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虽然梅拉妮·米歇尔强烈支持人工智能的研究，但也表达了对人工智能容易受到黑客攻击且一直受到来自社会的偏见的担忧。关于一般的人工智能，梅勒妮·米歇尔指出，”具备常识性知识”和”能够模仿人抽象和类比的能力”可能是构建超级人工智能所需的最后一步，但目前的技术还不能解决这个问题。[4]梅拉妮·米歇尔认为，像人类一样的视觉智能需要“一般知识、抽象概念和语言”，并假设视觉理解需要作为一种具体化的媒介进行学习，而不仅仅是观看图片。
虽然梅拉妮·米歇尔强烈支持人工智能的研究，但也表达了对人工智能容易受到黑客攻击且一直受到来自社会的偏见的担忧。关于一般的人工智能，梅勒妮·米歇尔指出，”具备常识性知识”和”能够模仿人抽象和类比的能力”可能是构建超级人工智能所需的最后一步，但目前的技术还不能解决这个问题。[4]梅拉妮·米歇尔认为，像人类一样的视觉智能需要“一般知识、抽象概念和语言”，并假设视觉理解需要作为一种具体化的媒介进行学习，而不仅仅是观看图片。
梅拉妮·米歇尔认为人们现在有理由为人工智能能够达到的智力程度感到不安。她认为人类最看重自己之所以成为人的原因是创造力，因为人类可以创造音乐和文学等，因此当人工智能写出或有可能会写出优秀的音乐、诗歌作品时，人们就会对它未来的发展潜力感到害怕。现在，不管是根据IBM的深蓝系统展现出超人的弈棋水平等现实材料，还是根据学者对人工智能未来的预测（Kurzweil到2045年，将会出现比人类聪明十亿倍的智能），超级人工智能的出现似乎已经成为必然。
梅勒妮·米歇尔认为有必要首先区分知识和智慧。诸如“埃菲尔铁塔有多高”是确切可以掌握的知识而“提高最低工资是否能改善贫困”则不是一个可以简单得到的知识。当人们谈到人工智能会给人带来“幸福”或“不幸”时，也会遇到每个人所定义的“幸福”或“不幸”究竟有什么内涵，是否可以用一组确切的知识来衡量的问题。而机器只能处理知识却很难掌握智慧，它们对人类世界的了解很有限，因此无法对人类可以简单地推测到的行为做出正确判断，因此它们也就不能掌握“幸福”和“不幸”这些概念的奥义。他们也许可以识别物体，但是不能将各个碎片拼接和联系起来，因此他们无法理解诸如“情感”这些层面的事情，也就无法带给人们“幸福”或“不幸”。她认为，在当前的计算机视觉中，输入数据的质量会很大程度影响机器学习的效果，机器没办法自己指导自己学习；诚然人类也会机械地对事物进行联系，形成个人的记忆和理解外界的体系，但是如米奇·卡普尔Mitch Kapor所言，除非人工智能经历了人类大脑经历的生活体验并将其分类，否则它们永远不会是“智能”的。
“So, in AI, people talk about this notion of distribution, which is kind of a statistics idea that your data has a certain distribution. The dogs in your training data have a certain range of features that your system learns and if you show it a new thing that is within that range of features then it can recognize it, but if it's outside of that distribution, it won't be able to transfer its knowledge to that. And that's something that we humans are able to do. One of the things that kind of surprised me: there's a huge focus in AI on this thing called 'transfer learning,' which is exactly what we're talking about. That is: learn one thing, learn to play chess, be able to transfer your knowledge to variations of chess or to checkers.”
人类可以“迁移学习”（transfer learning），比如辨认出动画片中的狗，但是如果机器的训练集当中没有动画片中的狗，它就不能很好地对这个图做出分类。机器无法把知识迁移到自己从未见过的范围内。
“'Intelligence' is one of those words that means different things in different contexts. （It means different things to different people. Here we are sitting in Washington, DC, and I think a lot of the country, a lot of people in the country think, 'Oh, Congress--there there's no intelligence there.' But, when I go around giving talks about AI and I say, 'Well, computers aren't very intelligent yet,' people tell me, 'Well, human beings aren't very intelligent, either.' But they're using the term just very differently. Intelligence isn't just one thing. ）It's not a yes or no thing either. And I think one of the problems is we don't have a good sense of what intelligence is. We don't understand our own intelligence very well. Our state of understanding the brain is still quite limited. Our understanding of human psychology is still rather limited. And I think intelligence is the one of those terms that's a placeholder for things we don't understand yet. It's kind of a phenomenon that we kind of have a general idea of what it is but we don't know specifically, and it's just waiting for more scientific advances to replace it with something more useful.”
“智慧”根据语境会有不同的含义。我们不太了解自己的智慧，对智慧是什么，大脑的工作方式是怎样的没有很好的认识。智慧是对我们还不理解的东西的一个指称，是一种现象。我们对它有一个大致的概念，但我们不知道具体是什么，它只是等待更多的科学进步，以更有用的东西来取代它。”
==代表作品==
==代表作品==