Society-in-the-loop: programming the algorithmic social contract
Author(s)
Rahwan, Iyad
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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 algorithmic social contract, a pact between various human stakeholders, mediated by machines. To achieve this, we can adapt the concept of human-in-the-loop (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop (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, ‘SITL = HITL + Social Contract.’ Keywords: Ethics, Artificial intelligence, Society, Governance, Regulation
Date issued
2017-08Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society; Massachusetts Institute of Technology. Media Laboratory; Program in Media Arts and Sciences (Massachusetts Institute of Technology)Journal
Ethics and Information Technology
Publisher
Springer Netherlands
Citation
Rahwan, Iyad. “Society-in-the-Loop: Programming the Algorithmic Social Contract.” Ethics and Information Technology 20, no. 1 (August 17, 2017): 5–14.
Version: Author's final manuscript
ISSN
1388-1957
1572-8439