AINCMay 18, 2023

A method for the ethical analysis of brain-inspired AI

arXiv:2305.10938v18 citations
Originality Synthesis-oriented
AI Analysis

This work addresses ethical implications for researchers and developers in AI, but it is incremental as it builds on existing ethical frameworks without introducing a novel paradigm.

The paper tackles the ethical challenges of brain-inspired AI by introducing a heuristic method to identify and address these issues, concluding that it raises new foundational and practical ethical concerns and exacerbates some existing ones compared to traditional AI.

Despite its successes, to date Artificial Intelligence (AI) is still characterized by a number of shortcomings with regards to different application domains and goals. These limitations are arguably both conceptual (e.g., related to underlying theoretical models, such as symbolic vs. connectionist), and operational (e.g., related to robustness and ability to generalize). Biologically inspired AI, and more specifically brain-inspired AI, promises to provide further biological aspects beyond those that are already traditionally included in AI, making it possible to assess and possibly overcome some of its present shortcomings. This article examines some conceptual, technical, and ethical issues raised by the development and use of brain-inspired AI. Against this background, the paper asks whether there is anything ethically unique about brain-inspired AI. The aim of the paper is to introduce a method that has a heuristic nature and that can be applied to identify and address the ethical issues arising from brain-inspired AI. The conclusion resulting from the application of this method is that, compared to traditional AI, brain-inspired AI raises new foundational ethical issues and some new practical ethical issues, and exacerbates some of the issues raised by traditional AI.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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