Cédric Villani：人类与机器的错乱关系还会维持【AI大神说】
曾几何时，01哲学小编认为，哲学家是这个世界上最性感的职业，因为哲学家看起来总是知道那些你还不知道、却又决定你命运的真相。其中，催人渴求的未知与性的魅惑有时候根本无法区分，更何况遇上特别帅气的男哲学家，例如【AI大神说】上一集介绍的马库斯・加布理尔（Markus Gabriel），或者你还可以想想沙特、卡缪或者维根斯坦⋯⋯
Markus Gabriel：不要神化人工智能【AI大神说】
怎么，原来你们都不同意吗？认为这都是哲学小编自己的 FF 吗？好吧！如果连擅长营造语言晕眩的哲学家，都没办法跟性感相关联，那么离群索居、枯坐冷板凳，终日操作公式记号与逻辑演算的数学家，想必就更困难了吧？
然而令人难以置信的是，当代法国竟然有一位“数学界的 Lady Gaga”！他是媒体的宠儿──镜头总是聚焦他的中分长发、他那十九世纪花花公子般的衣著与一枚个人标志性的蜘蛛饰物。不过最重要的是，他真的是一位彻头彻尾的数学家，研究的课题诸如“regularizing effects of grazing collisions in kinetic equations”和 “Space-inhomogeneous convergence to equilibrium”（小编就不献丑把它们强翻成中文了）。2010年，他还获得了数学界的奥斯卡奖──菲尔兹奖（Fields Medal），以表彰他在代数和几何领域的卓越成就。他为自己设定的重要任务，是将数学学科的乐趣与迷人之处借助媒体向大众宣扬。
他就是赛德里克・维拉尼（Cédric Villani）教授，索邦大学亨利庞加莱研究所（the Institut Henri Poincaré）总监，更是法国总统马克龙（他最近陷入麻烦，必须面对半世纪以来当地最大规模暴动）派往世界各地宣传法国人工智能政策的特使。可见，他还是一位政治家。就在刚刚过去的十一月，维拉尼教授到访香港；借此机会，01哲学编辑与维拉尼教授在香港科技大学商学院碰了面，并向他提出了两个关于AI的哲学问题。让我们一起看看这位数学大神对于 AI 怀有怎样性感的观点。
【以下附上英文原文对话，以供读者参考】
01哲学：第一个问题关于“愚蠢”。电影、娱乐与流行科幻小说中的 AI 形象一定程度上具有误导性。我自己更喜好“机器智能”这个说法而不是“人工智能”。机器智能是基于概率来发挥功能的。为了找到问题的最恰当的解决方案，机器愚蠢地需要执行大量运算。而我们人类并不总是先进行大量运算才把问题解决掉。我们先理解问题，然后便迅速将问题解决了。关于机器的愚蠢而不是智能，您有什么看法？
01 Philosophy: The first question is on stupidity. The images of AI in films, entertainment contents and popular science fiction are misleading in some sense. I myself prefer the term machine intelligence to artificial intelligence. The way the machine functions is based on probability. In order to figure out the most proper way to solve the problem, the machine, stupidly, needs to do a huge number of calculations. We humans are not always solving problems by firstly performing a huge number of calculations. We understand the problem and then solve it immediately. What do you think of the stupidity of the machine, instead of its intelligence?
赛德里克・维拉尼：是啊，这是一个很好的问题。在现今关于人工智能的算法中并没有智能可言。它确实是一部愚蠢的机器，围绕著大量概率、统计、关联性等问题工作。一些科学家甚至会说那根本就不是科学，因为机器都在努力复制任务而并不理解它们究竟在做什么。在医疗领域，机器能够定位癌症却并不知道癌症意味著什么。而这却是可行的。一部自动翻译机器恰恰在变得愚蠢、以自动复制策略取代智能语法的、语义学的、本体论的方法时才更为有效。这对人类智能来说是相当烦恼的。
Cédric Villani: Yes, it's a very good question. In current algorithm about artificial intelligence, there is no intelligence. It's indeed rather a stupid machine, working on a lot of probability, statistics, correlation etc. Some scientists will even say that's not science, because they strive to reproduce the tasks without understanding what they are doing. In health, it would be about identifying cancer without knowing anything about cancer. And it works. An automatic translation became much better when it turn to a stupid, automatic reproduction strategy, rather than intelligent syntactic, semantic, ontological approach. Very vexing for human intelligence.
