{"id":3170,"date":"2024-06-26T18:32:21","date_gmt":"2024-06-26T16:32:21","guid":{"rendered":"https:\/\/www.rivistaeco.com\/?p=3170"},"modified":"2024-06-26T18:32:21","modified_gmt":"2024-06-26T16:32:21","slug":"can-artificial-intelligence-lie-to-us-interview-with-tomaso-poggio","status":"publish","type":"post","link":"https:\/\/www.rivistaeco.com\/en\/2024\/06\/26\/can-artificial-intelligence-lie-to-us-interview-with-tomaso-poggio\/","title":{"rendered":"Can Artificial Intelligence Lie to Us? Interview with Tomaso Poggio"},"content":{"rendered":"

Tomaso Poggio is one of the founders of computational neuroscience and a prominent figure in the field of artificial intelligence. He is a professor at the Massachusetts Institute of Technology (MIT) and the director of the Center for Brains, Minds, and Machines (CBMM), an interdisciplinary centre that explores the scientific foundations of intelligence.<\/span><\/p>\n

Artificial intelligence (AI) is one of the technological innovations that has rapidly transitioned from researchers’ hands to those of end users. Although the audience for software like ChatGPT is already broad, we often struggle to understand what AI actually is and what it is capable of doing. After fifty years during which computer science meant programming computers, i.e., giving them instructions, the last twenty years have seen a radical shift: machines have started learning from examples and have long been able to beat the best human chess players. Progress is also tangible in more practical applications, such as autonomous driving, albeit with some limitations. Overlaying all this is the significant issue of regulation, such as privacy concerns amid growing public apprehensions, as well as the question of algorithm transparency. Finally, many questions remain open about the limitations of these machines. Are they conscious? Can they deceive us? These questions provoke broader reflections encompassing human knowledge and intelligence in a vast discourse intertwining philosophy, computational neuroscience, and computer science. Tomaso Poggio’s interdisciplinary research spans from the human brain to computers and is driven by the idea that understanding learning dynamics is essential for comprehending both biological and artificial intelligence. AI is already transforming our world in ways that seemed like science fiction just a few years ago. Exploring the challenges and future opportunities of artificial intelligence with one of the foremost experts in the field offers a stimulating and unique vision of the present and future of this technology.<\/span><\/i><\/p>\n

Professor Poggio, today AI is being discussed everywhere, sometimes even inappropriately. As one of the fathers of AI, could you explain what it is?<\/b>\u00a0<\/span><\/p>\n

Artificial intelligence falls into what Marvin Minsky called \u201csuitcase words\u201d – terms that don’t have a clear meaning in themselves but contain many different meanings. I would define artificial intelligence as the attempt to reproduce human intelligence in machines. In recent years, AI has materialised in machine learning, which is the attempt to teach machines to learn.<\/span><\/p>\n

AI is a true scientific revolution. Was there a particular moment when you realised a new science was being born?<\/b>\u00a0<\/span><\/p>\n

In the first fifty years of computer history, computer science was about programming them. In the 2000s, there was a paradigm shift, a real scientific revolution: from programming machines, we moved to teaching machines that learn from examples (the so-called deep learning).<\/span><\/p>\n

When did machines start competing with humans?<\/b>\u00a0<\/span><\/p>\n

Let me give you an example. DeepMind, a company founded in 2011 by a researcher I collaborated with, was created with the idea of building an AI system, based on learning, that could play any game. In 2015, they developed a system called AlphaGo that beat the unofficial world champion of Go in South Korea, a game much more complex than chess with a long tradition in Asia. During one of these games, AlphaGo made an incredible move, one of the so-called \u201cGod’s moves,\u201d so surprising and creative that it was studied for years. This was a great success because AlphaGo could learn to play chess, Go, and other games autonomously, simply by playing against itself. In six hours, it could become better than the world chess champion, and in twenty-four hours, it could become better than the Go champion. All this shows that in the virtual world of games, AI is already superior to human intelligence.<\/span><\/p>\n

Today AIs can solve real problems. How did this leap occur?<\/b>\u00a0<\/span><\/p>\n

