Luke Stark

41 papers receiving 2.0k citations

Luke Stark's Hit Papers

Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI 2020 · 256 citations
2560+3+6Years since publication100200300400500

Peers

Luke Stark
Comparison fields: 5 of 109
  • Health Informatics 116
  • Safety Research 675
  • Human-Computer Interaction 272
  • Marketing 429
  • Computer Science Applications 130
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Christian Sandvig United States
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Citations per year

Countries citing papers authored by Luke Stark

Since Specialization
Citations

This map shows the geographic impact of Luke Stark's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Luke Stark with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luke Stark more than expected).

Fields of papers citing papers by Luke Stark

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luke Stark. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Luke Stark. The network helps show where Luke Stark may publish in the future.

Co-authors

The 25 scholars most cited alongside Luke Stark, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Luke Stark Line = papers co-authored together Luke Stark links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Algorithmic Labor and Information Asymmetries: A Case Study of Uber’s Drivers
Hit paper breakdown →
2016596
2
Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI
Hit paper breakdown →
2020256
3
Better, Nicer, Clearer, Fairer: A Critical Assessment of the Movement for Ethical Artificial Intelligence and Machine Learning
Hit paper breakdown →
2019241
4 2015185
5 2015141
6 2018104
7 202193
8 201982
9 202153
10 201551
11 202047
12 201938
13 201936
14 201835
15 202030
16 201824
17 202020
18 201418
19 202017
20 201615

About Luke Stark

Luke Stark is a scholar working on Safety Research, Sociology and Political Science, Human-Computer Interaction, Cognitive Neuroscience and Artificial Intelligence, having authored 41 papers that have together received 2.2k indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (15 papers), Innovative Human-Technology Interaction (10 papers), Privacy, Security, and Data Protection (5 papers), Neuroethics, Human Enhancement, Biomedical Innovations (4 papers), Emotions and Moral Behavior (3 papers), Digital Economy and Work Transformation (3 papers), Digital Mental Health Interventions (3 papers) and Persona Design and Applications (3 papers). The work is most often cited by research in Health Informatics (116 citations), Safety Research (675 citations), Human-Computer Interaction (272 citations), Marketing (429 citations) and Computer Science Applications (130 citations). Luke Stark has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Alex Rosenblat, Anna Lauren Hoffmann, Kate Crawford, Daniel Greene, Jennifer Wortman Vaughan, Michael Madaio, Hanna Wallach, Jesse Hoey, Denise Anthony and Karen Levy. Their work appears in journals such as Ethics and Information Technology, History of the Human Sciences, New Media & Society, Communications of the ACM and Journal of the Association for Information Science and Technology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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