Best Practices for AI and Workplace Assessment Technologies
The Future of Privacy Forum, along with ADP, Indeed, LinkedIn, and Workday — leading hiring and employment software developers — released Best Practices for AI and Workplace Assessment Technologies. The Best Practices guide makes key recommendations for organizations as they develop, deploy, or increasingly rely on artificial intelligence (AI) tools in their hiring and employment decisions. Organizations are incorporating […]
The Spectrum of Artificial Intelligence Report & Infographic
The Spectrum of Artificial Intelligence – Companion to the FPF AI Infographic has been updated in June 2023 to account for the development and use of advanced generative AI tools. In December 2020, FPF published the Spectrum of Artificial Intelligence – An Infographic Tool, designed to visually display the variety and complexity of Artificial Intelligence […]
Generative AI for Organizational Use: Internal Policy Checklist
FPF’s Generative AI for Organizational Use: Internal Policy checklist helps decision-makers revisit their internal policies and procedures. The Checklist provides guidance in four areas:
5 Highlights from FPF’s “AI Out Loud” Expert Panel
On Wed., April 14th, FPF hosted an expert panel discussion on “AI Out Loud: Representation in Data for Voice-Activated Devices, Assistants.” FPF’s Senior Counsel and Director of AI and Ethics, Brenda Leong, moderated the panel featuring Anne Toth, the Director of Alexa Trust, Amazon; Irina Raicu, Internet Ethics Program Director, Markkula Center for Applied Ethics, […]
Warning Signs: The Future of Privacy and Security in an Age of Machine Learning Report
FPF is working with Immuta and others to explain the steps machine learning creators can take to limit the risk that data could be compromised or a system manipulated.
FPF Letter to NY State Legislature
On Friday, June 14, FPF submitted a letter to the New York State Assembly and Senate supporting a well-crafted moratorium on facial recognition systems for security uses in public schools.
Understanding Artificial Intelligence and Machine Learning
The opening session of FPF’s Digital Data Flows Masterclass provided an educational overview of Artificial Intelligence and Machine Learning – featuring Dr. Swati Gupta, Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech; and Dr. Oliver Grau, Chair of ACM’s Europe Technology Policy Committee, Intel Automated Driving Group, […]
The Privacy Expert’s Guide to AI and Machine Learning Report
Today, FPF announces the release of The Privacy Expert’s Guide to AI and Machine Learning. This guide explains the technological basics of AI and ML systems at a level of understanding useful for non-programmers, and addresses certain privacy challenges associated with the implementation of new and existing ML-based products and services.
Policy Brief: European Commission’s Strategy for AI, explained
The European Commission published a Communication on “Artificial Intelligence for Europe” on April 24th 2018. It highlights the transformative nature of AI technology for the world and it calls for the EU to lead the way in the approach of developing AI on a fundamental rights framework. AI for good and for all is the motto the Commission proposes. The Communication could be summed up as announcing concrete funding for research projects, clear social goals and more thinking about everything else.
Unfairness By Algorithm: Distilling the Harms of Automated Decision-Making Report & Infographic
Analysis of personal data can be used to improve services, advance research, and combat discrimination. However, such analysis can also create valid concerns about differential treatment of individuals or harmful impacts on vulnerable communities. These concerns can be amplified when automated decision-making uses sensitive data (such as race, gender, or familial status), impacts protected classes, or affects individuals’ eligibility for housing, employment, or other core services. When seeking to identify harms, it is important to appreciate the context of interactions between individuals, companies, and governments—including the benefits provided by automated decision-making frameworks, and the fallibility of human decision-making.