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2020 – today
- 2023
[j16]Thilo Hagendorff
, David Danks:
Ethical and methodological challenges in building morally informed AI systems. AI Ethics 3(2): 553-566 (2023)- [j15]Daniel Trusilo, David Danks:
Artificial intelligence and humanitarian obligations. Ethics Inf. Technol. 25(1): 12 (2023) - [c28]Kseniya Solovyeva, David Danks, Mohammadsajad Abavisani, Sergey M. Plis:
Causal Learning through Deliberate Undersampling. CLeaR 2023: 518-530 - [c27]Mohammadsajad Abavisani, David Danks, Sergey M. Plis:
GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints. ICLR 2023 - [i6]Jennifer Chien, David Danks:
Fairness Vs. Personalization: Towards Equity in Epistemic Utility. CoRR abs/2309.11503 (2023) - 2022
- [j14]David Danks, Daniel Trusilo:
The Challenge of Ethical Interoperability. Digit. Soc. 1(2) (2022) - [i5]Georgios Bakirtzis, Steven Carr, David Danks, Ufuk Topcu:
Dynamic Certification for Autonomous Systems. CoRR abs/2203.10950 (2022) - [i4]Mohammadsajad Abavisani, David Danks, Sergey M. Plis:
Constraint-Based Causal Structure Learning from Undersampled Graphs. CoRR abs/2205.09235 (2022) - [i3]Riccardo Fogliato, Sina Fazelpour, Shantanu Gupta, Zachary C. Lipton, David Danks:
Homophily and Incentive Effects in Use of Algorithms. CoRR abs/2205.09701 (2022) - 2021
- [j13]Christoph Lütge, Franziska Poszler, Aida Joaquin Acosta, David Danks, Gail Gottehrer, Lucian Mihet-Popa, Aisha Naseer:
AI4People: Ethical Guidelines for the Automotive Sector - Fundamental Requirements and Practical Recommendations. Int. J. Technoethics 12(1): 101-125 (2021) - [j12]Elizabeth Montague, T. Eugene Day, Dwight Barry, Maria Brumm, Aaron McAdie, Andrew B. Cooper, Julia Wignall, Steve Erdman, Diahnna Núñez, Douglas Diekema, David Danks:
The case for information fiduciaries: The implementation of a data ethics checklist at Seattle Children's Hospital. J. Am. Medical Informatics Assoc. 28(3): 650-652 (2021) - [j11]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:
Governing AI safety through independent audits. Nat. Mach. Intell. 3(7): 566-571 (2021) - [c26]Paige Golden, David Danks:
Ethical Obligations to Provide Novelty. AIES 2021: 502-508 - 2020
- [c25]Joy Lu, Dokyun Lee, Tae Wan Kim, David Danks:
Good Explanation for Algorithmic Transparency. AIES 2020: 93 - [c24]Yishan Zhou, David Danks:
Different "Intelligibility" for Different Folks. AIES 2020: 194-199 - [c23]Phuong (Phoebe) Dinh, David Danks:
Effects of Causal Determinism on Causal Learning Trajectories. CogSci 2020
2010 – 2019
- 2019
- [j10]David Danks, Sergey M. Plis:
Amalgamating evidence of dynamics. Synth. 196(8): 3213-3230 (2019) - [c22]Timothy Geary, David Danks:
Balancing the Benefits of Autonomous Vehicles. AIES 2019: 181-186 - [c21]Jack Parker, David Danks:
How Technological Advances Can Reveal Rights. AIES 2019: 201 - [c20]David Danks:
The Value of Trustworthy AI. AIES 2019: 521-522 - 2018
- [c19]Emily LaRosa, David Danks:
Impacts on Trust of Healthcare AI. AIES 2018: 210-215 - [c18]Alex John London, David Danks:
Regulating Autonomous Vehicles: A Policy Proposal. AIES 2018: 216-221 - [c17]Michael Henry Tessler, Noah D. Goodman, David Danks, Emily Foster Hanson, Marjorie Rhodes, Greg Carlson:
Generalizations, from representation to transmission. CogSci 2018 - 2017
- [j9]David Danks, Alex John London:
Regulating Autonomous Systems: Beyond Standards. IEEE Intell. Syst. 32(1): 88-91 (2017) - [j8]Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks:
