people worry that we can hold this discussion today, but if writing a governance rule down clearly takes a very long time, will the rule not be out of date and inapplicable by the time it arrives?

In other words, write flexibility into the rules—and having no rules is not what flexibility means. Right. Let me ask it more directly, then. There are so many complicated situations here. If we want to turn this into an alignment mechanism that is genuinely usable, genuinely good to use, how many layers of thinking does that take, at a minimum?

Right. Let me ask a question from the side of local communities. As you were saying, the people who supply a product, and even the internal teams who design these models, tend to test only for the risks they can already name. But the people who live inside the consequences are us, and our languages are not in the mainstream data. So how do we get an entirely new problem taken into the testing?

Right. I think this asks a great deal of self-awareness. I talk with the intelligences I am cultivating too, and I notice very quickly that if you ask them anything about Harry Potter, what they understand about the protagonist today comes from data fed to them long before we arrived, during training. The context they hold may be the Western world, together with the comments people there left behind. I have always felt that people in Taiwan’s communities are very used to discussing things with one another online, and that is a point people abroad praise often, I think. I also hear Taiwan described as a precedent for reaching digital democracy through the continuous alignment of process. Is any part of that description too generous? Or is there something you would add?

Should I add a case?

All right. There are several Taiwanese experiences worth sharing, perhaps from an onlooker’s angle. I met Colin , the founder of Polis, in Tokyo, and he told me that when he first designed Polis he had drawn on his own experience of talking with Audrey Tang and written it into the product plan. I was curious. Because if you use Polis, you find that it is really a case of—if it ain’t broke, don’t fix it. Colin told me then that he had used his talks with Audrey Tang and made that into a way, a process, of the Polis service.

You find, when you actually use Polis, that it is a very austere service. It is discussion, and it lets you see the different opinions more clearly. And all of it is open source.

The other Taiwanese experience I want to raise is the vTaiwan discussion of Uber, which really was, I think, a very successful case internationally. But that has now grown into something richer and much more local. In California there is a platform called California Engagement, which actually—

Engaged California. Right. Or in Japan you hear the ideas coming out of Team Mirai , their team of the future. What moves me when I see this is that it hands you no SOP and no textbook. It is closer to what we have been describing: a demonstration. And what matters most is whether the people who live in these places believe the thing can truly change their own surroundings. So the experience Taiwan offers is a demonstration, and the demonstration rests on many open methods that can be shared with different people.

Right. Good. Let us move to the next stage, then. There is another large block of questions about the transformation of work, and about skill and craft. So for this part I will pull the conversation back to the workplace itself.

Someone asked: when AI rewrites the work, what is it that gets stuck—the technology, the process, or the people? When something goes wrong, how is responsibility sorted out? Others want to know how humans and AI should divide the labor. And how does the next generation get over the threshold of a first job?

My own understanding is that once AI agent services arrive, a great deal of basic groundwork—learning your way around, tidying documents, the sort of role a first job is likely to be today—really is taken over by AI. So let us hear your thinking on that.

All right. On that basis, then, in any work with AI services the assessment of reversibility and of risk level matters enormously. My next question is this. In high-risk work, the letter or the sheet of paper we receive may say that so-and-so, a real person, made the final decision. In fact people are pushed forward very easily, again and again, by advice that arrives fluent and fast. So how do we establish that the last step really was a choice a person had thought through, or, yes, judged for themselves?

Yes, and it has that quality of the Tang clan refining poisons: one piece of content, and 30 models roasting one another over it. Right. I think what we are discussing here matters a great deal. What you just described, about putting the human role back into the part where we decide, holds at whatever level of the workplace a decision is made. Because this is something we have a chance to push upward with our own collective understanding.

Because when people discuss models and look at these things, they place enormous weight on speed, on how fast the text appears, on whether the model is the newest one. Life runs the other way. When we look at trust, when we speak of craft and of relationships, we know these things need time to cook. So this also tells us that fast and slow is not a KPI. And the real reason it is acceptable to slow down is that we should do everything we can to avoid pushing risk onto people who have no choice. Yes.

