Julia Haas

ORCID: 0000-0003-2330-1132
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About
Contact & Profiles
Research Areas
  • Psychology of Moral and Emotional Judgment
  • Neural and Behavioral Psychology Studies
  • Embodied and Extended Cognition
  • Evolutionary Game Theory and Cooperation
  • Cultural Differences and Values
  • Emotions and Moral Behavior
  • Child and Animal Learning Development
  • Hate Speech and Cyberbullying Detection
  • Ethics in Business and Education
  • Philosophy and History of Science
  • Mental Health Research Topics
  • Ethics and Social Impacts of AI

DeepMind (United Kingdom)
2022

Rhodes College
2019-2020

Australian National University
2020

Responsible innovation on large-scale Language Models (LMs) requires foresight into and in-depth understanding of the risks these models may pose. This paper develops a comprehensive taxonomy ethical social associated with LMs. We identify twenty-one risks, drawing expertise literature from computer science, linguistics, sciences. situate in our six risk areas: I. Discrimination, Hate speech Exclusion, II. Information Hazards, III. Misinformation Harms, IV. Malicious Uses, V. Human-Computer...

10.1145/3531146.3533088 article EN 2022 ACM Conference on Fairness, Accountability, and Transparency 2022-06-20

Abstract May cites a body of evidence suggesting that participants take consequences, personal harm, and other factors into consideration when making moral judgments. This is used to support the conclusion cognition relies on rule-based inference. commentary defends an alternative interpretation this evidence, namely, it can be explained in terms domain general valuation mechanisms .

10.1017/s0140525x18002686 article EN Behavioral and Brain Sciences 2019-01-01

Abstract In this opinionated review, I draw attention to some of the contributions reinforcement learning can make questions in philosophy mind. particular, highlight learning's foundational emphasis on role reward agent learning, and canvass two ways which framework may advance our understanding perception motivation.

10.1111/phc3.12865 article EN Philosophy Compass 2022-08-07

Explanation of binocular rivalry is taken as a classic illustration hierarchical predictive coding’s explanatory power. I revisit the account and show that it cannot explain role reward in rivalry. modified version processing approach may for by recasting form optimism bias. Accepting this account, however, at odds with epistemic commitments favored proponents coding.

10.1080/09515089.2020.1827228 article EN Philosophical Psychology 2020-10-13
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