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The Ethics of Analog AI

MCML Authors

Gitta Kutyniok

Prof. Dr.

Principal Investigator

Mathematical Foundations of Artificial Intelligence

Sven Nyholm

Prof. Dr.

Principal Investigator

Ethics of Artificial Intelligence

Abstract

AI ethics has matured as a field, yet its concepts and tools have been developed almost entirely with digital AI in mind. Emerging “analog” AI approaches, that is, systems that compute over continuous, rather than binary, signals, challenge this digital default. Analog AI promises substantial energy savings and alternative modes of information processing. However, it also departs in ethically significant ways from the widely discussed digital AI systems such that its differences from digital AI could mean that current ethical frameworks may not address analog AI’s unique challenges. This paper highlights how the distinctive characteristics of analog AI raise new ethical questions that require careful consideration. We examine four key areas of AI ethics, namely fairness, privacy, explainability, and safety, and propose a roadmap for the ethical examination of analog AI. Our aim is to lay the foundation for an important but hitherto unrecognized subfield within AI ethics: the ethics of analog AI.

article KBK+25