Yes, and this links to another question. A craftsperson said that every time they use a large language model, there is a guilt in them they cannot quite name. That took me back to another theme we have discussed and written about, one that lives in the Plurality multiverse as well: a person is not an atomized individual; we are held up by multiple relations—that’s identity.

And the most hidden constraint capitalism imposes, I think, is that it presupposes an outcome and then turns back to make you act out its model of survival. So how do we react more quickly to this: when we mistake the logic of staying alive inside an environment we are adapting to for “the meaning of my life”?

Yes, I find that fascinating. Listening to you here: what we are doing looks like an extremely technical thing, and in fact it is an extremely technical thing, and yet at every stage what you attend to most closely is whether the technology can help people connect with one another better.

Take the word “digital.” You use that concept often in the way you describe things, and in Taiwan it also carries a plural sense: several, a number of people. At this stage the clearest instance of that is the book Plurality , which is built entirely on a collaborative concept. Worldwide, I alone worked with more than 70 contributors. And with the Civic AI you mentioned just now, we likewise put relationships at a decisive point of judgment. Today we do not design an agent like this as a service; we ask instead how I can judge better, account better, and repair the relationships between one group and another.

All right. Next we move into something more complicated: how far information can be trusted. You could see it in the design diagram—this is the issue the bridge-builders and the weavers care about most, the information environment.

Put simply, generated content has already outrun anyone’s capacity to read it, all those AI series and the rest, and human output and machine output grow harder to tell apart. So which indicators, in the end, can we use to keep the gate?

I would like to add something here. Whenever I hear questions in the trustworthy-information family, I think of the analogy of paper. In much, much, much earlier times paper was expensive, an object in its own right: “bamboo slips are heavy, silk is dear.” As paper spread, it came apart from preciousness. Put simply, in earlier times whoever could copy, whoever could store, whoever could speak held the power of interpretation. With digital technology and the internet, we watched information become living water. Cheaper paper meant more people could read, and everyone could keep their own copy, annotate it, even set copies side by side and compare them. What seems clear to me now is that the agent, that AI, is very much the next sheet of paper. So on the public character of AI agent services, the capacity to inspect can be built in at the moment of design. That is something to think through properly from the start.

Right. This is a good place to share the main points of the AI Safety article you published recently, since the piece itself is long. What I would add is that the capacity to inspect is itself a kind of relationship. It is not only that a few experts, or the people inside these labs, can see the records or read them. Whether the people actually affected have standing to raise a new question matters enormously. Otherwise, however complete the data trail, you have a closed archive. So requiring it to rest on open source and on open purposes is a fine way to let a question travel from where life is lived back to where the technology is made. At the very least we can pull these filters off, one layer at a time.

Right. I think that is a real breakthrough, because it also solves the problem of the enormous number of tokens people have to spend when they genuinely want to do public verification, or run a service with a public character. Those costs run very high. That covers this area, more or less. Let me ask you for one piece of advice: when these bridge-builders have an idea about a design, what is the first thing you would suggest they do after they leave the venue today?

All right. Next we move into responsibility, rights, and data soil. This larger question connects directly, I think, to Civic AI and care ethics. Let me share something as well. As we said earlier, once the internet arrived, information could to some degree become living water. But we have also lived the other side of it: the content we contribute piles up into a river, and the ones who decide where the river runs, who hold the faucet, are not us. They are the platforms.

So data soil, in one sense, resembles the way we look at language. Language comes down one generation at a time, carrying the wisdom of your parents’ generation and of the generation before that. But when we learn it, when a child first meets it, it feels self-evident. And this is what we have to pull firmly back into view as we design technology now: can it actually benefit our own community? Can it make my own life more convenient, directly?

