Events
Critical AI’s main focal point for Fall 2021 is our Ethics of Data Curation workshop (to be held over Zoom), the product of a National Endowment for the Humanities and Rutgers Global sponsored international collaboration between Rutgers and the Australian National University. The lead organizers for the series are Katherine Bode and Baden Pailthorpe at ANU and Lauren M.E. Goodlad at Rutgers. All of the workshops and associated talks are free and open to the public but space is limited so please register well in advance (see schedule and registration links below).
“Artificial Intelligence” (AI) today centers on the technological affordances of data-centric machine learning. While talk of making AI ethical, democratic, human-centered, and inclusive abounds, it suffers from lack of interdisciplinary collaboration and public understanding.
At the heart of AI’s social impact is the determinative power of data:
the leading technologies derive their “intelligence” from mining huge troves of data (often the product of unconsented surveillance) through opaque and resource-intensive computation.
The Big Tech tendency to favor ever-larger models that use data “scraped” from the internet creates complications of many kinds including
the under-presentation of women, people of color, and people in the developing world;
the mistaken belief that stochastic text-generating software like GPT-3 truly “understands” natural language;
the misguided haste to uphold this technology as the “foundation” on which the future of all AI will be built;
and the environmental and social impact of privileging ever-larger models that emit tons of carbon and cost millions of dollars to train.
Our Ethics of Data Curation workshop invites you to join a network of cross-disciplinary scholars including leading thinkers on the question of data curation and data-centric machine learning technologies. Please join the discussion, or if the time doesn’t work for you, watch the recordings of our workshop meetings and join us on Critical AI’s blog for asynchronous conversations.
Note: at present we are still organizing the details of various sessions, including the readings, but if you register in advance we will be certain to email you as soon as the links to readings are live!
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SCHEDULE AND REGISTRATION LINKS
Meeting 1: STOCHASTIC PARROTS:
A comprehensive discussion of the social and technological dimensions of large language models (LLMS).
Th Oct. 7, 2021 at 5:30 PM EST (Oct. 8, 8:30 AM AEDT)
- Co-facilitators: Katherine Bode (Data-Rich Literary History, ANU) and Matthew Stone (Computer Science, Rutgers)
- Primary Reading: Emily M. Bender, Timnit Gebru et al. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big??”
- Check out the video and Lauren Goodlad’s blog of this event!
Suggested Further Readings:
- Thompson, Greenewald, Lee, Manso: “Deep Learning’s Diminishing Returns” (2021)
- Dodge, Sap, Marasović, et al.: “Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus” (2021)
- Abid, Farooqi, and Zou: “Persistent Anti-Muslim Bias in Large Language Models” (2021)
- Myers: “Rooting Out Anti-Muslim Bias in Popular Language Model GTP-3” (2021)
- Welble, Glaese, and Uesato: “Challenges in Detoxifying Language Models” (2021)
- (Watch) Emily M. Bender’s keynote at the Alan Turing Institute (2021)
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Meeting 2: DATA JOURNALISM:
A talk and discussion with Meredith Broussard, Research Director at the NYU Alliance for Public Interest Technology and author of the award-winning book, Artificial Unintelligence: How Computers Misunderstand the World (MIT, 2018).
Th Oct. 14, 2021 at 5:30 PM EST (Oct. 15, 8:30 AM AEDT)
- Professor Broussard will be introduced by Caitlin Petre (Journalism and Media Studies, Rutgers).
- Readings: Chapter 4 and Chapter 6 of Artificial Unintelligence: How Computers Misunderstand the World (MIT, 2018).
- Check out the video and Rutgers Undergraduate Nidhi Salian’s blog of this event!
Suggested Further Readings:
- Chapters 1-3 of Artificial Unintelligence: How Computers Misunderstand the World (MIT, 2018).
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Meeting 3: BIG DATA:
A workshop discussion about two recent publications of importance to data curation and its discontents.
