#AI #DataSets #AIEthics: The Google memo points to the dawning realization that improvements in AI will require putting a lot more care and thought into how data is collected and curated. Even OpenAI, which relies on gargantuan datasets to make its products, is now pointing to this issue. A close engagement with datasets has been deeply undervalued in the AI field, and this neglect has had serious consequences downstream, from technical failures to human rights violations.

This is why investigating datasets is so important. Not because companies want an edge in the current AI wars, but to understand the ideologies, viewpoints, and harms that are being ingested, concentrated, and reproduced by AI systems. The new internet-scale datasets require new investigative methods, new research questions. What political and cultural inflections are baked into training sets? Who and what is represented? What is rendered invisible and unintelligible? Who profits from all this data, and at whose expense? What legal issues does the mass extraction of data raise for copyright, privacy, moral rights, and the right to publicity? What about the people whose creative work and livelihoods are impacted? How could these practices change? And as the accelerating machines of scrape-generate-publish-repeat begin to ingest their own material, what logics, perspectives, and aesthetics will be reinforced in this recursive loop?"

https://knowingmachines.org/9-ways-to-see/9-ways-to-see-a-dataset