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- Title
Society-in-the-loop: programming the algorithmic social contract.
- Authors
Rahwan, Iyad
- Abstract
Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an <italic>algorithmic social contract</italic>, a pact between various human stakeholders, mediated by machines. To achieve this, we can adapt the concept of <italic>human-in-the-loop</italic> (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call <italic>society-in-the-loop</italic> (SITL), which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, ‘<italic>SITL</italic> = <italic>HITL</italic> + <italic>Social Contract</italic>.’
- Subjects
ARTIFICIAL intelligence; MACHINE learning; ARTIFICIAL neural networks; HUMAN-computer interaction; ELECTRONIC data processing
- Publication
Ethics & Information Technology, 2018, Vol 20, Issue 1, p5
- ISSN
1388-1957
- Publication type
Article
- DOI
10.1007/s10676-017-9430-8