MYTHS AND REALITY OF ARTIFICIAL INTELLIGENCE

The “Università degli Studi Milano Bicocca”, in collaboration with “The Innovation Group” organises on March 2 from 9am to 1pm, 2018 in Aula Martini, Building U6 at the “Università degli Studi Milano Bicocca, a:

SEMINAR:

“MYTHS AND REALITY OF ARTIFICIAL INTELLIGENCE”

Theoretical issues and practical developments

THE THEME OF THE SEMINAR:

Which are the theoretical, philosophical foundations of what we call “Artificial Intelligence? And which are its main social and ethical implications, challenges and concerns?”

According to Luciano Floridi (“The Fourth revolution”) two souls of A.I. are facing each other: the engineering and the cognitive one. This brings us back to John Searles “Chinese room” argument, or, in other terms, to the famous “Turing test”.

Are we really facing a “weak” and a “strong “A.I.”? And do we agree that what we see as major achievements of A.I. are simply the results of powerful syntactic engines, capable of manipulating enormous arrays of data, but structurally unable to achieve the semantic level, where you have to manipulate not simple data, but information – data with a meaning?

As Floridi says: “The snag is semantics. How do data acquire their meaning? This is known in A.I as the “Symbol grounding process”.

Somebody, as Eric Schmidt, believes that we are fast approaching this level. Floridi on the opposite thinks that we are very far from it and that, while the engineering souls of A.I. has achieved excellent results, the cognitive approach didn’t go very far at all.

And while, according to a purely “syntactic” approach, the statement of Chris Anderson, «The end of theory: The data deluge makes the scientific method obsolete» (2008) makes perfect sense, this statement on the opposite, according to a semantic perspective, could become very questionable.

All this has to do with a major debate related to the philosophical and the knowledge theory; but relevant issues are even being raised as far as the ethical implications of A.I. are concerned, for instance as far as the relationship between predictivity and anticipation is concerned.

And all these theoretical issues entail major practical implications: is it legitimate talking about “intelligent” refrigerators, laundry machines, or even “intelligent” smartphones with a neural processor, or was it right E. W. Dijkstra when saying that “The question of whether a computer can think is no more interesting than the question of whether a submarine can swim”?

On the other hand, there are schools of thought that on the opposite theorize that in a few decades the intelligence of the machine will surpass the combined brain power of all human beings combined.

Consequent practical perspectives are, of course, very different. But we should not proceed with engineering new architectures, devices, and tons of gadgets, without discussing in depth the underlying theoretical issues.

This is the reason why we believe that this opportunity of sharing and discussing different views will be welcome by all, philosophers, academics, practitioners, and industry leaders.

SEMINAR: