Workshop
Workshop on Human and Machine Decisions
Daniel Reichman · Joshua Peterson · Kiran Tomlinson · Annie Liang · Tom Griffiths
Tue 14 Dec, 6:05 a.m. PST
Understanding human decision-making is a key focus of behavioral economics, psychology, and neuroscience with far-reaching applications, from public policy to industry. Recently, advances in machine learning have resulted in better predictive models of human decisions and even enabled new theories of decision-making. On the other hand, machine learning systems are increasingly being used to make decisions that affect people, including hiring, resource allocation, and paroles. These lines of work are deeply interconnected: learning what people value is crucial both to predict their own decisions and to make good decisions for them. In this workshop, we will bring together experts from the wide array of disciplines concerned with human and machine decisions to exchange ideas around three main focus areas: (1) using theories of decision-making to improve machine learning models, (2) using machine learning to inform theories of decision-making, and (3) improving the interaction between people and decision-making AIs.
Schedule
Tue 6:05 a.m. - 6:20 a.m.
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Opening remarks
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Opening remarks
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SlidesLive Video |
Tom Griffiths 🔗 |
Tue 6:20 a.m. - 6:50 a.m.
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Modeling Human Decision-Making: Never Ending Learning
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Keynote
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SlidesLive Video |
Sarit Kraus 🔗 |
Tue 6:50 a.m. - 7:20 a.m.
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Evaluating and Improving Economic Models
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Keynote
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SlidesLive Video |
Drew Fudenberg 🔗 |
Tue 7:20 a.m. - 7:30 a.m.
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Break
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Tue 7:30 a.m. - 8:00 a.m.
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Integrating Explanation and Prediction in Computational Social Science
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Keynote
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SlidesLive Video |
Duncan J Watts 🔗 |
Tue 8:00 a.m. - 9:00 a.m.
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Panel I: Human decisions
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Panel, moderated by Annie Liang
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SlidesLive Video |
Jennifer Trueblood · Alex Peysakhovich · Angela Yu · Ori Plonsky · Tal Yarkoni · Daniel Bjorkegren 🔗 |
Tue 9:00 a.m. - 9:40 a.m.
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Break
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Tue 9:40 a.m. - 10:00 a.m.
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New Perspectives on Habit Formation from Machine Learning and Neuroeconomics
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Keynote
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SlidesLive Video |
Colin Camerer 🔗 |
Tue 10:00 a.m. - 11:00 a.m.
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Keynote speakers Q&A
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Panel
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SlidesLive Video |
Sarit Kraus · Drew Fudenberg · Duncan J Watts · Colin Camerer · Johan Ugander · Emma Pierson 🔗 |
Tue 11:00 a.m. - 11:10 a.m.
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The Effect of an Algorithmic Tool on Child Welfare Decision Making: A Preliminary Evaluation
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Contributed talk
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SlidesLive Video |
Marie-Pascale Grimon · Chris Mills 🔗 |
Tue 11:10 a.m. - 11:40 a.m.
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Choices and Rankings with Irrelevant Alternatives
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Keynote
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SlidesLive Video |
Johan Ugander 🔗 |
Tue 11:40 a.m. - 12:00 p.m.
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Break
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Tue 12:00 p.m. - 1:00 p.m.
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Panel II: Machine decisions
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Panel, moderated by Brian Christian
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SlidesLive Video |
Anca Dragan · Karen Levy · Himabindu Lakkaraju · Ariel Rosenfeld · Maithra Raghu · Irene Y Chen 🔗 |
Tue 1:00 p.m. - 1:10 p.m.
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Bayesian Persuasion for Algorithmic Recourse
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Contributed talk
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SlidesLive Video |
Keegan Harris · Valerie Chen · Joon Sik Kim · Ameet Talwalkar · Hoda Heidari · Steven Wu 🔗 |
Tue 1:10 p.m. - 1:40 p.m.
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Policing, Pain, and Politics: Diagnosing Human Bias and Error with Machine Learning
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Keynote
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SlidesLive Video |
Emma Pierson 🔗 |
Tue 1:40 p.m. - 1:50 p.m.
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Designing Defaults for School Choice
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Contributed talk
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SlidesLive Video |
Amel Awadelkarim · Johan Ugander · Itai Ashlagi · Irene Lo 🔗 |
Tue 1:50 p.m. - 2:00 p.m.