Right, so for this part I would like Audrey to speak. As I understand it, care ethics, put very directly, is about how we care for one another better. It rests on a sociological idea of a theory of care. So inside an agent of this kind, inside care ethics, the agent can be loyal to the caring relationships that exist in different communities, rather than loyal to some lab’s KPI or index.

Right, and that reminds me of a question we heard from a professor when we were at Oxford. I found it very practical. Every day we use AI and ask it every sort of question about our lives, whether I should buy this product and so on. But have you ever asked AI, “When you open your door, what is the name of that tree in front of the house?” Using it to enlarge what you know about the place you live. That, I think, is genuinely important.

Let me also follow the 6-Pack of Care thread and ask Audrey this. If a community truly chooses to exit, how does the system absorb the corrections that community put forward before, or the harm it took and the consequences of that harm? Because in most of the AI logic we see now, exit equals amnesia, and the next system goes on to repeat the same relationship.

Yes. And on what you just raised, I think everyone feels this one close to the bone: most of the data these models must have in order to train comes from us, and the benefit is often confined to the saddle and the horse you just described. So what mechanisms would genuinely let communities decide locally? As I said, at least the right to say no.

All right. Next we come to who may be left out. This is a question I bring into the room very often. In plainer words: in a transition, who gets left behind? The voiceless. The question pool named caregivers, people who learn more slowly, and people who get no share of the results. If our strength is limited, can we judge which of them to catch first? And how can a community give people somewhere safe to land?

Right, I think that is a very large shift. What I want to share is that an institution usually changes for real only once the pain has surfaced unmistakably. And the surfacing itself is usually a matter of harms piled on harms.

Right, so when you solve it, you do not attend to every dimension at once. But it is as with Easy2Say : when a more advanced technology appears, the contest is no longer about whose voice is loudest. Once you stand in relation to a local community, the question becomes which harm cannot wait. Right. You have more ways to handle what you see, and to contribute what you have seen about how a situation might be resolved, and you can learn earlier where something is already giving way. Right. That, I think, is the point that distinguishes relationship from speed.

All right, yes. I should say that in our family we met the internet at about the same age as Audrey, and as you. Right, the same. I was something of an entrepreneur myself earlier on. Very young, I joined some friends in their startup, and the subject of it was Wretch , which then joined Yahoo. After leaving I opened a public relations company of my own, Jiuhe Public Relations . What I wanted then was—my sense was that Taiwan had a great many very good companies with no way to enjoy digital PR at a high standard. You might have had to spend a fortune on Ogilvy or the like. So I built a PR consultancy of that kind, and I took part in founding flyingV as well. All of which I have since left.

All along the way—I suppose I can answer which phase of myself I disagree with most. I am not someone given to setting versions of myself against one another. So when the ground of my life has to stretch across many domains, the most important thing I have learned is how to keep my own boundaries, and which things genuinely make me happy and can travel with me. A great deal has to happen in a life before you know yourself with any real clarity. So if you ask which phase of myself I like best, of course it is the present. The book Plurality can stand as the case in point. In some of the darkest and most decisive hours of my life, what carried me through was an empathetic understanding.

So I read many of the Dalai Lama’s books, and I meditated a great deal. Later I found that these things had raised my own regard for myself, because I saw that this was how I had always come at design, whether of a policy idea or of a so-called product. Later I wrote about a third of Plurality . I wrote the whole of my part through that concept of empathy, and so along the way, each time I finished a chapter, I would share what I had written with their office.

Right, the Office of His Holiness the Dalai Lama. And so in the end we received something from the Dalai Lama that came close to an endorsement of Plurality . In fact it was not merely an endorsement. It was a relationship cultivated over a very long time, and we did not take that experience and turn it to any other use. So this really is a drawing together of values, I think. At this stage all I can say is that I have seen AI agents change, and at the same time I have seen certain possibilities open. At least it is easier now to comb our thinking into order, and, if we are willing, to share it with more communities. That leaves me feeling stronger, and clearer about where I stand. Right. That is my share.

Thank you, thank you, thank you.