然而，将会有一个时刻，正如我在讲座中所坚持的那样，在那时概率方法将与更为本体论的方法结合起来。这是一条路径，在其中机器的强力破解方法已不再足够。某些智能，即原创思想，将必然会发生。而且，关涉到对于人类认知过程的理解，以及我们可以从自动化智能与人类智能的来来回回当中学到的东西──如今它们还大相径庭，将会有极多的边缘地带被发现。
However, there would come a time, I insist this in my talk, in which the probabilistic approach has to be combined with a more ontological approach. And it is a way in which brute force would not be sufficient. Some intelligence — original thinking ── would have to take place. And also, there are enormous margins to be found in respect to the understanding of our cognitive processes, and what we can learn back and forth from automatic intelligence and the human intelligence - so far they are extremely different.
还有我们必须承认某些案例中的算法非常聪明从而改变了我们的知识。或许最瞩目的就是围棋博弈。在由 DeepMind 开发的机器中，机器做出的一些举动是完全不可预测的，并不仅仅是复制人类知识。它发现了某些新的举动是人类从来没有思考过的。所以，人工智能的愚蠢会挑战人类智能并且帮助我们寻觅出新的领域──智能的领域。这并不是非黑即白。
Also we have to acknowledge that these algorithms in some cases have found very clever and thus they change our knowledge. Maybe the most spectacular is the emblematic Go game-playing. In the Machine built by DeepMind, some of the moves that it has made were totally unexpected — not just reproducing the human-based knowledge. It was finding some new moves that no human has ever thought of. So, this artificial stupidity can challenge our intelligence and help us in finding new territories — intellectual territories. It is not that black and white.
01哲学：第二个问题关于“熵”。机器与人类之间存在差异。在人类生命中，总有一些东西不可预测、不确定，甚至是错的，即总有一种不透明性。但是机器可以是透明的：一切都早已包含在机器运作范围之内。考虑到熵，即创生的终结，概率的终结，可能性的终结，会存在一种情况，人工智能将把人类带到一切都早已被人工智能计算殆尽，从而再也没有新的事物的地步？
01 Philosophy: The second question is about entropy. I think there are some differences between machine and human. In human lives, there are something unpredictable, uncertain and even wrong — non-transparency. But in machine, it can be transparent — everything already contained in its operation. To consider the question of entropy, namely, the end of production, the end of probabilities, the end of possibilities, can it be a situation that AI will bring us into a situation that everything have already been calculated by AI - there is nothing new anymore?
赛德里克・维拉尼：首先，我们是基于功能失调与功能相结合的奇特存在，其中一些不运作的东西一直面临著犹如处于演化与改良的游戏的状态。你或许知道，一位美国生物学家史蒂芬・古尔德（Stephen Jay Gould）会称之为熊猫的拇指，显示出熊猫尽管没有拇指，但它需要拿住竹子。从演化上说，为熊猫摘竹子提供的一个人工拇指，就像在某样不完美的事物之上重构、优化某样事物，却保留不完美，并且一直与它共同生活下去。我们一直必须处理这种在我们身上随处可见的不完美。
Cédric Villani: First, we are strange beings based on the combination of dysfunctionality and functionality, in which some not-working things have been faced as if they were in the game of evolution and improvement. You may know this, an American biologist Stephen Jay Gould call it The Panda's Thumb — showing pandas do not have the thumb, but it needs to take the bamboo. Evolutionarily speaking, an artificial thumb for panda's bamboo-picking, it is like reconstructing, perfecting something on top of something imperfect but keep the imperfection and live with it always. We always have to handle with this imperfection that we have everywhere.
