TLDR: Johns Hopkins University is hosting an information session for congressional staffers to provide a deep understanding of artificial intelligence, its applications, and the complex policy issues surrounding its regulation, including ethics, bias, and intellectual property. Experts from various AI fields will present to help guide informed decision-making in Congress.
Johns Hopkins University is proactively engaging with U.S. policymakers by hosting an information session designed to equip congressional staffers with a comprehensive understanding of artificial intelligence (AI) and its far-reaching implications. The initiative, organized by Johns Hopkins faculty members, aims to bridge the knowledge gap between cutting-edge AI research and legislative decision-making.
Brian Caffo, a professor of biostatistics at the Bloomberg School of Public Health and director of academic programs at the Johns Hopkins Data Science and AI Institute, is a key organizer of the session. Caffo, whose own research involves extensive use of AI and machine learning in neuroscience and neuroimaging, emphasizes the public service aspect of this educational endeavor. The goal is to connect congressional staff with leading AI researchers who approach the field from diverse perspectives.
The session will feature a diverse lineup of experts. For instance, Liz Chin, a colleague of Caffo’s from Biostatistics, will delve into the critical topic of AI ethics, including its applications and potential biases within systems like the carceral system. Mark Dredze, an expert in AI for speech and language, will discuss advancements in areas such as large language models like ChatGPT. Haris Sair will provide insights into AI’s significant impact on radiology, a medical field experiencing substantial transformation due to AI.
Key policy issues highlighted for discussion include the ethical deployment of AI, particularly concerning its use in areas like sentencing and bail determination, and the challenge of ensuring AI models do not perpetuate existing biases present in data. Intellectual property rights related to AI are also a core component of the discussions. Caffo underscores that AI policy is a ‘high-dimensional problem’ requiring a multitude of angles and opinions, making a multi-disciplinary session crucial for effective policymaking.
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The university’s effort underscores the growing recognition among lawmakers of AI’s potential to reshape nearly every sector and the urgent need to consider how—or if—to regulate this rapidly evolving technology. By providing data, resources, and expert insights, Johns Hopkins aims to empower policymakers to make informed decisions that will guide the future of AI governance in the United States.
