Objective Epistemic Consequentialism
Askell, Amanda. ‘Objective Epistemic Consequntialism.’ BPhil thesis, University of Oxford (2011).
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Epistemic Consequentialism and Epistemic Enkrasia
Askell, Amanda. ‘Epistemic Consequentialism and Epistemic Enkrasia’. In Epistemic Consequentialism, edited by Kristoffer Ahlstrom-Vij and Jeff Dunn. Oxford: Oxford University Press, 2018
Pareto Principles in Infinite Ethics
Askell, Amanda. ‘Pareto Principles in Infinite Ethics.’ PhD thesis, New York University (2018).
AI Safety Needs Social Scientists
Irving & Askell, ‘AI Safety Needs Social Scientists’, Distill, 2019.
Prudential Objections to Atheism
Askell, Amanda. ‘Prudential Objections to Atheism’. In A Companion to Atheism and Philosophy, edited by Graham Oppy. Wiley-Blackwell, 2019.
The Role of Cooperation in Responsible AI Development
Askell, Amanda, Miles Brundage, and Gillian Hadfield. ‘The Role of Cooperation in Responsible AI Development.’ arXiv preprint arXiv:1907.04534 (2019).
Release Strategies and the Social Impacts of Language Models
Solaiman, Irene, et al. ‘Release strategies and the social impacts of language models.’ arXiv preprint arXiv:1908.09203 (2019).
Evidence Neutrality and the Moral Value of Information
Askell, Amanda. ‘Evidence Neutrality and the Moral Value of Information’. In Effective Altruism: Philosophical Issues, edited by Hilary Greaves and Theron Pummer. Oxford: Oxford University Press, 2019.
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
Miles Brundage, Shahar Avin, Jasmine Wang, and Haydn Belfield, et al. ‘Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims’. arXiv preprint arXiv:2004.07213 (2020).
Language Models are Few-Shot Learners
Brown, Tom; Mann, Ben; Ryder, Nick; Subbiah, Melanie et al. ‘Language Models are Few-Shot Learners.’ arXiv preprint arXiv:2005.14165 (2020).
Learning Transferable Visual Models From Natural Language Supervision
Radford, Alec & Kim, Jong Wook, et al. "Learning Transferable Visual Models From Natural Language Supervision." (2021).
Ensuring the Safety of Artificial Intelligence
Askell, Amanda. ‘Ensuring the Safety of Artificial Intelligence’. In The Long View: Essays on policy, philanthropy, and the long-term future. Edited by Natalie Cargill and Tyler M. John. First Strategic Insight Ltd, 2021.
A General Language Assistant as a Laboratory for Alignment
Askell, Amanda; Bai, Yuntao; Chen, Anna; Drain, Dawn; Ganguli, Deep; Henighan, Tom; Jones, Andy Joseph, Nicholas; Ben Mann, et al. A General Language Assistantas a Laboratory for Alignment. arXiv preprint arXiv:2112.00861 (2021)