Criticizing Ethics According to Artificial Intelligence

TL;DR

The paper critiques conventional AI ethics by arguing that core concepts such as autonomy, morality, and ethics are increasingly inadequate for autonomous AI and require redefinition. It proposes a deep critique framework built on clarifying conceptual ambiguities, examining epistemic issues, and exploring fundamental normative problems to guide future normative theory. It analyzes contested notions of intelligence, agency, and autonomy and discusses epistemic challenges around explainability and the shift toward data-centric knowledge. It questions both overhyped and underappreciated AI risks and critiques attempts at normative programming, such as ethical governors and data-driven moral judgments like the Moral Machine. It concludes that a coherent AI ethics will need a new science of normativity that can reconcile conflicting theories and support ethical guidance in AI systems.

Abstract

This article presents a critique of ethics in the context of artificial intelligence (AI). It argues for the need to question established patterns of thought and traditional authorities, including core concepts such as autonomy, morality, and ethics. These concepts are increasingly inadequate to deal with the complexities introduced by emerging AI and autonomous agents. This critique has several key components: clarifying conceptual ambiguities, honestly addressing epistemic issues, and thoroughly exploring fundamental normative problems. The ultimate goal is to reevaluate and possibly redefine some traditional ethical concepts to better address the challenges posed by AI.