When we assess how AI fits within the health sector, two things stand out: first, how healthcare, as the most data-intensive industry on the planet, continually generates exabytes of information with massive potential to fuel AI-driven insight and improvement; and second, how incredibly damaging AI systems might be to patients and healthcare missions if organizations can鈥檛 fully manage risks of algorithmic bias, diagnostic error, and breaches of sensitive data.
Given this complexity and the growing need for a sector-specific approach to responsible AI, 蘑菇视频 Allen has joined the , a diverse community of collaborators dedicated to the idea that health AI systems can be both powerful and transparent, as well as transformative and safe.
鈥淚 am thrilled to welcome 蘑菇视频 Allen Hamilton to our growing community of organizations committed to ensuring responsible health AI for all of us,鈥� shared Brian Anderson, CHAI鈥檚 chief executive officer. 鈥淲e are driven by the expertise and diverse perspectives of our members together with the feedback of our broader health ecosystem and the public. We look forward to working together to unlock the potential benefits of AI, on a foundation of trust and safety.鈥�
CHAI is a vibrant stakeholder ecosystem that brings technology leaders, academic researchers, healthcare organizations, government agencies, and patients together around a shared commitment鈥攖o promote the development, evaluation, adoption, and appropriate use of credible, fair, and ethical health AI.
蘑菇视频 Allen will provide expertise for CHAI鈥檚 focused work to help healthcare organizations better assess, monitor, and implement reporting mechanisms for AI in ways that empower patients and caregivers and improve health outcomes. As the number-one provider of AI services to the U.S. federal government, we鈥檙e excited to contribute to multiple CHAI working groups and projects that are poised to transform today鈥檚 health AI landscape, including, but not limited to:
- Fostering dialog and collaboration across the coalition to enable the identification of vetted best practices, including equity and fairness standards, for the development and deployment of health AI applications
- Defining core principles and criteria for sustaining responsible AI practices to help healthcare organizations, health AI developers, and end users alike balance AI鈥檚 promise and risk throughout the system lifecycle
- Creating and promoting a standard labeling schema to provide a new level of transparency and eliminate the black-box effect to increase the credibility of health AI systems for patients and doctors
- Orchestrating traditional machine learning algorithms along with new generative AI tools to transform how organizations test and evaluate AI
- Identifying practical measurement frameworks to enable leaders to better assess potential use cases and document the results achieved from their health AI programs
Together, initiatives like these will equip an array of healthcare enterprises鈥攆rom academic medical centers and other health systems, to health plans, medical device manufacturers, and biopharma companies鈥攚ith the best practices, measures, and toolkits they need to harness AI for the benefit of patients while safeguarding sensitive data and managing risk.
What underlies this work is a belief that organizations need support to gain a deep understanding of how AI systems are developed and to thoroughly assess potential use cases to feel confident in realizing the mission value of these applications.
Through CHAI, our collaborations with other AI leaders, major tech companies, and industry innovators will generate insights and frameworks that help our clients reliably and ethically enhance their missions with AI applications. Whether it鈥檚 predicting patient outcomes with higher accuracy, streamlining drug discovery, supplementing provider expertise, automating routine administrative tasks, or maximizing resource efficiency, we want to help shape the most responsible way to integrate AI鈥檚 power with health-sector priorities.