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Closing remarks
(
Closing remarks
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SlidesLive Video |
🔗 |
Tue 2:00 p.m. - 2:40 p.m.
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Poster session I ( Poster session ) > link | 🔗 |
Tue 2:40 p.m. - 3:20 p.m.
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Poster session II ( Poster session ) > link | 🔗 |
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Neural-Symbolic Integration for Interactive Learning and Conceptual Grounding
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Poster
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Benedikt Wagner · Artur Garcez 🔗 |
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Improving Learning-to-Defer Algorithms Through Fine-Tuning
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Poster
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Naveen Raman · Michael Yee 🔗 |
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Artificial Intelligence, Ethics, and Intergenerational Responsibility
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Poster
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Alicia von Schenk · Marie C Villeval · Victor Klockmann 🔗 |
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Extrapolation Frameworks in Cognitive Psychology Suitable for Study of Image Classification Models
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Poster
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Roozbeh Yousefzadeh · Jessica Mollick 🔗 |
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Representational Denoising to Improve Medical Image Decision Making
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Poster
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Eeshan Hasan · Jennifer Trueblood · Quentin Eichbaum · Adam Seegmiller · Charles Stratton 🔗 |
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Improving Human Decision-Making with Machine Learning
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Poster
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Hamsa Bastani · Osbert Bastani · Park Sinchaisri 🔗 |
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Probabilistic Performance Metric Elicitation
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Poster
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Zachary Robertson · Hantao Zhang · Sanmi Koyejo 🔗 |
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Assigning Credit to Human Decisions using Modern Hopfield Networks
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Poster
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Michael Widrich · Markus Hofmarcher · Vihang Patil · Angela Bitto · Sepp Hochreiter 🔗 |
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Explainable Patterns for Distinction and Prediction of Moral Judgement on Reddit
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Poster
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Ion Stagkos Efstathiadis · Guilherme Paulino-Passos · Francesca Toni 🔗 |
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Excited and aroused: The predictive importance of simple choice process metrics
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Poster
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Steffen Mueller · Patrick Ring · Maria Fischer 🔗 |
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In silico manipulation of human cortical computation underlying goal-directed learning
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Poster
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Jaehoon Shin · Jee Hang Lee · Sang Wan Lee 🔗 |
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Will We Trust What We Don’t Understand? Impact of Model Interpretability and Outcome Feedback on Trust in AI
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Poster
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Daehwan Ahn · Abdullah Almaatouq · Monisha Gulabani · Kartik Hosanagar 🔗 |
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Catastrophe, Compounding & Consistency in Choice
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Poster
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Christopher Gagne · Peter Dayan 🔗 |
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Leveraging Information about Background Music in Human-Robot Interaction
(
Poster
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Elad Liebman · Peter Stone 🔗 |
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Semiparametric approaches for decision making in high-dimensional sensory discrimination tasks
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Poster
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Stephen Keeley · Ben Letham · Chase Tymms · Michael Shvartsman 🔗 |
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Integrating Machine Learning and a Cognitive Modeling of Decision Making
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Poster
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Taher Rahgooy · Jennifer Trueblood · Brent Venable 🔗 |
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Nearest-neighbor is more useful than feature attribution in improving human accuracy on image classification
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Poster
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Giang Nguyen · Anh Nguyen 🔗 |
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Deep Gaussian Processes for Preference Learning
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Poster
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Rex Chen · Norman Sadeh · Fei Fang 🔗 |
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On the Value of ML Models
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Poster
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Fabio Casati · Pierre-André Noël · Jie Yang 🔗 |
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Trucks Don’t Mean Trump: Diagnosing Human Error in Image Analysis
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Poster
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J.D. Zamfirescu-Pereira · Jerry Chen · Emily Wen · Allison Koenecke · Nikhil Garg · Emma Pierson 🔗 |
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The Effect of an Algorithmic Tool on Child Welfare Decision Making: A Preliminary Evaluation
(
Poster
)
>
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Marie-Pascale Grimon · Chris Mills 🔗 |
-
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Bayesian Persuasion for Algorithmic Recourse
(
Poster
)
>
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Keegan Harris · Valerie Chen · Joon Sik Kim · Ameet Talwalkar · Hoda Heidari · Steven Wu 🔗 |
-
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Designing Defaults for School Choice
(
Poster
)
>
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Amel Awadelkarim · Johan Ugander · Itai Ashlagi · Irene Lo 🔗 |