Publications
- Blameworthiness in Multi-Agent Settings (paper)
Meir Friedenberg and Joseph Y. Halpern
AAAI Conference on Artificial Intelligence, 2019
Abstract: We provide a formal definition of blameworthiness in settings where multiple agents can collaborate to avoid a negative outcome. We first provide a method for ascribing blameworthiness to groups relative to an epistemic state (a distribution over causal models that describe how the outcome might arise). We then show how we can go from an ascription of blameworthiness for groups to an ascription of blameworthiness for individuals using a standard notion from cooperative game theory, the Shapley value. We believe that getting a good notion of blameworthiness in a group setting will be critical for designing autonomous agents that behave in a moral manner.
- Combining the Causal Judgments of Experts with Possibly Different Focus Areas (paper)
Meir Friedenberg and Joseph Y. Halpern
International Conference on Principles of Knowledge Representation and Reasoning, 2018
Abstract: In many real-world settings, a decision-maker must combine information provided by different experts in order to decide on an effective policy. Alrajeh, Chockler, and Halpern showed how to combine causal models that are compatible in the sense that, for variables that appear in both models, the experts agree on the causal structure. In this work we show how causal models can be combined in cases where the experts might disagree on the causal structure for variables that appear in both models due to having different focus areas. We provide a new formal definition of compatibility of models in this setting and show how compatible models can be combined. We also consider the complexity of determining whether models are compatible. We believe that the notions defined in this work are of direct relevance to many practical decision making scenarios that come up in natural, social, and medical science settings.
- Expert, Crowdsourced, and Machine Assessment of Suicide Risk via Online Postings (Paper, Dataset)
Han-Chin Shing, Suraj Nair, Ayah Zirikly, Meir Friedenberg, Hal Daumé III, and Philip Resnik
Workshop on Computational Linguistics and Clinical Psychology (CLPsych), 2018
Abstract: We report on the creation of a dataset for studying assessment of suicide risk via online postings in Reddit. Evaluation of risk-level annotations by experts yields what is, to our knowledge, the first demonstration of reliability in risk assessment by clinicians based on social media postings. We also introduce and demonstrate the value of a new, detailed rubric for assessing suicide risk, compare crowdsourced with expert performance, and present baseline predictive modeling experiments using the new dataset, which will be made available to researchers through the American Association of Suicidology.