点击查看更多维拉尼教授图片：
我曾为两部漫画写作剧本，其中一部是个科幻故事：在某个遥远的未来，人类创造的机器人还在，人类却不在了。机器人要重新发现人类是什么。漫画中的关键字句由我节选自一首法语歌曲：“我们是方程式的一个错误结果”。我对这种包含在我们当中的不完美情有独钟。它是我们自我身份的组成部分。
I wrote scripts for two comics, one of them is a science fiction story, which in a long-distant future, there are robots created by mankind, but mankind is not there. There are robots rediscover what was mankind. The key sentence in the comic which I took from a French song is "we are the result of a wrong equation". I like this imperfection so much in us. It is part of our identity.
现在你或许要问“人工智能将会带来更为完美同时也是令人恐惧的东西吗？”在这一刻，这毋庸置疑是一项理论争辩，因为人工智能在如此实用主义的路径上得到发展。我们也需要如此之多的工作和努力来获取与人工智能的良好合作。我的意思是，人类与机器，事情还会持续误入歧途一段相当长的日子。我们还将持续拥有一个非常不完美的世界，而如今甚至变得更不完美而不是完美一段相当长的日子。
Now we may ask "will the AI bring in more perfection which might be frightening in some way?" For the moment, it really is a theoretical debate, because AI has developed in such a pragmatic way. And it too needs so much work and effort for us to have a good cooperation with the artificial intelligence. I mean, the human and the machine, things will continue to go wrong for a long time. We'll continue to have a world that is very imperfect and currently going rather more imperfectly than perfectly for a long time.
关于熵以及这将把我们引向何方的诠释，非常不清晰。就熵或复杂性而言，将我们的大脑与人工智能作比较吗？我们的大脑描述起来要更为复杂，更为有效率，特别在以下意义上，即我们的大脑于如此紧密的部位耗费如此少的能量，而机器却如此巨大并且耗费巨大能量。我们的大脑就印象和感觉而言更为不完美。我们仅仅探索了可能事物的一小部分，但是直觉却诱导我们认为把握了更高机会去给出解决方案，而机器则是野蛮地探测：它非常暴力。这是完全不同的路径。
In terms of the interpretation about entropy and where will this lead, it is very not clear. Is it comparing our brain to the artificial intelligence, in terms of entropy, in terms of complexity? Ours is much more complicated to describe, much more efficient also in a sense we use so little energy in such a compact place when we have this big machine which use huge energy whatever. Ours is much more imperfect in regard with impression and feeling. We are exploring just a small portion of possible things, but intuition leads us to think there are higher chance to give a solution, whereas machine is brutally exploring: it is very violent. It is a very different kind of approach.
我们人类在更为脆弱、更为有弹性的建构这一边。我们的系统内有更多冗余，而且非常稳固。我们知道，你大脑中有一些枝干可能遭受打击，而我们还可以继续思想。然而计算机倘若有一部分芯片损毁了，它就不能运作，就必须拿些别的芯片来替换。所以在结构上真是大相径庭的。由生命演化出来并在结构上边执行一些结构原本不该执行的运算。我觉得人类智能比人工智能更性感，同时也更为神秘。
We remain on the side that is more fragile, more resilient construction. There is more redundancy in our system, very robust. We know you may have some trunks of your brains hit by stroke or something, and still we can continue to think. While in the computer if there are some parts of chips that are damaged, it just doesn’t work, it needs to just get other ones to replace them. So it is really a different construction: evolved from life and performing some computation on top of construction that is not supposed to do it. I think this is much more fascinating than the artificial intelligence; but also much more mysterious.
技术人文实验室【AI大神说】栏目将第一身与思想大神、技术大神接触，为读者带来大神们对于人工智能和当代技术的新鲜思考与犀利观点。
关于当代技术对人类社会的重塑，我们应如何看待？哲学可以对此给出甚么分析、探索与回应？
01哲学“技术人文实验室”于11月正式成立，作为实验室第一弹专题研习活动，我们即将举办【哲学1001工作坊第七期】，以“机器智能时代的形上学”为主题，欢迎报名参加！
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