Although artificial intelligence in health has shown great promise, pressure is mounting for regulators around the world to act, as AI tools demonstrate potentially harmful outcomes.
Copyright: news.mit.edu – “What To Do About AI In health?”
Before a drug is approved by the U.S. Food and Drug Administration (FDA), it must demonstrate both safety and efficacy. However, the FDA does not require an understanding a drug’s mechanism of action for approval. This acceptance of results without explanation raises the question of whether the “black box” decision-making process of a safe and effective artificial intelligence model must be fully explained in order to secure FDA approval.
This topic was one of many discussion points addressed on Monday, Dec. 4 during the MIT Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) AI and Health Regulatory Policy Conference, which ignited a series of discussions and debates amongst faculty; regulators from the United States, EU, and Nigeria; and industry experts concerning the regulation of AI in health.
As machine learning continues to evolve rapidly, uncertainty persists as to whether regulators can keep up and still reduce the likelihood of harmful impact while ensuring that their respective countries remain competitive in innovation. To promote an environment of frank and open discussion, the Jameel Clinic event’s attendance was highly curated for an audience of 100 attendees debating through the enforcement of the Chatham House Rule, to allow speakers anonymity for discussing controversial opinions and arguments without being identified as the source.
Rather than hosting an event to generate buzz around AI in health, the Jameel Clinic’s goal was to create a space to keep regulators apprised of the most cutting-edge advancements in AI, while allowing faculty and industry experts to propose new or different approaches to regulatory frameworks for AI in health, especially for AI use in clinical settings and in drug development.[…]
Read more: www.news.mit.edu
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