An AI-based computer system can gather data and use that data to make decisions or solve problems – using algorithms to perform tasks that, if done by a human, would be said to require intelligence. The benefits created by AI and machine learning (ML) systems for better health care, safer transportation, and greater efficiencies across the globe are already happening. But the increased amounts of data and computing power that enable sophisticated AI and ML models raise questions about the privacy impacts, ethical consequences, fairness, and real world harms if the systems are not designed and managed responsibly. FPF works with commercial, academic, and civil society supporters and partners to develop best practices for managing risk in AI and ML and assess whether historical data protection practices such as fairness, accountability, and transparency are sufficient to answer the ethical questions they raise.
Let’s Look at LLMs: Understanding Data Flows and Risks in the Workplace
Over the last few months, we have seen generative AI systems and Large Language Models (LLMs), like OpenAI’s ChatGPT, Google Bard, Stable Diffusion, and Dall-E, send shockwaves throughout society. Companies are racing to bake AI features into existing products and roll out new services. Many Americans are worrying whether generative AI and LLMs are going […]
Knowledge is Power: The Future of Privacy Forum launches FPF Training Program
“An investment in knowledge always pays the best interest”–Ben Franklin Let’s make 2023 the year we invest in ourselves, our teams, and the knowledge needed to best navigate this dynamic world of privacy and data protection. I am fortunate to know many of you who will read this blog post, but for those who I […]
Understanding Extended Reality Technology & Data Flows: Privacy and Data Protection Risks and Mitigation Strategies
This post is the second in a two-part series. Click here for FPF’s XR infographic. The first post in this series focuses on the key functions that XR devices may feature, and analyzes the kinds of sensors, data types, data processing, and transfers to other parties that power these functions. I. Introduction Today’s virtual (VR), […]
Understanding Extended Reality Technology & Data Flows: XR Functions
This post is the first in a two-part series on extended reality (XR) technology, providing an overview of the technology and associated privacy and data protection risks. See the bottom of the page for FPF’s infographic, “Understanding Extended Reality Technology & Data Flows.” I. Introduction Today’s virtual (VR), mixed (MR), and augmented (AR) reality environments, […]
New Infographic Highlights XR Technology Data Flows and Privacy Risks
As businesses increasingly develop and adopt extended reality (XR) technologies, including virtual (VR), mixed (MR), and augmented (AR) reality, the urgency to consider potential privacy and data protection risks to users and bystanders grows. Lawmakers, regulators, and other experts are increasingly interested in how XR technologies work, what data protection risks they pose, and what […]
FPF at CPDP LatAm 2022: Artificial Intelligence and Data Protection in Latin America
This summer the first-ever in-person Computers, Privacy and Data Protection Conference – Latin America (CPDP LatAm) took place in Rio de Janeiro on July 12 and 13. The Future of Privacy Forum (FPF) was present at the event, titled Artificial Intelligence and Data Protection in Latin America, participating in two panels and submitting a paper […]
BCI Technical and Policy Recommendations to Mitigate Privacy Risks
This is the final post of a four-part series on Brain-Computer Interfaces (BCIs), providing an overview of the technology, use cases, privacy risks, and proposed recommendations for promoting privacy and mitigating risks associated with BCIs. Click here for FPF and IBM’s full report: Privacy and the Connected Mind. In case you missed them, read the […]
BCI Commercial and Government Use: Gaming, Education, Employment, and More
This post is the third in a four-part series on Brain-Computer Interfaces (BCIs), providing an overview of the technology, use cases, privacy risks, and proposed recommendations for promoting privacy and mitigating risks associated with BCIs. Click here for FPF and IBM’s full report: Privacy and the Connected Mind. In case you missed them, read the […]
BCIs & Data Protection in Healthcare: Data Flows, Risks, and Regulations
This post is the second in a four-part series on Brain-Computer Interfaces (BCIs), providing an overview of the technology, use cases, privacy risks, and proposed recommendations for promoting privacy and mitigating risks associated with BCIs. Click here for FPF and IBM’s full report: Privacy and the Connected Mind. In case you missed it, read the […]
Brain-Computer Interfaces & Data Protection: Understanding the Technology and Data Flows
This post is the first in a four-part series on Brain-Computer Interfaces (BCIs), providing an overview of the technology, use cases, privacy risks, and proposed recommendations for promoting privacy and mitigating risks associated with BCIs. Click here for FPF and IBM’s full report: Privacy and the Connected Mind. Additionally, FPF-curated resources, including policy & regulatory […]