111 citations · 320 across the 14 of their papers we have counts for
14 papers
AHA!: Facilitating AI Impact Assessment by Generating Examples of Harms
Zana Buçinca, Chau Minh Pham, Maurice Jakesch +3
While demands for change and accountability for harmful AI consequences mount, foreseeing the downstream effects of deploying AI systems remains a challenging task. We developed AH…
Challenges to Evaluating the Generalization of Coreference Resolution Models: A Measurement Modeling Perspective
Ian Porada, Alexandra Olteanu, Kaheer Suleman +2
It is increasingly common to evaluate the same coreference resolution (CR) model on multiple datasets. Do these multi-dataset evaluations allow us to draw meaningful conclusions ab…
Can Workers Meaningfully Consent to Workplace Wellbeing Technologies?
Shreya Chowdhary, Anna Kawakami, Mary L. Gray +3
Sensing technologies deployed in the workplace can unobtrusively collect detailed data about individual activities and group interactions that are otherwise difficult to capture. A…
Sensing Wellbeing in the Workplace, Why and For Whom? Envisioning Impacts with Organizational Stakeholders
Anna Kawakami, Shreya Chowdhary, Shamsi T. Iqbal +4
With the heightened digitization of the workplace, alongside the rise of remote and hybrid work prompted by the pandemic, there is growing corporate interest in using passive sensi…
Human-Centered Responsible Artificial Intelligence: Current & Future Trends
Mohammad Tahaei, Marios Constantinides, Daniele Quercia +13
In recent years, the CHI community has seen significant growth in research on Human-Centered Responsible Artificial Intelligence. While different research communities may use diffe…
The KITMUS Test: Evaluating Knowledge Integration from Multiple Sources in Natural Language Understanding Systems
Akshatha Arodi, Martin Pömsl, Kaheer Suleman +3
Many state-of-the-art natural language understanding (NLU) models are based on pretrained neural language models. These models often make inferences using information from multiple…