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Greaves, Mark

Publications and source records attributed to Greaves, Mark.

Safety in Artificial Intelligence: Challenges and Opportunities for the U.S. National Labs and Beyond

This report discusses the importance of the critical and underexplored topic of artificial intelligence (AI) safety, as highlighted during the “Strategy Alignment on AI Safety” workshop convened at Lawrence Livermore National Laboratory (LLNL) in April 2024. Through a summary of keynote talks, panel discussions, and breakout sessions, world-leading AI safety experts from academic, industry, national labs, and government agencies clearly agree on the need for and importance of large-scale investments for research and capabilities in AI safety. With the field innovating at unprecedented rates, there is increasing urgency to develop novel evaluation methodologies that allow full considerations of risks/threats of AI technologies in different domains. Quantitative metrics and effective methodologies that can evaluate and audit the “safeness” of how a given AI technology is trained, deployed, or regulated are, at best, nascent for certain scenarios or, more commonly, nonexistent. This maturation gap presents the possibility of serious threats to national security, and further inaction may have serious consequences. Additionally, the gap between the public’s and research community’s perceptions of AI risks/rewards is significant. While numerous voices from the AI community have expressed concern that the risks could be so high that future AI systems could inflict extinction-level damage to humanity if deployed incorrectly, the public largely is aware only of risk in low-impact scenarios. This discrepancy highlights the crucial need for researchers to articulate to governmental bodies what, why, and when various AI risks matter as part of motivating funding requests. Thus, the call to action for this community is to pursue AI safety as a “Big Science” project on a scale comparable to the Manhattan Project. High risks and high payoffs are on the table, but safe AI is a fast-moving target, and large-scale investments are needed to guide development of this technology in a responsible way. We highlight the need for a multilayered solution combining the development of new methods and algorithmic approaches to mitigate threats with an active participation of the government(s) in setting high industry standards and regulations based on state-of-the-art technology. The U.S. Department of Energy (DOE) national laboratories have served as leading institutions for scientific innovation in the U.S. for more than 70 years. Drawing on their expertise in the AI community and their history of safeguarding critical and sensitive information, and as we look to the future, national labs are the best choice for evaluating and safeguarding AI technologies.

97 MATHEMATICS AND COMPUTING↗

Protecting scientific integrity in an age of generative AI

Revolutionary advances in AI have brought us to a transformative moment for science. AI is accelerating scientific discoveries and analyses. At the same time, its tools and processes challenge core norms and values in the conduct of science, including accountability, transparency, replicability, and human responsibility (1–3). These difficulties are particularly apparent in recent advances with generative AI. Future innovations with AI may mitigate some of these or raise new concerns and challenges.

99 GENERAL AND MISCELLANEOUS↗

Defining the Synthetic Biology Supply Chain

In this article, a team of experts in synthetic biology, data analytics, and national security describe the overall supply chain surrounding synthetic biology. The team analyzes selected interactions within that network to better understand the risks raised by synthetic biology and identifies opportunities for risk mitigation. To introduce the concept, the article will briefly describe how an understanding of supply chains has been important in promoting nuclear nonproliferation objectives. The article concludes by assessing the structure and networks identified in the supply chains to reveal potential opportunities for future biodefense research and development; options for additional information exchange; and means to interdict, detect, or deter suspicious activity.

nuclear supply chain↗

Technosocial Predictive Analytics for Security Informatics

Challenges to the security, health, and sustainable growth of our society keep escalating asymmetrically due to the growing pace of globalization and global change. The increasing velocity of information sharing, social networking, economic forces, and environmental change has resulted in a rapid increase in the number and frequency of “game-changing moments” that a community can face. Social movements that once took a decade to build now take a year; shifts in public opinion that once took a year to take root now take a couple of months. More and more frequently, these critical moments occur too suddenly for the affected communities to succeed in countering the consequent adversities or seizing the emerging opportunities. Now more than ever, we need anticipatory reasoning technologies to forecast and manage change in order to secure and improve our way of life and the environment we inhabit.

analytical gaming↗

Human-Centered Design for the Personal Satellite Assistant

The Personal Satellite Assistant (PSA) is a softball-sized flying robot designed to operate autonomously onboard manned spacecraft in pressurized micro-gravity environments. We describe how the Brahms multi-agent modeling and simulation environment in conjunction with a KAoS agent teamwork approach can be used to support human-centered design for the PSA.

Bradshaw, Jeffrey M.↗