Some problems in Automatic Natural Language Generation

Alan Turing

ChatGPT and similar tools have more than met the Turing test, for they are capable of fooling many human beings (I don’t know how many, but certainly more than 30%) into believing that there is a mind behind such simple algorithms. But, quoting Evan Ackerman (Senior Editor of IEEE Spectrum):

The problem with the Turing Test is that it’s not really a test of whether an artificial intelligence program is capable of thinking: it’s a test of whether an AI program can fool a human. And humans are really, really dumb.

The limits of mathematics

Kurt Gödel

In the last decades of the nineteenth century, Friedrich Ludwig Gottlob Frege, a professor in the university of Vienna, undertook an ambitious goal: formalizing the arithmetic in a set of axioms and deduction rules, in such a way that every true theorem would be deductible from the axioms by a finite number of applications of the deduction rules. The result was a monumental book, Grundgesetze der Arithmetike (1893-1903), which introduced, among other things, a basic formalization of set theory and a cumbersome notation, quickly replaced by Peano’s, which we are using now.

Unfortunately for Frege, when the second volume of his book was about to be published, he received a letter from Bertrand Russell, proving that his formulation of set theory entails an inconsistency. In Frege’s set theory, some sets are not member of themselves (as the set of all integers, which is not an integer), while other sets are members of themselves (as the set of all infinite sets, which is an infinite set). Russell then defined this set: the set of all sets that are not members of themselves. It is easy to see that this set leads to a paradox: if it is a member of itself, it cannot be a member of itself, and vice versa. Russell’s paradox wreaked havoc with Frege’s work, who had to add a hasty appendix to his book and then abandoned his research on the fundamentals of mathematics.

The three laws of Robotics

Isaac Asimov

Isaac Asimov was a prolific science fiction and popular science writer who published in the 40s a series of stories about robots, later compiled in the I, Robot collection. In these stories he invented a word that has become a part of the technological vocabulary, as the name of a discipline: Robotics. He also formulated the three famous laws of Robotics, which in his opinion should be implemented in every robot to make secure our interactions with these machines that, when Asimov formulated the laws, were simple future forecasts.

The three laws of Robotics are the following:

First Law: A robot may not harm a human being, or through inaction allow a human being to come to harm.

Second Law: A robot must obey any order given by a human being, except those that conflict with the first law.

Third Law: A robot must protect its own existence as long as such protection does not conflict with the first two laws.

The limits of quantum computing

Alan Turing

In an interview in a major Spanish newspaper (La Vanguardia) published on July 27, 2019, David Pérez García, a researcher in quantum physics, says this: We are just in the beginning of some technologies that we still don’t know how far they will go. He is right, because the future is hardly predictable, but when it comes to quantum computing we tend to think that these computers, if they are viable, will let us solve problems quite different from those that can be addressed by the traditional computers to which we are used. In this context, however, mathematics can help us distinguish between what can be done, and what is completely impossible.

Although quantum computing is a fairly modern concept, its theoretical foundation was established by Alan Turing during the 1930s. Let us review a little of what he showed, for in this way we can correct a few optimistic ideas spread by the media, often driven by experts who approach the issue from very different points of view, compared to Turing.

Travelling to the past?

S.Augustin, by Louis Comfort Tiffany
Lightner Museum

In his Confessions (Book XI, chapter 14), St. Augustine wrote these words, still valid today:

What then is time? If no one asks me, I know what it is. If I wish to explain it to him who asks, I do not know.

In the current situation of our scientific and philosophical knowledge, we still don’t know what time is.

·         For classical philosophy and Newton’s science, time is a property of the universe. Therefore, time would be absolute.

·         For Kant, time is an a priori form of human sensibility (i.e. a kind of mental container to which our sensory experiences adapt).

·         For Einstein, time is relative to the state of repose or movement of each physical object. There is, therefore, no absolute time.

·         For the standard cosmological theory, there is the possibility to define an absolute cosmic time for every physical object, measuring the time distance since the Big Bang to the present.

·         For the A theory of time (using J. McTaggart’s terminology) the flow of time is part of reality. The past no longer exists. The future does not yet exist. There is only the present. If the A theory is correct, travel to the past is impossible, because you cannot travel to what does not exist.

·         For the B theory of time, the flow of time is an illusion. Past, present and future exist simultaneously, but for each of us the past is no longer directly accessible, and the future is not yet accessible. Einstein adopted the B philosophy of time. In a condolence letter written to someone who had lost a beloved person, he wrote the following:

The distinction between past, present and future is only a stubbornly persistent illusion.

Fred Saberhagen versus the Turing Test

Alan Turing

In 1950, the English mathematician and chemist Alan Turing tried to define the conditions so that it would be possible to affirm that a machine is capable of thinking like us. For Turing, this will be achieved when the machine is capable of deceiving human beings, making them think that it is one of them. This test is called the imitation game. I have talked about this in a previous post in this blog.

In 1956, Arthur Samuel of IBM built a program to play the game called draughts or checkers. The program kept information about the moves in the games it had played, which was used to modify its future moves (in other words, it learned). In a few years, after playing many games, the program was able to defeat its creator and played reasonably well in official championships.

That same year, during a summer course held in Dartmouth College, John McCarthy and other computer pioneers coined the term artificial intelligence. Getting their hopes too high, they predicted spectacular advances for the next ten years, which did not take place in the time envisaged, but much later. I have also written about this in another post.

In 1963, science fiction writer Fred Saberhagen published the first story of his famous series about the berserkers, autonomous and intelligent space fortresses created by an ancient extraterrestrial civilization to exterminate intelligent life wherever it appears in the galaxy. This story, titled Without a thought, is an answer to the Turing Test and a brake to the unbridled hopes of the inventors of the term artificial intelligence. This is the plot of the story:

The Turing test

Alan Turing

In 1950, in an article published in the Mind magazine, Alan Turing wrote this:

I believe that in about fifty years' time it will be possible to programme computers, with a storage capacity of about 10⁹, to make them play the imitation game so well that an average interrogator will not have more than 70 per cent. chance of mating the right identification after five minutes of questioning.

Why precisely 70 percent? Because studies conducted, where some persons tried to deceive about their sex another person who couldn’t see them, gave that result. In seventy percent of the cases, the persons who had to guess if they were being cheated found the correct answer. In other words, what Turing said was this:

If the machine were able to deceive human beings, posing as human, with the same ease with which a human being can deceive another, it should be considered intelligent.