One of the main challenges is undoubtedly applying AI in the real world. Mobileye, founded by my former collaborator Amnon Shashua, is the company that provided the first automatic driving systems for Tesla. Recently, they had to stop supplying because Elon Musk did not adequately explain the limitations of these machines to his customers, leading to a fatal accident in Texas. Beyond the challenge of creating systems safe enough for real-world applications, these machines must be taught to handle out-of-the-ordinary situations. Mobileye developed a system that works very well even in the chaotic traffic of Jerusalem. However, these systems depend on precise maps and may not work in unmapped areas. Moreover, they might not be able to handle specific situations like accidents or orders from authorities.<\/span><\/p>\n

You work in the United States. Do you think there is a gap in AI research and development between Europe and the US?<\/b>\u00a0<\/span><\/p>\n

Yes, there is. Currently, the two superpowers in AI are the United States and China. The know-how exists in other parts of the world, such as Italy and Europe, and the quality of university education is comparable to that in the US. The problem is that Europe lacks companies with sufficient resources and personnel to have a real impact. For example, DeepMind, the company I mentioned earlier, was founded over ten years ago in London. Recently, it was acquired by Google, and now 1000 people work in London, while between San Francisco and Mountain View, there are 2500.<\/span><\/p>\n

How should European companies change to close the gap?<\/b>\u00a0<\/span><\/p>\n

To have a significant impact in AI, a concentration of resources is necessary. A single brilliant researcher is not enough. Interesting ideas can still come from individual researchers, but to develop products, companies with large human and computational resources and significant financial investments are needed. The funds raised by startups like OpenAI are impressive. We’re talking about hundreds of billions of dollars. In Europe, there are some initiatives and promising startups, particularly in France, but Italy is lagging. I know that some funds allocated for AI in Italy have been dispersed across too many projects, and this is a mistake because resources need to be concentrated to have a significant impact.<\/span><\/p>\n

Another relevant aspect that seems to worry the public is the risks of AI. Among these is the creation of false but extremely realistic content, the so-called \u201cdeep fakes.\u201d How can we reduce the risk of disinformation?<\/b>\u00a0<\/span><\/p>\n

Certainly, there are evident risks. It’s not just a problem of deep fakes but also intellectual property, as the origin of any disseminated content should always be explicitly declared. From a practical standpoint, the difficulty with AI is greater as it is accessible to everyone, unlike technologies such as nuclear energy and atomic bombs, which are costly and require extensive infrastructure. We can prohibit certain practices in Europe, but they may still be adopted in Korea, China, or Africa. The genie is out of the bottle and cannot be stopped. Therefore, we must not forget that risks exist, but there are also great potential benefits, and the political challenge is perhaps more complex than the technological and scientific problems.<\/span><\/p>\n

Another concern is user privacy. Large language models like the one behind ChatGPT are trained using vast amounts of data. How can we ensure that users’ personal data remains private?<\/b>\u00a0<\/span><\/p>\n

I agree with the attention the European Union pays to privacy. This is a real danger not just with AI and models like ChatGPT but with all large companies like Google that collect enormous amounts of information about each of us without ever truly asking for our consent in an appropriate manner. We should have the right to privacy and our data, a right that will become increasingly important in the future. One of the European Community’s demands is that if a person believes their data has been used without consent and wants it removed, it should be possible to delete it. For current training systems like those used for GPT, this is a significant problem because it’s not possible to remove data without restarting the entire training process, which takes months. However, new technological solutions might emerge in the future, representing substantial progress in respecting user rights.<\/span><\/p>\n

There is also the problem of the lack of transparency in algorithms, which would make it difficult to identify and correct erroneous or unethical results. Do you think current standards are sufficient?<\/b>\u00a0<\/span><\/p>\n

It’s essential to improve them. The lack of transparency in algorithms is a significant problem for AI and many other advanced technologies. Publishing algorithms would be important not only in regards to transparency for users but also to advance research. Unlike earlier phases, very few companies currently publish their algorithms. OpenAI, despite its name \u201copen,\u201d is not one of them.<\/span><\/p>\n

