17 citations · 23 across the 6 of their papers we have counts for
7 papers
Why AI Slop Matters, but Not Like That
Sachita Nishal, Marijn Sax, Kimon Kieslich
This is a response to the paper ''Why Slop Matters''. By offering both immanent and external critique, we argue that the authors' reasoning neglects the socio-technical context of…
Towards Real-World Validity in Generative AI Benchmarks: Understanding and Designing Domain-Centered Evaluations for Journalism Practitioners
Charlotte Li, Nick Hagar, Sachita Nishal +2
Benchmarks play a significant role in how technology companies communicate about model capabilities and how researchers and the public understand generative AI systems. However, ex…
De-jargonizing Science for Journalists with GPT-4: A Pilot Study
Sachita Nishal, Eric Lee, Nicholas Diakopoulos
This study offers an initial evaluation of a human-in-the-loop system leveraging GPT-4 (a large language model or LLM), and Retrieval-Augmented Generation (RAG) to identify and def…
Domain-Specific Evaluation Strategies for AI in Journalism
Sachita Nishal, Charlotte Li, Nicholas Diakopoulos
News organizations today rely on AI tools to increase efficiency and productivity across various tasks in news production and distribution. These tools are oriented towards stakeho…
Envisioning the Applications and Implications of Generative AI for News Media
Sachita Nishal, Nicholas Diakopoulos
This article considers the increasing use of algorithmic decision-support systems and synthetic media in the newsroom, and explores how generative models can help reporters and edi…
Understanding Practices around Computational News Discovery Tools in the Domain of Science Journalism
Sachita Nishal, Jasmine Sinchai, Nicholas Diakopoulos
Science and technology journalists today face challenges in finding newsworthy leads due to increased workloads, reduced resources, and expanding scientific publishing ecosystems.…