06-19, 09:35–10:15 (Europe/Berlin), Kesselhaus
This talk focuses on unpacking this year’s big buzzwords of “open AI” and “responsible AI” to highlight the range of (sometimes contradictory) activities that exist under these umbrella terms and how
While the majority of AI production is concentrated within a few companies in even fewer countries, alternative pathways are emerging for more people to participate in the process of building, applying, and governing ML models. Open Artificial Intelligence (open AI) initiatives offer new spaces to reimagine how AI is developed and who can be part of the process. However, over the past year, the intensification of AI model development and hype has made the already nebulous term “AI” even more confusing when extended with terms like “open”, “responsible”, “trustworthy”, and “democratic”. This talk focuses on unpacking this year’s big buzzwords of “open AI” and “responsible AI” to highlight the range of (sometimes contradictory) activities that exist under these umbrella terms and how the AI field is expanding the practice of “open” beyond traditional FOSS contexts. Following an overview of the current open and responsible AI landscape, we will end with a discussion on community priorities for focus and intervention to build AI production pipelines that live up to aspirational attributes, like “open.”
Jennifer Ding is a Research Application Manager at The Alan Turing Institute, the UK’s national institute for data science and artificial intelligence. Previously, she was a startup founder and data scientist at several public interest tech companies, creating data products for industry and government partners. She enjoys massaging data big and small, and is co-leading the first ever London Data Week, which takes place 3 -9 July 2023.