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P. Eckersley

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • middle author1
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CY2
  • cs.AI1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedToward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims

219 citations · 235 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CY2020★ 219 cited

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims

Miles Brundage, Shahar Avin, Jasmine Wang +56

With the recent wave of progress in artificial intelligence (AI) has come a growing awareness of the large-scale impacts of AI systems, and recognition that existing regulations an…

cs.LG2019

Explainable Machine Learning in Deployment

Umang Bhatt, Alice Xiang, Shubham Sharma +7

Explainable machine learning offers the potential to provide stakeholders with insights into model behavior by using various methods such as feature importance scores, counterfactu…

cs.CY2019

Theories of Parenting and their Application to Artificial Intelligence

Sky Croeser, Peter Eckersley

As machine learning (ML) systems have advanced, they have acquired more power over humans' lives, and questions about what values are embedded in them have become more complex and…

cs.AI2019★ 16 cited

Impossibility and Uncertainty Theorems in AI Value Alignment (or why your AGI should not have a utility function)

Peter Eckersley

Utility functions or their equivalents (value functions, objective functions, loss functions, reward functions, preference orderings) are a central tool in most current machine lea…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.