REGISTER HERE Numerous AI documentation processes and practices have been developed in recent years, with goals including improving transparency, safety, fairness, and accountability for the development and uses of AI systems. Well known AI documentation standards include Google’s Model Cards, Microsoft’s Datasheets for Datasets, IBM’s FactSheets, and more recently Meta’s…
“Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems,” a new report by a team of researchers affiliated with the UC Berkeley Center for Long-Term Cybersecurity’s Artificial Intelligence Security Initiative (AISI), examines potential benefits and challenges related to reinforcement learning, and provides recommendations to help policymakers ensure that RL-based systems are deployed safely and responsibly.
The UC Berkeley Center for Long-Term Cybersecurity (CLTC) is proud to announce the recipients of our 2021 research grants. In total, 15 different student-led research groups have been awarded grants to support initiatives related to digital security issues emerging at the intersection of technology and society. Three of the projects were jointly funded with the UC Berkeley Center for Technology, Society & Policy, a multi-disciplinary research center focused on emergent social and policy issues of technology.
On December 10, the Center for Long-Term Cybersecurity hosted the third event in our 2020 Research Exchange, a series of three virtual conferences that showcased CLTC-funded researchers working across a wide spectrum of cybersecurity-related topics. The December event, themed “Long-Term Security Implications of AI/ML Systems.” featured talks from a…
Countries and corporations around the world are vying for leadership in AI development and use, prompting widespread discussions of an “AI arms race” or “race to the bottom” in AI safety. But the competitive development of AI will take place across multiple industries and among very different sets of actors,…
The Center for Long-Term Cybersecurity has issued a new report that assesses how competitive pressures have affected the speed and character of artificial intelligence (AI) research and development in an industry with a history of extensive automation and impressive safety performance: aviation. The Flight to Safety-Critical AI: Lessons in AI…
“Decision Points in AI Governance” takes an in-depth look at recent efforts to translate artificial intelligence (AI) principles into practice. Authored by CLTC Research Fellow and AI Security Initiative (AISI) Program Lead Jessica Cussins Newman, the report provides an overview of 35 efforts already under way to implement AI principles, and highlights three recent efforts as case studies.
In a recent paper, “Artificial Intelligence Ethics in Practice,” published in ;login:, the USENIX Magazine, Jessica Cussins Newman, Research Fellow at CLTC and Program Director for the AI Security Initiative, together with Rajvardhan Oak, a graduate researcher at CLTC, described some of the key ethical challenges associated with artificial intelligence.
On February 19, 2020 the AI Security Initiative at the Center for Long-Term Cybersecurity (CLTC) hosted a lunchtime seminar featuring Bin Yu, Chancellor’s Professor in the Departments of Statistics and Electrical Engineering & Computer Science at UC Berkeley. CLTC’s AI Security Initiative (AISI) works across technical, institutional, and policy domains…
CLTC has launched a new series of “explainer videos” to break down complex cybersecurity-related topics for a lay audience. The first of these videos focuses on “adversarial machine learning,” when AI systems can be deceived (by attackers or “adversaries”) into making incorrect assessments. An adversarial attack might entail…