A constraint optimization approach to causal discovery from subsampled time series data. Int. J. Approx. Reason. 90: 208-225 (2017) - [c16]Rick Kazman, Robert Stoddard, David Danks, Yuanfang Cai:
Causal modeling, discovery & inference for software engineering. ICSE (Companion Volume) 2017: 172-174 - [c15]David Danks, Alex John London:
Algorithmic Bias in Autonomous Systems. IJCAI 2017: 4691-4697 - 2016
- [j7]Sarah Wellen, David Danks:
Adaptively Rational Learning. Minds Mach. 26(1-2): 87-102 (2016) - [c14]Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks:
Causal Discovery from Subsampled Time Series Data by Constraint Optimization. Probabilistic Graphical Models 2016: 216-227 - [i2]Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks:
Causal Discovery from Subsampled Time Series Data by Constraint Optimization. CoRR abs/1602.07970 (2016) - 2015
- [j6]David Danks:
Goal-dependence in (scientific) ontology. Synth. 192(11): 3601-3616 (2015) - [c13]Sergey M. Plis, David Danks, Cynthia Freeman, Vince D. Calhoun:
Rate-Agnostic (Causal) Structure Learning. NIPS 2015: 3303-3311 - [c12]Sergey M. Plis, David Danks, Jianyu Yang:
Mesochronal Structure Learning. UAI 2015: 702-711 - 2014
- [j5]Erich Kummerfeld, David Danks:
Model change and reliability in scientific inference. Synth. 191(12): 2673-2693 (2014) - [j4]Erich Kummerfeld, David Danks:
Erratum to: Model change and methodological virtues in scientific inference. Synth. 191(14): 3469-3472 (2014) - [c11]Sarah Wellen, David Danks:
Learning with a Purpose: The Influence of Goals. CogSci 2014 - 2013
- [j3]Conor Mayo-Wilson, Kevin J. S. Zollman, David Danks:
Wisdom of crowds versus groupthink: learning in groups and in isolation. Int. J. Game Theory 42(3): 695-723 (2013) - [c10]Daphna Buchsbaum, Caren M. Walker, Alison Gopnik, Nick Chater, David Danks, Christopher G. Lucas, Charles Kemp, Eva Rafetseder, Josef Perner:
What if? Counterfactual reasoning, pretense, and the role of possible worlds. CogSci 2013 - [c9]David Danks:
Moving from Levels & Reduction to Dimensions & Constraints. CogSci 2013 - [c8]Erich Kummerfeld, David Danks:
Tracking Time-varying Graphical Structure. NIPS 2013: 1205-1213 - [i1]David Danks, Clark Glymour:
Linearity Properties of Bayes Nets with Binary Variables. CoRR abs/1301.2263 (2013) - 2012
- [c7]Sarah Wellen, David Danks:
Actor-Observer Asymmetries in Judgments of Intentional Actions. CogSci 2012 - [c6]Sarah Wellen, David Danks:
Learning Causal Structure through Local Prediction-error Learning. CogSci 2012 - 2011
- [j2]Frederick Eberhardt, David Danks:
Confirmation in the Cognitive Sciences: The Problematic Case of Bayesian Models. Minds Mach. 21(3): 389-410 (2011) - 2010
- [j1]Clark Glymour, David Danks, Bruce Glymour, Frederick Eberhardt, Joseph D. Ramsey, Richard Scheines, Peter Spirtes, Choh Man Teng, Jiji Zhang:
Actual causation: a stone soup essay. Synth. 175(2): 169-192 (2010)
2000 – 2009
- 2008
- [c5]Robert E. Tillman, David Danks, Clark Glymour:
Integrating Locally Learned Causal Structures with Overlapping Variables. NIPS 2008: 1665-1672 - 2004
- [c4]David Danks:
Constraint-Based Human Causal Learning. ICCM 2004: 342-343 - 2002
- [c3]David Danks:
Learning the Causal Structure of Overlapping Variable Sets. Discovery Science 2002: 178-191 - [c2]David Danks, Thomas L. Griffiths, Joshua B. Tenenbaum:
Dynamical Causal Learning. NIPS 2002: 67-74 - 2001
- [c1]David Danks, Clark Glymour:
Linearity Properties of Bayes Nets with Binary Variables. UAI 2001: 98-104
Coauthor Index
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last updated on 2023-09-28 03:40 CEST by the dblp team
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