As-If Agents: Misrecognition and the Ethics of Non-Agentive AI
TL;DR
An ethics of non-agentive AI is sketched: the authors should see these systems as powerful, instrument-like extensions of human cognition, not as knowers in their own right, and design institutions, interfaces and norms of trust accordingly.
Abstract
What if the most influential voices in our epistemic lives are not agents at all, but machines we keep mistaking for them? I argue that contemporary AI systems function more and more like epistemic authorities while lacking the psychological resources that underpin human epistemic agency. Building on work on artificial epistemic authority and algorithmic truth, I show how search engines, recommendation systems and large language models are already treated as sources of knowledge in medicine, education and everyday deliberation. I then turn to the distinction between episodic and semantic memory in human cognition and argue that current AI only has the latter in a thin, decontextualized form. It has no episodic memory, no autobiographical perspective and no capacity to remember past episodes as ‘things that happened to me.’ This, I claim, makes our growing tendency to relate to AI as if it were a responsible testifier a form of misrecognition. I conclude by sketching an ethics of non-agentive AI: we should see these systems as powerful, instrument-like extensions of human cognition, not as knowers in their own right, and design institutions, interfaces and norms of trust accordingly.