David Danks

According to our database, David Danks authored at least 56 papers between 2001 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Governing Ethical Gaps in Distributed AI Development.

Nandhini Swaminathan, David Danks

Digit. Soc., April, 2024

Application of the NIST AI Risk Management Framework to Surveillance Technology.

Nandhini Swaminathan, David Danks

CoRR, 2024

Future of Pandemic Prevention and Response CCC Workshop Report.

David Danks, Rada Mihalcea, Katie Siek, Mona Singh, Brian Dixon, Haley Griffin

CoRR, 2024

Commercial AI, Conflict, and Moral Responsibility: A theoretical analysis and practical approach to the moral responsibilities associated with dual-use AI technology.

Daniel Trusilo, David Danks

CoRR, 2024

Beyond Behaviorist Representational Harms: A Plan for Measurement and Mitigation.

Jennifer Chien, David Danks

CoRR, 2024

2023

Dynamic Certification for Autonomous Systems.

Georgios Bakirtzis, Steven Carr, David Danks, Ufuk Topcu

Commun. ACM, September, 2023

Ethical and methodological challenges in building morally informed AI systems.

Thilo Hagendorff, David Danks

AI Ethics, May, 2023

Artificial intelligence and humanitarian obligations.

Daniel Trusilo, David Danks

Ethics Inf. Technol., March, 2023

Fairness Vs. Personalization: Towards Equity in Epistemic Utility.

Jennifer Chien, David Danks

CoRR, 2023

The Ambiguity of Robot Rights.

Anisha Bontula, David Danks, Naomi T. Fitter

Proceedings of the Social Robotics - 15th International Conference, 2023

GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints.

Mohammadsajad Abavisani, David Danks, Sergey M. Plis

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Causal Learning through Deliberate Undersampling.

Kseniya Solovyeva, David Danks, Mohammadsajad Abavisani, Sergey M. Plis

Proceedings of the Conference on Causal Learning and Reasoning, 2023

2022

The Challenge of Ethical Interoperability.

David Danks, Daniel Trusilo

Digit. Soc., September, 2022

Homophily and Incentive Effects in Use of Algorithms.

Riccardo Fogliato, Sina Fazelpour, Shantanu Gupta, Zachary C. Lipton, David Danks

CoRR, 2022

Constraint-Based Causal Structure Learning from Undersampled Graphs.

Mohammadsajad Abavisani, David Danks, Sergey M. Plis

CoRR, 2022

2021

Governing AI safety through independent audits.

Gregory Falco, Ben Shneiderman, Julia Badger, Ryan Carrier, Anton Dahbura, David Danks, Martin Eling, Alwyn Goodloe, Jerry Gupta, Christopher Hart, Marina Jirotka, Henric Johnson, Cara Lapointe, Ashley J. Llorens, Alan K. Mackworth, Carsten Maple, Sigurður Emil Pálsson, Frank Pasquale, Alan F. T. Winfield, Zee Kin Yeong

Nat. Mach. Intell., 2021

The case for information fiduciaries: The implementation of a data ethics checklist at Seattle Children's Hospital.

Elizabeth Montague, T. Eugene Day, Dwight Barry, Maria Brumm, Aaron McAdie, Andrew B. Cooper, Julia Wignall, Steve Erdman, Diahnna Núñez, Douglas Diekema, David Danks

J. Am. Medical Informatics Assoc., 2021

AI4People: Ethical Guidelines for the Automotive Sector - Fundamental Requirements and Practical Recommendations.

Christoph Lütge, Franziska Poszler, Aida Joaquin Acosta, David Danks, Gail Gottehrer, Lucian Mihet-Popa, Aisha Naseer

Int. J. Technoethics, 2021

Individual Differences in Causal Learning.

Laila Johnston, Noah Hillman, David Danks

Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

Reason-Based Constraint in Theory of Mind.

Corey J. Cusimano, Natalia C. Zorrilla, David Danks, Tania Lombrozo

Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

Ethical Obligations to Provide Novelty.

Paige Golden, David Danks

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

Effects of Causal Determinism on Causal Learning Trajectories.

Phuong (Phoebe) Dinh, David Danks

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

Different "Intelligibility" for Different Folks.

