Beyond Failures: Repairing the Future of AI with Public Values
Failures in AI implementations and flawed data practices have not only raised public concern but have also significantly shaped policymaking processes within the EU. Beyond the realm of policymaking, a multitude of repair efforts have emerged to address the shortcomings of failing, inadequate, or poorly designed AI systems. This often involves a reevaluation of governance strategies and a renewal of data practices, fostering the development of AI-related expertise and practices crucial for both informing policy and translating it into effective actions. This panel delves into the practices and commitments aimed at strengthening public values in the realm of AI, drawing on case studies from Finland, the Netherlands, and Italy. The discussed cases span diverse sectors, including media, energy, health, social work, and policymaking, highlighting various dimensions of AI usage. Through this discussion, the panel aims to pinpoint both beneficial and urgently needed ways to support responsible data practices and uses of AI. By fostering a deep dive into these critical issues, the goal is to transcend past shortcomings and transform them into valuable lessons for the future.
• What have AI failures taught us?
• How to design and enforce checks and balances to safeguard that AI practices support public values?
• How do specific local strengths contribute to the development of beneficial AI and data practices, and related policies?
• In what ways can researchers, practitioners, and citizens promote a
Organised by University of Helsinki (FI)
Moderator Iris Muis, Utrecht University (NL)
Speakers Mirko Tobias Schäfer, Data School (NL); Minna Ruckenstein, University of Helsinki (FI); Anni Ojajärvi, Kela - the Social Insurance Institution of Finland (FI); Diletta Huyskes, University of Milan / Privacy Network (IT)