Unifying Principles and Metrics for Safe and Assistive AI

Authors

  • Siddharth Srivastava Arizona State University

Keywords:

AI Safety, AI And The Future Of Work, Taskable AI Systems, Usability Of AI Systems, Metrics For Safe And Beneficial AI Systems

Abstract

The prevalence and success of AI applications have been tempered by concerns about the controllability of AI systems about AI's impact on the future of work. These concerns reflect two aspects of a central question: how would humans work with AI systems? While research on AI safety focuses on designing AI systems that allow humans to safely instruct and control AI systems, research on AI and the future of work focuses on the impact of AI on humans who may be unable to do so. This Blue Sky Ideas paper proposes a unifying set of declarative principles that enable a more uniform evaluation of arbitrary AI systems along multiple dimensions of the extent to which they are suitable for use by specific classes of human operators. It leverages recent AI research and the unique strengths of the field to develop human-centric principles for AI systems that address the concerns noted above.

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Published

2021-05-18

How to Cite

Srivastava, S. (2021). Unifying Principles and Metrics for Safe and Assistive AI. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 15064-15068. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17769

Issue

Section

Senior Member Presentation: Blue Sky Papers