Yishan Zhou, David Danks

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

Good Explanation for Algorithmic Transparency.

Joy Lu, Dokyun Lee, Tae Wan Kim, David Danks

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2019

Amalgamating evidence of dynamics.

David Danks, Sergey M. Plis

Synth., 2019

How Technological Advances Can Reveal Rights.

Jack Parker, David Danks

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Balancing the Benefits of Autonomous Vehicles.

Timothy Geary, David Danks

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

The Value of Trustworthy AI.

David Danks

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

Generalizations, from representation to transmission.

Michael Henry Tessler, Noah D. Goodman, David Danks, Emily Foster Hanson, Marjorie Rhodes, Greg Carlson

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

Regulating Autonomous Vehicles: A Policy Proposal.

Alex John London, David Danks

Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

Impacts on Trust of Healthcare AI.

Emily LaRosa, David Danks

Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

2017

A constraint optimization approach to causal discovery from subsampled time series data.

Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks

Int. J. Approx. Reason., 2017

Regulating Autonomous Systems: Beyond Standards.

David Danks, Alex John London

IEEE Intell. Syst., 2017

Algorithmic Bias in Autonomous Systems.

David Danks, Alex John London

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Causal modeling, discovery & inference for software engineering.

Rick Kazman, Robert Stoddard, David Danks, Yuanfang Cai

Proceedings of the 39th International Conference on Software Engineering, 2017

2016

Adaptively Rational Learning.

Sarah Wellen, David Danks

Minds Mach., 2016

Causal Discovery from Subsampled Time Series Data by Constraint Optimization.

Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

2015

Goal-dependence in (scientific) ontology.

David Danks

Synth., 2015

Mesochronal Structure Learning.

Sergey M. Plis, David Danks, Jianyu Yang

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Rate-Agnostic (Causal) Structure Learning.

Sergey M. Plis, David Danks, Cynthia Freeman, Vince D. Calhoun

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Erratum to: Model change and methodological virtues in scientific inference.

Erich Kummerfeld, David Danks

Synth., 2014

Model change and reliability in scientific inference.

Erich Kummerfeld, David Danks

Synth., 2014

Learning with a Purpose: The Influence of Goals.

Sarah Wellen, David Danks

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014

2013

Wisdom of crowds versus groupthink: learning in groups and in isolation.

Conor Mayo-Wilson, Kevin J. S. Zollman, David Danks

Int. J. Game Theory, 2013

Tracking Time-varying Graphical Structure.

Erich Kummerfeld, David Danks

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Moving from Levels & Reduction to Dimensions & Constraints.

David Danks

Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

What if? Counterfactual reasoning, pretense, and the role of possible worlds.

Daphna Buchsbaum, Caren M. Walker, Alison Gopnik, Nick Chater, David Danks, Christopher G. Lucas, Charles Kemp, Eva Rafetseder, Josef Perner

Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

2012

Learning Causal Structure through Local Prediction-error Learning.

Sarah Wellen, David Danks

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

Actor-Observer Asymmetries in Judgments of Intentional Actions.

Sarah Wellen, David Danks

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

2011

Confirmation in the Cognitive Sciences: The Problematic Case of Bayesian Models.

Frederick Eberhardt, David Danks

Minds Mach., 2011

2010

Actual causation: a stone soup essay.

Clark Glymour, David Danks, Bruce Glymour, Frederick Eberhardt, Joseph D. Ramsey, Richard Scheines, Peter Spirtes, Choh Man Teng, Jiji Zhang

Synth., 2010

2008

Integrating Locally Learned Causal Structures with Overlapping Variables.

Robert E. Tillman, David Danks, Clark Glymour

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2004

Constraint-Based Human Causal Learning.

David Danks

Proceedings of the International Conference on Cognitive Modelling, 2004

2002

Dynamical Causal Learning.

David Danks, Thomas L. Griffiths, Joshua B. Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Learning the Causal Structure of Overlapping Variable Sets.

David Danks

Proceedings of the Discovery Science, 5th International Conference, 2002

2001

Linearity Properties of Bayes Nets with Binary Variables.

David Danks, Clark Glymour

Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001