Th Oct. 28, 2021 at 5:30 PM EST (Oct. 29, 8:30 AM AEDT)
- Co-facilitators: Ella Barclay (Design and Digital Media, ANU) and Britt Paris (Critical Informatics, Rutgers)
- Primary Readings: Chapter 2 of Catherine D’Ignazio and Lauren Klein’s Data Feminism and Emily Denton, Alex Hanna, et al.’s “On the Genealogy of Machine Learning Datasets.”
- Look out for guest blogger Ryan Heuser’s blog after the event.
Suggested Further Readings:
- Chapter 1 of Catherine D’Ignazio and Lauren Klein’s Data Feminism
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Meeting 4: DATA RELATIONALITIES:
A talk and discussion with Salomé Viljoen (Columbia Law) on her pioneering work on the relationality of data.
Th Nov 11, 2021 at 5:30 EST (Nov 12, 9:30 AM AEDT)
- Professor Viljoen will be introduced by Michele Gilman (Venable Professor of Law, University of Baltimore).
- Primary Readings: “Data as Property?” (2020)
- NEW: Check out the video and Kayvon Paul’s blog of this event!
Suggested Further Readings:
- Viljoen: “Democratic Data: A Relational Theory of Data Governance” (2020)
- (Watch) Tech Conversation Series—Democratic data: privacy harms and data governance (2021)
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Meeting 5: DATA JUSTICE:
An interview and open discussion with Sasha Costanza-Chock (Director of Research & Design, Algorithmic Justice League) including Kate Henne (School of Regulation and Global Governance, ANU), Sabelo Mhlambi (Berkman-Klein Center for Internet & Society), and Anand Sarwate (Electrical & Computer Engineering, Rutgers).
Th Dec. 2, 2021 at 5:30 PM EST (Dec. 3, 9:30 AM AEDT)
Registration for Sasha Constanza-Chock’s talk at 5:30
Registration for the workshop discussion to follow
Primary Readings:
- From Design Justice: Community-Led Practices to Build the Worlds We Need (2020)
- Introduction: “#TravelingWhileTrans, Design Justice, and Escape from the Matrix of Domination.”
- Ch.2 “Design Practices: Nothing About Us Without Us”
- Look out for guest blogger Jonathan Calzada’s blog after the event.
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Meeting 6: IMAGE DATASETS:
A special event on AI & the Arts with Katrina Sluis (Photograph and Media Arts, ANU) and Nicolas Malevé (Visual Artist and Researcher, CSNI). Both will be introduced by Baden Pailthorpe (School of Art & Design, ANU).
Th Dec. 16, 2021 at 5:30 PM EST (Dec. 17, 9:30 AM AEDT)
Registration for the talk at 5:30
Registration for the workshop discussion to follow
Primary Readings:
- Katrina Sluis’s Photography must be Curated! Park 4: Survival of the Fittest Image (2019)
- Nicolas Malevé’s On the Dataset’s Ruins (2020).
- Save the Date! Emily M. Bender will be joining us on March 24, 2022 as our workshop continues on the related theme, Data Ontologies.
Suggested Further Readings:
- Fei-Fei Li: Where Did ImageNet Come From? An invited talk given to the public on the 10th Anniversary of the Dataset at The Photographers’ Gallery, London (2019)
- Fei-Fei Li: Large-scale Image Classification: ImageNet and ObjectBank, a Google Tech talk given to computer scientists (2011)
- Exhibiting Imagenet at The Photographers’ Gallery (2019), includes a link to a 12 hr YouTube feed of ImageNet organised by synset
- Commissioned texts by artists and writers relating to Data/Set/Match programme at The Photographers’ Gallery (2019-2020) at Unthinking Photography
- Look out for ANU undergraduate blogger Madeleine Hepner’s blog after the event.
- Save the Date! Emily M. Bender will be joining us on March 24, 2022 as our workshop continues on the related theme, Data Ontologies.
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