mlsanityData to 7 Oct 2026

BLIP: Facilitating the Exploration of Undesirable Consequences of Digital Technologies

arXiv 2405.06783 ↗First posted 10 May 2024cs.HC cs.AI cs.CYcited by 6

Not on the map. Why?

Abstract (arXiv)

Digital technologies have positively transformed society, but they have also led to undesirable consequences not anticipated at the time of design or development. We posit that insights into past undesirable consequences can help researchers and practitioners gain awareness and anticipate potential adverse effects. To test this assumption, we introduce BLIP, a system that extracts real-world undesirable consequences of technology from online articles, summarizes and categorizes them, and presents them in an interactive, web-based interface. In two user studies with 15 researchers in various computer science disciplines, we found that BLIP substantially increased the number and diversity of undesirable consequences they could list in comparison to relying on prior knowledge or searching online. Moreover, BLIP helped them identify undesirable consequences relevant to their ongoing projects, made them aware of undesirable consequences they "had never considered," and inspired them to reflect on their own experiences with technology.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 33 of its 122 references that are in the map. First posted on arXiv 10 May 2024.

Builds on

33 of 122 references.

References · 33

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  3. 2019The Curious Case of Neural Text Degenerationcited by 2,881
  4. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
  5. 2017Billion-scale similarity search with GPUscited by 2,477
  6. 2018Datasheets for Datasetscited by 1,371
  7. 2018Model Cards for Model Reportingcited by 1,068
  8. 2020On Faithfulness and Factuality in Abstractive Summarizationcited by 895
  9. 2023Benchmarking Large Language Models for News Summarizationcited by 444
  10. 2022Social Simulacra: Creating Populated Prototypes for Social Computing Systemscited by 300
  11. 2019The What-If Tool: Interactive Probing of Machine Learning Modelscited by 207
  12. 2019Fine-Grained Analysis of Propaganda in News Articlescited by 130
21 more
  1. 2021Decontextualization: Making Sentences Stand-Alonecited by 101
  2. 2020Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Databasecited by 95
  3. 2019FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learningcited by 93
  4. 2023NLPositionality: Characterizing Design Biases of Datasets and Modelscited by 91
  5. 2018Modeling Naive Psychology of Characters in Simple Commonsense Storiescited by 59
  6. 2021Changing the World by Changing the Datacited by 51
  7. 2023AHA!: Facilitating AI Impact Assessment by Generating Examples of Harmscited by 26
  8. 2020Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberationcited by 24
  9. 2022Paper Plain: Making Medical Research Papers Approachable to Healthcare Consumers with Natural Language Processingcited by 23
  10. 2021Unpacking the Expressed Consequences of AI Research in Broader Impact Statementscited by 22
  11. 2022Threddy: An Interactive System for Personalized Thread-based Exploration and Organization of Scientific Literaturecited by 21
  12. 2021Ethics Sheets for AI Taskscited by 18
  13. 2021AI Ethics Statements -- Analysis and lessons learnt from NeurIPS Broader Impact Statementscited by 16
  14. 2021It's Time to Do Something: Mitigating the Negative Impacts of Computing Through a Change to the Peer Review Processcited by 11
  15. 2023Auditing Cross-Cultural Consistency of Human-Annotated Labels for Recommendation Systemscited by 9
  16. 2020Anticipatory Ethics and the Role of Uncertaintycited by 8
  17. 2023"That's important, but...": How Computer Science Researchers Anticipate Unintended Consequences of Their Research Innovationscited by 8
  18. 2022Fuse: In-Situ Sensemaking Support in the Browsercited by 6
  19. 2020Like a Researcher Stating Broader Impact For the Very First Timecited by 5
  20. 2023Anticipating Unintended Consequences of Technology Using Insights from Creativity Support Toolscited by 1
  21. 2023The Case for Anticipating Undesirable Consequences of Computing Innovations Early, Often, and Across Computer Sciencecited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 3; 2026: 1.

6 papers.