2. Philosophy - Stefano Franchi

B ETWEEN ENGINEERING, SCIENCE, AND PHILOSOPHY.
what it means to speak and play chess. What in essence, speaking a language or playing
chess is all about (and, therefore, what it should be when properly performed); in other
words, are we learning what these activities consist in, regardless of whether human per-
formance is always, as a matter of fact, concretely up to the task.
Different answers to this questions have a profoundly different effect, as it should be
apparent, on the status of Artificial Intelligence. The first kind of answer puts AI in the field
of engineering, the second pulls it toward psychology, the third one drives it more and more
in the philosophical field. Moreover, the three questions are not mutually exclusive: after
all, you might have a learning experience in a car dealership as well, if you decide to speak
with the head mechanic instead of the sales manager. Arguably, all eight possible combina-
tions can be (and, presumably, have been) defended on AI’s behalf, although with different
intensity.
More generally, I think these three possible answers can be assumed to constitute the
three poles around which both the self-understanding of Artificial Intelligence and its con-
sideration from the standpoint of outside observers is organized. I will now go through the
three different perspective, one at a time, and will focus on the reasons that speak against
a positioning of AI in that field.
The first reason why the engineering side can be is because of the actual lack of results
when the output of AI research is judged according to industrial standards. In spite of all
the promises that have come out of the field, there is quite a dearth of reliable, industrial
strength AI products on the marketplace. In fact, I think it would be fairly safe to assert that
if we leave aside the tools that people use to write AI programs, the industrial relevance of
AI products is so negligible to be non existent. Moreover, this judgment is now shared by
many workers in the field.
However, this objection to the engineering viability of AI, although quite powerful
from the practical point of view, can be quite easily disposed of in the theoretical realm.
After all, it might be claimed that it is impossible to predict how long it will take to develop
the insights and intuitions that are required to reach the industrial goals.
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