A. Feder Cooper | DeepAI

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∙ 09/15/2023

Talkin' 'Bout AI Generation: Copyright and the Generative-AI Supply Chain

"Does generative AI infringe copyright?" is an urgent question. It is al...

0 Katherine Lee, et al. ∙

∙ 01/27/2023

Variance, Self-Consistency, and Arbitrariness in Fair Classification

In fair classification, it is common to train a model, and to compare an...

0 A. Feder Cooper, et al. ∙

∙ 08/03/2022

Fast or Accurate? Governing Conflicting Goals in Highly Autonomous Vehicles

The tremendous excitement around the deployment of autonomous vehicles (...

0 A. Feder Cooper, et al. ∙

∙ 06/23/2022

Non-Determinism and the Lawlessness of ML Code

Legal literature on machine learning (ML) tends to focus on harms, and a...

0 A. Feder Cooper, et al. ∙

∙ 06/14/2022

Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects

Fairness, Accountability, and Transparency (FAccT) for socio-technical s...

0 Benjamin Laufer, et al. ∙

∙ 02/10/2022

Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning

In 1996, philosopher Helen Nissenbaum issued a clarion call concerning t...

0 A. Feder Cooper, et al. ∙

∙ 01/28/2022

Making the Unaccountable Internet: The Changing Meaning of Accounting in the Design of the Early Internet

Contemporary concerns over the governance of technological systems often...

0 A. Feder Cooper, et al. ∙

∙ 09/22/2021

Tecnologica cosa: Modeling Storyteller Personalities in Boccaccio's Decameron

We explore Boccaccio's Decameron to see how digital humanities tools can...

0 A. Feder Cooper, et al. ∙

∙ 04/01/2021

Model Selection's Disparate Impact in Real-World Deep Learning Applications

Algorithmic fairness has emphasized the role of biased data in automated...

9 Jessica Zosa Forde, et al. ∙

∙ 02/01/2021

Emergent Unfairness: Normative Assumptions and Contradictions in Algorithmic Fairness-Accuracy Trade-Off Research

Across machine learning (ML) sub-disciplines, researchers make explicit ...

0 A. Feder Cooper, et al. ∙

∙ 10/20/2020

Where Is the Normative Proof? Assumptions and Contradictions in ML Fairness Research

Across machine learning (ML) sub-disciplines researchers make mathematic...

0 A. Feder Cooper, et al. ∙

∙ 07/04/2020

Regulating Accuracy-Efficiency Trade-Offs in Distributed Machine Learning Systems

In this paper we discuss the trade-off between accuracy and efficiency i...

0 A. Feder Cooper, et al. ∙

∙ 06/20/2020

Asymptotically Optimal Exact Minibatch Metropolis-Hastings

Metropolis-Hastings (MH) is a commonly-used MCMC algorithm, but it can b...

1 Ruqi Zhang, et al. ∙

∙ 02/29/2020

AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC

Stochastic gradient Hamiltonian Monte Carlo (SGHMC) is an efficient meth...

0 Ruqi Zhang, et al. ∙

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