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[…] The homepage displays the latest activity from not only your current working group communities, but all FPF communities you are able to join. In the center activity feed, you will see recent community discussions, announcements, library resources, and event details. Use the filter feature in the right corner of the activity feed to switch […]

This Preview highlights key findings from FPF’s forthcoming report “2025 U.S. State AI Legislation: An Examination of State Approaches to AI,” which provides a data-driven snapshot of enacted and key AI bills affecting the private sector, organizes activity into distinct approaches, and helps stakeholders understand emerging trends and obligations. As AI technologies rapidly integrate […]

[…] prominence to certain results, based on general consumer data or specific customer behavioral data. This could potentially include changing the prominence of given products based on their price. This resource distinguishes between these different pricing strategies in order to help lawmakers, businesses, and consumers better understand how these different practices work. View the resource here

[…] that often look different from one another, create different benefits for consumers and companies, and carry different risks. Distinguishing and disaggregating these pricing strategies will help policymakers, businesses, and consumers better understand how the relevant technologies and practices work, and better analyze the relevant benefits and risks. The chart below describes the major different […]

A significant new chapter for data privacy protections in the United States has commenced as more than twenty recently enacted significant state privacy laws have taken effect by July 1, 2025. To assist stakeholders in tracking the emerging state privacy landscape, the Future of Privacy Forum has prepared a resource listing key dates for state […]

[…] fo r Bro ad Sta te Priv a cy La w s As of Ju ly 10 , 20 25 N ote : La w s are org an iz e d ch ro no lo g ic a lly by eff ectiv e date s, no t by sta te (h e nce […]

[…] tools were not designed with older adults or caregiving relationships in mind, and few provide clear information about how AI is used or how sensitive personal data feeds into machine learning systems. Without frameworks for trustworthiness and subsequent trust from older adults and caregivers, the gap between innovation and accountability will continue to grow, […]

Cross-border data flows are critical to Africa’s digital economy, enabling trade, innovation, and access to continental and global markets. As the drive towards data-driven technologies among businesses and governments grows, the ability to transfer personal data across borders efficiently and securely has become a key policy concern on the continent, a position echoed by […]

[…] script and configuration files form a neural network.  There are two essential stages to model training. The first stage is tokenisation. This is when training data is broken down into smaller units (i.e. segmented) and converted into tokens. For now, think of each token as representing a word (we will discuss subword tokenisation later). […]