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Welcome to our Workshop on Responsible Data!

The development of large-scale datasets has been essential to the progress of machine learning and artificial intelligence. However, many of these datasets are not inclusive or diverse - particularly computer vision datasets, which can lead to biased models and algorithms. This workshop will bring together practitioners and researchers to discuss the challenges and opportunities of building more responsible datasets.

The workshop will cover a range of topics, including:

Post workshop, we plan to write a white paper summarizing the round table discussions and opinions from experts in the field (with necessary permissions). We will also follow through with making a community space on discord (or similar platform) to continue the community building and collaboration post-workshop.

Call for Papers

Authors are invited to submit relevent research (including work in progress, novel perspectives, etc.) as extended abstracts for the poster session and workshop discussion. Please see relevent topics above. Accepted abstracts will be presented at the poster session, and will not be included in the printed proceedings of the workshop.

The extended abstract can be at most 4 pages long in CVPR format, not including references. Authors may supply supplementary material, however, reviewers will not be required to read this material. Reviews will be double blind. The submission deadline is March 31, 2024.

Submit your extended abstracts through OpenReview.

Important Dates

Submission Deadline March 31, 2024 April 12, 2024
Final Decisions April 22, 2024 April 30, 2024


The following schedule is tentative and will be confirmed closer to the workshop:

Time Topic Speaker(s)/Presenter(s)
8:30-8:45 Opening Remarks Dr. Candice Schumann
8:45-9:15 Keynote Dr. Sara Beery
9:15-9:30 Rapid Fire Talks 1 TBD
9:30-10:00 Poster Session 1 TBD
10:00-10:30 Coffee Break  
10:30-11:30 Round Table Discussion 1  
11:30-12:30 Lunch Break  
12:30-13:00 Keynote Dr. William Agnew
13:00-13:15 Rapid Fire Talks 2 TBD
13:15-13:45 Poster Session 2 TBD
13:45-14:15 Coffee Break  
14:15-15:15 Round Table Discussion 2  
15:15-16:15 Panel Discussion Moderator: Dr. Vikram V. Ramaswamy

Panelists: Nati Catalan, Dr. Sven Cattell, Dr. Morgan Klaus Scheuerman, Emily McReynolds
16:15-16:30 Closing Remarks Dr. Caner Hazirbas

Keynote Speakers

Sara Beery
Sara Beery (She/Her)
Assistant Professor
William Agnew
William Agnew
CBI Postdoc Fellow
Dr. Sara Beery is the Homer A. Burnell Career Development Professor in the MIT Faculty of Artificial Intelligence and Decision-Making. She was previously a visiting researcher at Google, working on large-scale urban forest monitoring as part of the Auto Arborist project. She received her PhD in Computing and Mathematical Sciences at Caltech in 2022, where she was advised by Pietro Perona and awarded the Amori Doctoral Prize for her thesis. Her research focuses on building computer vision methods that enable global-scale environmental and biodiversity monitoring across data modalities, tackling real-world challenges including geospatial and temporal domain shift, learning from imperfect data, fine-grained categories, and long-tailed distributions. She partners with industry, nongovernmental organizations, and government agencies to deploy her methods in the wild worldwide. She works toward increasing the diversity and accessibility of academic research in artificial intelligence through interdisciplinary capacity building and education, and has founded the AI for Conservation slack community, serves as the Biodiversity Community Lead for Climate Change AI, and founded and directs the Summer Workshop on Computer Vision Methods for Ecology.

Dr. William Agnew coming soon.


Nati Catalan
Nati Catalan (He/Him)
Sven Cattell
Sven Cattell
Founder of AI Village
Morgan Klaus Scheuerman
Morgan Klaus Scheuerman (He/Him)
Postdoctoral Associate
CU Boulder
Emily McReynolds
Emily McReynolds
Lead AI Strategist
Nati Catalan is a seasoned professional with a background in Computer Science and Mathematics, boasting two decades of leadership in startups and enterprises. Over the past 9 years, Nati has passionately dedicated efforts to bridging the gap between artificial intelligence and human intuition. As the Co-Founder of, Nati champions the cause of incorporating humans in machine learning solutions. Nati is a firm advocate for the essential role of human guidance in responsible AI development, whose challenges he solves with global, diverse, and responsible human input on an unprecedented scale. This approach has positioned a unique platform for Data Science and ML teams, especially those pursuing Responsible AI in an effortless and scalable way.

Sven Cattell coming soon.

Morgan Klaus Scheuerman coming soon.

Emily McReynolds (She/Her) has worked in data protection, machine learning & AI, across academia, civil society, and in the tech industry. In previous roles, she led partnerships with civil society & industry engagement on responsible AI at Meta, and created end-to-end data strategy for ML development at Microsoft. With a passion for translating complex technical concepts into understandable sound bites, she has spearheaded a number of tech explanation projects including AI System Cards, a resource for understanding how AI works in different contexts. She was the founding program director for the University of Washington’s Tech Policy Lab, an interdisciplinary collaboration across the Computer Science, Information, and Law schools. She started coding in the time of HTML and taught people to use computers back when we used floppy disks.


Candice Schumann
Candice Schumann (They/She)
Research Engineer
Google Research
Caner Hazirbas
Caner Hazirbas (He/Him)
Research Scientist
Meta AI
Olga Russakovsky
Olga Russakovsky (She/Her)
Associate Professor, CS
Vikram V. Ramaswamy
Vikram V. Ramaswamy (He/They)
Lecturer, CS
Jerone Andrews
Jerone Andrews (He/Him)
Research Scientist
Sony AI
Alice Xiang
Alice Xiang (She/Her)
Global Head of AI Ethics
Sony AI
Susanna Ricco
Susanna Ricco (She/Her)
Research Engineer
Google Research
Courtney Heldreth
Courtney Heldreth (She/Her)
UX Researcher
Google Research
Biao Wang
Biao Wang (He/Him)
Associate Product Manager
Google Research
Cristian Canton Ferrer
Cristian Canton Ferrer (He/Him)
Head of GenAI Trust & Safety
Meta AI
Jess Holbrook
Jess Holbrook (He/Him)
Director and Principal Researcher, GenAI
Meta AI


Contact the organizers at