Join Pacific Northwest National Laboratory at the International Conference on Machine Learning in Seoul, Korea!
Graphic created by Kelly Machart | Pacific Northwest National Laboratory
Seoul, Korea
The 43rd International Conference on Machine Learning (ICML) will feature the latest research from data scientists, computer scientists, and mathematicians at Pacific Northwest National Laboratory (PNNL), who will contribute through a series of papers and posters highlighting the latest breakthroughs in AI and machine learning (ML).
The widely known conference has established itself as one of the fastest-growing AI conferences in the world and as a premier destination for experts to gather and discuss breakthrough research in ML and its related domains, such as AI, statistics, and data science.
Throughout the nearly week-long conference, thought leaders and professionals from a wide range of backgrounds will explore the impact of ML in application areas like machine vision, speech recognition, robotics, and computational biology—ideating on how these advancements can be harnessed to address some of today’s most complex challenges in science and beyond.
Authors: Ted Fujimoto and Jacob Benz
The advancement of AI capabilities compels researchers and the public to be more aware of its potential worldwide impact. A pressing near-term concern is the regulation of military AI applications. Armament manufacturers and defense contractors are increasingly investing in AI capabilities and forging partnerships with AI companies, creating a burgeoning coalition that demands military leaders, arms control diplomacy experts, and AI researchers to collaborate to ensure a safer future. While AI researchers often focus on the long-term implications of super intelligent AI, this approach may not adequately address the immediate challenges posed by AI in military applications. Success requires acknowledging and mitigating the emerging risks of frontier AI models that plan to be applied to defense applications, like military AI systems. Arms control has reduced past catastrophic risks, so lessons learned from nuclear deterrence can guide AI safety and security research toward innovations in verification and diplomacy. AI researchers, however, must assist in leading the technical research that clearly defines and alleviates instability in military settings. Given these new responsibilities and the lack of sufficiently reliable solutions, we argue that AI researchers must take a leading role in advancing arms control research to minimize risk in military AI applications.
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