A planning committee of the National Academies of Sciences, Engineering, and Medicine will organize and host a 1.5-day public workshop that will examine the current and potential future uses of Artificial Intelligence (AI) in cancer care, and ways to anticipate and address challenges related to integration of these technologies in the care of patients with cancer. With a focus on the responsible and effective use of AI in oncology, the workshop will consider current policy initiatives across healthcare and the unique needs for oncology care. Presentations and discussions at the workshop may include:

• The current state and future applications of AI in oncology care: the different types of AI and their application in current care and their future potential (e.g., AI biomarkers, treatment planning and clinical decision support systems, facilitating clinical efficiencies, product discovery, data curation, clinical evidence generation).
• Existing policies and policy gaps for rigorous and transparent assessment of data sets, training and validation, clinical validation, safety, and effectiveness of tools; for implementing new tools; and for monitoring use and performance, both for individual AI-based tools and within the global context of health care delivery.
• Ethical and legal challenges such as data security and patient privacy, algorithmic bias and drift, liability in AI-driven decisions, implications of autonomous decision-making tools, impact on access to care, transparency in the selection of training data, the models and objective functions used in training the data, code development and tool output, the role of AI in clinical decision-making for patients and clinicians, and intellectual property.
• Potential future challenges such as accuracy of AI output in the setting of rapidly changing evidence and clinical practice guidelines, increasing autonomy of AI systems, integration with other advanced technologies (e.g., genomics), and the need for adaptable policies that can evolve with rapid technological changes.
• Ways to engage key participants in dialogue and policy formulation, including patients, AI developers, healthcare providers, ethicists, legal experts, and industry leaders.
• Data governance for responsible use of patient data in AI systems, such as data anonymization, patient consent, data sharing practices, and accountability for data misuse.
• Educational and training initiatives on AI literacy to support effective utilization and interpretation of AI-generated insights by healthcare professionals, and to help patients understand how AI might influence their care.

The planning committee will develop the agenda for the workshop sessions, select and invite speakers and discussants, and moderate the discussions. A proceedings of the presentations and discussions at the workshop will be prepared by a designated rapporteur in accordance with institutional guidelines.