The Problem of Meaning in AI and Robotics: Still with Us after All These Years
Philosophies April 3, 2019 Peer reviewed DOI: 10.3390/philosophies4020014 via DOAJ
Summary
Meaning in AI and robotics remains unsolved because deep neural networks and cognitive robotics do not address the problem fundamentally. The enactive approach correctly holds that living beings experience meaning due to their precarious, adaptive autopoietic existence, but it fails to explain how meaning could influence behavior if life and mind are fully deterministic physical phenomena. To resolve this, the concept of nature must be revised to allow physical indeterminacy at the macroscopic scale of living systems, with implications for synthetic approaches to mind and body.
Study at a glance
| Design | theoretical or philosophical paper |
|---|---|
| Key finding | Meaning can play a causal role in behavior only if nature is revised to include physical indeterminacy at the macroscopic scale of living systems. |
Abstract
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.