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arXiv · 2204.07612

Contextualizing Artificially Intelligent Morality: A Meta-Ethnography of Top-Down, Bottom-Up, and Hybrid Models for Theoretical and Applied Ethics in Artificial Intelligence

Jennafer S. Roberts·Laura N. Montoya
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Abstract

In this meta-ethnography, we explore three different angles of ethical artificial intelligence (AI) design implementation including the philosophical ethical viewpoint, the technical perspective, and framing through a political lens. Our qualitative research includes a literature review that highlights the cross-referencing of these angles by discussing the value and drawbacks of contrastive top-down, bottom-up, and hybrid approaches previously published. The novel contribution to this framework is the political angle, which constitutes ethics in AI either being determined by corporations and governments and imposed through policies or law (coming from the top), or ethics being called for by the people (coming from the bottom), as well as top-down, bottom-up, and hybrid technicalities of how AI is developed within a moral construct and in consideration of its users, with expected and unexpected consequences and long-term impact in the world. There is a focus on reinforcement learning as an example of a bottom-up applied technical approach and AI ethics principles as a practical top-down approach. This investigation includes real-world case studies to impart a global perspective, as well as philosophical debate on the ethics of AI and theoretical future thought experimentation based on historical facts, current world circumstances, and possible ensuing realities.

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BibTeXRIS

Jennafer S. Roberts, Laura N. Montoya. 2022-04-15. Contextualizing Artificially Intelligent Morality: A Meta-Ethnography of Top-Down, Bottom-Up, and Hybrid Models for Theoretical and Applied Ethics in Artificial Intelligence. https://arxiv.org/abs/2204.07612

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