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“Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty Through Sociotechnical Commitments” Accepted by AIES
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“Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty Through Sociotechnical Commitments” Accepted by AIES

The AAAI/ACM Conference on AI, Ethics, and Society (AIES) 2020 accepted a paper, “Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty through Sociotechnical Commitments,” coauthored by CHAI machine ethics researcher Thomas Gilbert.

International Conference on Learning Representations Accepts “Adversarial Policies: Attacking Deep Reinforcement Learning”
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International Conference on Learning Representations Accepts “Adversarial Policies: Attacking Deep Reinforcement Learning”

Adam Gleave, Michael Dennis, Neel Kant, Cody Wild, Sergey Levine, and Stuart Russell had a new paper, “Adversarial Policies: Attacking Deep Reinforcement Learning”, accepted by the International Conference on Learning Representations (ICLR).

NeurIPS 2019 Accepts CHAI Researchers’ Paper “On the Utility of Learning about Humans for Human-AI Coordination”
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NeurIPS 2019 Accepts CHAI Researchers’ Paper “On the Utility of Learning about Humans for Human-AI Coordination”

The paper authored by Micah Carroll, Rohin Shah, Tom Griffiths, Pieter Abbeel, and Anca Dragan, along with two other researchers not affiliated with CHAI, was accepted to NeurIPS 2019. An ArXiv link for the paper will be available shortly.

Siddharth Srivastava Awarded NSF Grant on AI and the Future of Work
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Siddharth Srivastava Awarded NSF Grant on AI and the Future of Work

Siddharth Srivastava, along with other faculty from Arizona State University, was awarded a grant as a part of the NSF’s Convergence Accelerator program. The project focuses on safe, adaptive AI systems/robots that enable workers to learn how to use them on the fly. The central question behind their research is: How can we train people to use adaptive AI systems, whose behavior and functionality is expected to change from day to day? Their approach uses self-explaining AI to enable on-the-fly training. You can read more about the project here.

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Rohin Shah Publishes “Clarifying Some Key Hypotheses in AI Alignment” on the Alignment Forum

CHAI PhD student Rohin Shah, along with Ben Cottier, pubished the blog post “Clarifying Some Key Hypotheses in AI Alignment” on the AI Alignment Forum. The post maps out different key and controversial hypotheses of the AI Alignemnt problem and how they relate to each other.