Toni Witt is on location at the HIMSS23 Global Health Conference and Exhibition, which runs this week in Chicago. In this special “On Location” report, Toni discusses the importance of frameworks as healthcare organizations implement artificial intelligence (AI) and machine learning (ML).
Highlights
00:19 — A unique factor of AI adoption and healthcare is the intense focus on responsible AI development, especially as the healthcare industry handles patient data.
00:36 — A session at HIMSS tackled the question, “How should healthcare organizations think about responsible AI development and how does that differ from other industries?” Toni reports that an attendee brought up the dozens of AI frameworks that can help organizations develop guidelines for AI implementation and questioned why there isn’t a unified framework that can help all organizations in all industries.
01:03 — Toni suggests a possible reason being that AI is advancing too rapidly right now. With the constant development of AI, there are also many governance principles being proposed. As new iterations of AI come out, so do new governance principles which require the models themselves to be reassessed and retained frequently.
01:45 — “The whole ‘let’s just build it and see what happens’ mentality that we have in the startup industry doesn’t exactly apply in healthcare,” Toni raises, taking the iteration process into consideration.
02:20 — The panelists at this session recommended that companies should look across the many existing frameworks, evaluate the similarities and differences, and then make sure the company values align with those guidelines.
02:47 — In the future, there may be a unified principle and unified rubric for developing AI. Although we’re not at that point yet, Toni notes that “it’s definitely not a good idea to wait for that point to happen.”
03:05 — While the discussion around responsible AI is a developing conversation, healthcare organizations can still start applying AI and ML now to save lives.
