Institutional Metaphors for Designing Large-Scale Distributed AI versus AI Techniques for Running Institutions

Alexander Boer; Giovanni Sileno

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arXiv · 1803.03407

Institutional Metaphors for Designing Large-Scale Distributed AI versus AI Techniques for Running Institutions

Alexander Boer·Giovanni Sileno

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Abstract

Artificial Intelligence (AI) started out with an ambition to reproduce the human mind, but, as the sheer scale of that ambition became manifest, it quickly retreated into either studying specialized intelligent behaviours, or proposing over-arching architectural concepts for interfacing specialized intelligent behaviour components, conceived of as agents in a kind of organization. This agent-based modeling paradigm, in turn, proves to have interesting applications in understanding, simulating, and predicting the behaviour of social and legal structures on an aggregate level. For these reasons, this chapter examines a number of relevant cross-cutting concerns, conceptualizations, modeling problems and design challenges in large-scale distributed Artificial Intelligence, as well as in institutional systems, and identifies potential grounds for novel advances.

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Alexander Boer, Giovanni Sileno. 2018-03-09. Institutional Metaphors for Designing Large-Scale Distributed AI versus AI Techniques for Running Institutions. https://arxiv.org/abs/1803.03407

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