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FPF-Sponsorship-Prospectus-Singles-DC-Privacy-Forum
[…] 1 available »Company name and logo included in schedule of events with recognition “Lunch brought to you by [Your company name]” »Company name and logo displayed on signage at Luncheon »Company logo on event webpage with link, located on FPF website »Official recognition of sponsor during the Luncheon by FPF »Opportunity to make short […]
Minding Mindful Machines: AI Agents and Data Protection Considerations
[…] privacy and data protection risks related to the collection and processing of personal information. They also present novel technical challenges related to testing and human oversight, for organizations seeking to develop or deploy AI agents in commercial settings. Specifically, this Issue Brief explores: Part 1: Definitions. While agents are not new, emerging definitions across […]
Minding Mindful Machines_ AI Agents and Data Protection Considerations
[…] A bou t FP F T he Fu tu re of Priv a cy Fo ru m (F P F ) is a no n-p ro fit org an iz a tio n th at se rv e s as a ca ta ly st fo r priv a cy l e ad ers […]
Potential Harms And Mitigation Practices for Automated Decision-making and Generative AI
[…] navigate these issues; however, if developers and deployers of AI tools evaluate their risk mitigation strategies to consider the vast array of potential AI harms, it can promote fairness, encourage responsible data use, and combat discrimination. To facilitate these discussions, the Future of Privacy Forum (FPF) has updated our 2017 resource (“Distilling the Harms […]
Potential Harms And Mitigation Practices for Automated Decision-making and Generative AI
FPF has updated our 2017 resource (“Distilling the Harms of Automated Decision-making”) with the goal of identifying and categorizing a broad range of potential harms that may result from automated decision-making, including heightened harms related to generative AI (GenAI), and potential mitigation practices. FPF reviewed leading books, articles, and other literature on the […]
FPF AI Harms Charts Only R2
[…] patterns Narrowing of Choice for Groups SOCIAL DETRIMENT Network Bubbles E.g. Varied exposure to opportunity or evaluation based on “who you know” Filter Bubbles E.g. Algorithms that promote only familiar news and information Dignitary Harms E.g. Emotional distress due to bias or a decision based on incorrect data Stereotype Reinforcement E.g. Assumption that computed […]
FPF AI Harms R5
[…] navigate these issues; however, if developers and deployers of AI tools evaluate their risk mitigation strategies to consider the vast array of potential AI harms, it can promote fairness, encourage responsible data use, and combat discrimination. To facilitate these discussions, the Future of Privacy Forum (FPF) has updated our 2017 resource (“Distilling the Harms […]
Chatbots in Check: Utah’s Latest AI Legislation
With the close of Utah’s short legislative session, the Beehive State is once again an early mover in U.S. tech policy. In March, Governor Cox signed several bills related to the governance of generative Artificial Intelligence systems into law. Among them, SB 332 and SB 226 amend Utah’s 2024 Artificial Intelligence Policy Act (AIPA) while HB 452 establishes new regulations […]
FPF Publishes Infographic, Readiness Checklist To Support Schools Responding to Deepfakes
FPF released an infographic and readiness checklist to help schools better understand and prepare for the risks posed by deepfakes. Deepfakes are realistic, synthetic media, including images, videos, audio, and text, created using a type of Artificial Intelligence (AI) called deep learning. By manipulating existing media, deepfakes can make it appear as though […]