Sometimes, we see predictions on an idyllic future of AI or, more often, on the catastrophes that it will cause. We love to scare ourselves, in that way we are sure to make newspaper headlines. However, given the vagueness of these predictions, it is impossible to see whether we could overcome these potential difficulties. Some even want to stop AI research; this is due to a distrust of science, and will leads to the catastrophe that they want to avoid. Indeed, to run efficiently a country or a large company is a daunting challenge; I believe that it exceeds the capacity of human intelligence. Refusing AI’s help will more surely lead to a catastrophe. In particular, some are worried that the robots would take power, and will enslave us. They believe that all intelligence must be similar to the human one; therefore, robots will be aggressive and overbearing, as ourselves. In fact, we have these characteristics because our intelligence is a product of evolution in a resource-constrained environment. However, Darwinian evolution is not the only path for creating intelligent beings; I even think that it is not the right direction in AI research: it requires too much time and too many individuals.

It is unrealistic to predict how AI will turn out for the long term. To be convinced, it is enough to look at what recently happened in Computer Science. Sixty years ago, who saw what it is now? I took my first steps in this domain in 1958, and almost all those who were in this area thought it would be useful for scientific computing and business management; nevertheless, in those days, no one was thinking about the Internet and the Web. Moreover, we did not think that the cost of computer time would decrease so fast. Only one hour of computing on the fastest machines was very expensive, it far exceeded a one-month salary. Their power seemed amazing: almost one Million Instructions Per Second for the IBM 704, the workhorse of many of the first AI realizations! We did not think that their power would incredibly increase, while their cost would incredibly decrease: c.1965, someone suggested (and I am not sure that he believed it) that, in the future, the computer plant visitors would receive the CPU as a key fob. We all laughed at this joke, how could such a precious component could become so cheap? Changing drastically the cost of computing has made it possible to realize applications that were unthinkable. This is the main reason in the mistakes that I had made in 1962, when I had written a paper describing the state of AI. Naturally, there was a section on its future; among my predictions, some were true, and some false. The main reason of my mistakes: I had not seen that the computer cost would go down so much, and that the computer power would go up so much.

However, it is possible to predict some specific achievements: for instance, there will be self-driving cars: this is the normal course of events for a research well under way. It is reasonable to think that with AI improvements, some professions will disappear, such as it already happened with computers. Unfortunately, many changes are impossible to foresee: they will depend not only on new research directions for AI, but also on progress in other domains, particularly with computers.

I strongly believe that all human activities, without any exception, could be undertaken by AI systems, and they would be much better than us. However, I do not predict that this will happen, even in the far future: human intelligence is perhaps not enough to reach his goal. Creating systems that create systems is an extremely difficult area, and evolution did not optimize our capabilities in this field.

Moreover, the research structure does not encourage what needs to be done. Many researchers do an excellent thesis but if they want to pursue a career, they must quit the kind of research that is interesting to the future of AI. New ideas come naturally when one develops a large system with a computer; to do that, for many years one must spend at least half of his time on it. This is impossible if one also has important responsibilities as a teacher and as a manager. Besides, the weight given to publications is not a favorable element in AI research: how can we describe a system that uses much more than 10,000 rules? It is almost impossible to do for a system with many meta-rules that create new rules. It is much easier to write a theoretical paper, which will be understood easily. It is no coincidence that several teams that recently achieved spectacular results were not from the university, but from the industry. However, the industry’s goal is not to develop research for the very long term: profitability is important for any business. I believe about the importance of bootstrapping AI, although this will take a lot of time and the results will be poor for long enough. This encourages neither the university, nor the industry to engage in this way.

I do not want to give precise predictions for the long term, mission impossible. Nevertheless, I am sure that if we succeed to bootstrap AI, the consequences will be immeasurable: intelligence is essential to the development of our civilization. However, we cannot conceive what could be a super-intelligence, in the same way that a dog cannot conceive what is our intelligence. And, finally, it is very possible that this goal will never be achieved because human intelligence is too limited for such a huge task; even so, it is worth a try.