News on the limits of AI and alternatives

My university published an interview about my views on the limits of AI and what I think are better alternatives for technological development.

Here is a short video clip:

Roundtable talk on the problem of meaning in AI

I was invited to give a presentation on the problem of meaning in artificial intelligence as part of an international roundtable on machine learning, artificial intelligence, and super-computation.

Here is the official poster with the details:

The Problem of Meaning in AI and Robotics: Still with Us after All These Years

Fittingly published in the 10-year anniversary of the publication of “enactive AI“, here is a critical retrospective piece that at the same time marks a significant departure into new, largely unexplored directions. Exciting times!

The Problem of Meaning in AI and Robotics: Still with Us after All These Years

Tom Froese and Shigeru Taguchi

In this essay we critically evaluate the progress that has been made in solving the problem of meaning in artificial intelligence (AI) and robotics. We remain skeptical about solutions based on deep neural networks and cognitive robotics, which in our opinion do not fundamentally address the problem. We agree with the enactive approach to cognitive science that things appear as intrinsically meaningful for living beings because of their precarious existence as adaptive autopoietic individuals. But this approach inherits the problem of failing to account for how meaning as such could make a difference for an agent’s behavior. In a nutshell, if life and mind are identified with physically deterministic phenomena, then there is no conceptual room for meaning to play a role in its own right. We argue that this impotence of meaning can be addressed by revising the concept of nature such that the macroscopic scale of the living can be characterized by physical indeterminacy. We consider the implications of this revision of the mind-body relationship for synthetic approaches.