Jane Im

2papers

2 Papers

5.2HCApr 20
Enabling Sensitive Conversations with Consent Boundaries: Moa, a Platform for Discussing PhD Advising Relationships

Jane Im, Kentaro Toyama

When an individual is harmed by someone in power, such as a workplace manager, it can help to identify allies--people who would offer sympathy, advice, or supportive action. However, ally discovery is fraught because the very people who might be most relevant--e.g., someone who reports to the same manager--might not be sympathetic and could potentially exacerbate the harm. We examine this problem in the specific context of PhD students navigating advising challenges and present a social media platform called "Moa" that brings together a number of features that we believe facilitate ally discovery. Moa's most novel element is an audience selection process that uses what we call consent boundaries, which allow users to flexibly define each post or comment's audience based on factors such as common social identity or lived experience, all while preserving anonymity--neither senders nor recipients learn each other's identities, even as the post reaches the right audience. A 3-week field study with 47 real-world users showed that the features in combination facilitated sensitive conversations about advising, with 22.6% of users using consent boundaries. We discuss both our overall "recipe" for systems for ally discovery and the benefits of a consent-centered approach to design.

HCAug 17, 2021
Searching For or Reviewing Evidence Improves Crowdworkers' Misinformation Judgments and Reduces Partisan Bias

Paul Resnick, Aljohara Alfayez, Jane Im et al.

Can crowd workers be trusted to judge whether news-like articles circulating on the Internet are misleading, or does partisanship and inexperience get in the way? And can the task be structured in a way that reduces partisanship? We assembled pools of both liberal and conservative crowd raters and tested three ways of asking them to make judgments about 374 articles. In a no research condition, they were just asked to view the article and then render a judgment. In an individual research condition, they were also asked to search for corroborating evidence and provide a link to the best evidence they found. In a collective research condition, they were not asked to search, but instead to review links collected from workers in the individual research condition. Both research conditions reduced partisan disagreement in judgments. The individual research condition was most effective at producing alignment with journalists' assessments. In this condition, the judgments of a panel of sixteen or more crowd workers were better than that of a panel of three expert journalists, as measured by alignment with a held out journalist's ratings.