activity
20192023
most cited"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models

115 citations · 295 across the 9 of their papers we have counts for

collaborators

9 papers

cs.HC2023★ 3 cited

Co-audit: tools to help humans double-check AI-generated content

Andrew D. Gordon, Carina Negreanu, José Cambronero +9

Users are increasingly being warned to check AI-generated content for correctness. Still, as LLMs (and other generative models) generate more complex output, such as summaries, tab…

cs.HC2023★ 49 cited

Exploring Perspectives on the Impact of Artificial Intelligence on the Creativity of Knowledge Work: Beyond Mechanised Plagiarism and Stochastic Parrots

Advait Sarkar

Artificial Intelligence (AI), and in particular generative models, are transformative tools for knowledge work. They problematise notions of creativity, originality, plagiarism, th…

cs.HC2023★ 20 cited

Should Computers Be Easy To Use? Questioning the Doctrine of Simplicity in User Interface Design

Advait Sarkar

That computers should be easy to learn and use is a rarely-questioned tenet of user interface design. But what do we gain from prioritising usability and learnability, and what do…

cs.HC2023★ 47 cited

Enough With "Human-AI Collaboration"

Advait Sarkar

Describing our interaction with Artificial Intelligence (AI) systems as 'collaboration' is well-intentioned, but flawed. Not only is it misleading, but it also takes away the credi…

cs.HC2023★ 3 cited

User Perceptions of Automatic Fake News Detection: Can Algorithms Fight Online Misinformation?

Bruno Tafur, Advait Sarkar

Fake news detection algorithms apply machine learning to various news attributes and their relationships. However, their success is usually evaluated based on how the algorithm per…

cs.HC2023★ 115 cited

"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models

Michael Xieyang Liu, Advait Sarkar, Carina Negreanu +4

Code-generating large language models translate natural language into code. However, only a small portion of the infinite space of naturalistic utterances is effective at guiding c…

cs.HC2022★ 47 cited

What is it like to program with artificial intelligence?

Advait Sarkar, Andrew D. Gordon, Carina Negreanu +3

Large language models, such as OpenAI's codex and Deepmind's AlphaCode, can generate code to solve a variety of problems expressed in natural language. This technology has already…

cs.AI2022★ 9 cited

Is explainable AI a race against model complexity?

Advait Sarkar

Explaining the behaviour of intelligent systems will get increasingly and perhaps intractably challenging as models grow in size and complexity. We may not be able to expect an exp…

cs.HC2019★ 2 cited

Somewhere Around That Number: An Interview Study of How Spreadsheet Users Manage Uncertainty

Judith Borghouts, Andrew D. Gordon, Advait Sarkar +2

Spreadsheet users regularly deal with uncertainty in their data, for example due to errors and estimates. While an insight into data uncertainty can help in making better informed…