Amanda Bower – Fairness in Compound Decision Making Processes
Ansgar Koene – Trustworthy Algorithmic Decision-Making, Based on the UnBias project
Anthony T. Pinter – Algorithms as Audiences
Berk Ustun – Trustworthy Decision-Making via Optimal Scoring Systems
Bo Cowgill and Catherine Tucker – Algorithmic Bias: A Counterfactual Perspective
Christin Seifert – Contextialized and personalized explainations of machine learning algorithms
Christine T. Wolf – Algorithmic Living: A Practice-based Approach to Studying Algorithmic Systems
Chuck Howell – Fairness Cases: A framework for incremental progress in consequential machine learning
David J Stracuzzi – Increasing Trust By Quantifying Uncertainty
David Weinberger – Don’t explain. Optimize.
Elijah Mayfield – The Hidden Work of Implementing Technology in Education
Ellen Vorhees – Datasets and Benchmarks for AI
Emrah Akyol – Trustworthy Algorithmic Decision-Making via Transparent Machine Learning
Ezekiel Dixon-Román – Algorithmic Reasoning as Racializing Assemblages
Finale Doshi-Velez, Ryan Budish, and Mason Kortz – The Role of Explanation in Algorithmic Trust
Galen Harrison – Publicly Fair Machine Learning
Inbal Talgam-Cohen – Pricing Equilibrium – Inherently Trustworthy, Approximately Fair
Jed Brubaker – Socializing Algorithms
Jenn Halen – Discriminatory biases can become a subtle, built-in feature of algorithmic design
Joshua Kroll – Accountability, Evidence, and Trust in Automated Decision-Making
Katharina A. Zweig – Data Donations – A Study Design to hold Algorithms Accountable by Crowd Sourcing
Kristen Vaccaro – Algorithmic Appeals
Ling Liu – Trustworthiness of Deep Learning in Adversarial Settings
Maria Y. Rodriguez, PhD, MSW, Teresa De Candia, and Leila Pree – Evaluating Predictive Algorithms for Racial Equity: A Case Study of the NYC Administration for Children’s Services
Matthew Zook – Smart Cities and Secret Algorithms: How do we Trust Big Data Urban Algorithms?
Min Kyung Lee – A contextual framework for conceptualizing fair & trustworthy algorithmic decisions
Nicholas Diakopoulos – Towards Algorithmic Transparency
Raquel L. Hill – Online Data and the Job Seeker
Rishi Ahuja and Bryce Stephens – Potential Risks and Legal Challenges Associated with the Use of Alternative Data and Algorithms in the Credit Process
Shion Guha – Trust and Ethics in Algorithmic Crime Analysis
Stacy Wood – Algorithmic Trust within the Criminal Justice Context
Vincent Conitzer, Jana Schaich Borg, and Walter Sinnott-Armstrong – Using Human Subjects’ Judgments for Automated Moral Decision Making
William Rinehart – Understanding the Impact of Algorithms Requires Social Significance, Not Simply Statistical Significance
Zhe Zhang and Daniel B. Neill – Increasing Trust By Detecting Hidden Prediction Bias and Mistakes