76 citations · 233 across the 8 of their papers we have counts for
8 papers
Labeling Synthetic Content: User Perceptions of Warning Label Designs for AI-generated Content on Social Media
Dilrukshi Gamage, Dilki Sewwandi, Min Zhang +1
In this research, we explored the efficacy of various warning label designs for AI-generated content on social media platforms e.g., deepfakes. We devised and assessed ten distinct…
Moral intuitions behind deepfake-related discussions in Reddit communities
Dilrukshi Gamage, Hariharan Ravinthran, Kazutoshi Sasahara
Deepfakes are AI-synthesized content that are becoming popular on many social media platforms, meaning the use of deepfakes is increasing in society, regardless of its societal imp…
Are Deepfakes Concerning? Analyzing Conversations of Deepfakes on Reddit and Exploring Societal Implications
Dilrukshi Gamage, Piyush Ghasiya, Vamshi Krishna Bonagiri +2
Deepfakes are synthetic content generated using advanced deep learning and AI technologies. The advancement of technology has created opportunities for anyone to create and share d…
Together we learn better: leveraging communities of practice for MOOC learners
Dilrukshi Gamage, Mark E Whiting
MOOC participants often feel isolated and disconnected from their peers. Navigating meaningful peer interactions, generating a sense of belonging, and achieving social presence are…
Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms
Snehalkumar, S. Gaikwad, Durim Morina +35
Paid crowdsourcing platforms suffer from low-quality work and unfair rejections, but paradoxically, most workers and requesters have high reputation scores. These inflated scores,…
Prototype Tasks: Improving Crowdsourcing Results through Rapid, Iterative Task Design
Snehalkumar "Neil" S. Gaikwad, Nalin Chhibber, Vibhor Sehgal +26
Low-quality results have been a long-standing problem on microtask crowdsourcing platforms, driving away requesters and justifying low wages for workers. To date, workers have been…
Improving Assessment on MOOCs Through Peer Identification and Aligned Incentives
Dilrukshi Gamage, Mark Whiting, Thejan Rajapakshe +3
Massive Open Online Courses (MOOCs) use peer assessment to grade open ended questions at scale, allowing students to provide feedback. Relative to teacher based grading, peer asses…
Crowd Guilds: Worker-led Reputation and Feedback on Crowdsourcing Platforms
Mark E. Whiting, Dilrukshi Gamage, Snehalkumar S. Gaikwad +25
Crowd workers are distributed and decentralized. While decentralization is designed to utilize independent judgment to promote high-quality results, it paradoxically undercuts beha…