In machine learning systems, the output is generated automatically from the machine’s training on large datasets. Do you see any possibility of consciousness in this process?<\/b>\u00a0<\/span><\/p>\n

This is a relevant topic. First, it’s unclear what we mean by consciousness. One form of consciousness is self-awareness, the awareness that a subject has of itself. For example, a being is considered self-aware when it can recognise itself in a mirror (mirror test). Few animal species pass this test. Would ChatGPT pass it? I asked it, and it claimed it could, but only because it knows what it is. It would be interesting to remove any reference to the mirror test from ChatGPT’s dataset to see if it would actually pass the test.<\/span><\/p>\n

Are there other ways to test ChatGPT’s consciousness?<\/b>\u00a0<\/span><\/p>\n

I wondered, for example, if ChatGPT lies. ChatGPT can \u201cdeceive\u201d us if we explicitly ask it to pretend to be a specific person. But if it lied to us or hid answers intentionally, a bit like in the movie Ex Machina (which I recommend), then it would indeed be conscious, and we currently don’t have a way to discover it.<\/span><\/p>\n

AI was born from the study of human intelligence. The similarity between human and artificial neural networks is the most intuitive example. Do you think further progress requires more borrowing from biology, or does evolution rely on something else?<\/b>\u00a0<\/span><\/p>\n

Until ten years ago, I was convinced that discoveries about machines would come from advances in studying the human mind. Neuroscience guided the first steps in creating intelligent machines. For instance, neural networks and algorithms like deep learning originate from neuroscience. In the last seven years, however, progress in AI has occurred without drawing from neuroscience, because engineering has enhanced existing algorithms without being inspired by the human brain. I’m referring to large language models, for example, which led to the development of ChatGPT. I don’t rule out that in the coming years we might need to return to neuroscience for inspiration.<\/span><\/p>\n

Is the opposite possible? Can discoveries about the human mind derive from studying machine intelligence? Has it ever happened?<\/b>\u00a0<\/span><\/p>\n

For the first time we have intelligences at our level. This means we can now conduct comparative studies between human intelligence and new intelligences. Think of DNA, the universal genetic basis of almost all known life forms. Similarly, if we discover some common principles among different forms of intelligence, then yes, we could make discoveries about the human mind by studying artificial intelligence.<\/span><\/p>\n

We know humans have cognitive biases in reasoning. Do you think AI, as it is trained, has inherited these human flaws?<\/b>\u00a0<\/span><\/p>\n

Certainly, machines have inherited human biases because they are trained with the products of the human mind. It’s hard to say if AI has a limit imposed by what the human mind has known or if it will be capable of originality in mathematics and generating new conjectures.<\/span><\/p>\n

Can we expect this to happen in the coming years?<\/b>\u00a0<\/span><\/p>\n

Yes, I expect we will have a conscious machine in the future. A few years ago, I believed it would take at least fifty years. Now I think it could happen even tomorrow.<\/span><\/p>\n

What will be the impact on society?<\/b>\u00a0<\/span><\/p>\n

Two centuries ago, Alessandro Volta invented the battery, which for the first time provided a continuous source of electricity; from then on, many applications followed rapidly. The paradigm shift from programming computers to teaching them has undoubtedly paved the way for a series of innovations that we must expect to come at a very fast pace. One of the great dangers is that this time the change will happen too quickly. It takes time for society to adapt. When we transitioned from horses to trains, many people working with carriages lost their jobs, but it didn’t happen all at once. There was an adaptation period which seems to be being lost today. What do I think the impact on society will be? I can’t say if the stock market is too optimistic, but AI will undoubtedly lead to an industrial revolution. It’s essential for society to keep up and adapt to reap all the benefits this new science has to offer us.<\/span><\/p>\n

Bio<\/span><\/em><\/p>\n

Martina Barni is a student of economics and social sciences at Bocconi University and a member of the student association Economic Society for Bocconi Students.<\/span><\/em><\/p>\n

Federico Casotto is a student of economics and finance at Bocconi University and a member of the student association Economic Society for Bocconi Students.<\/span><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

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