Health Data Ethics

In this episode I talk with Jack Stock, Senior IT BRM at Cleveland Clinic, about changes he's seen in the field over his career. Jack also shares some sage advice for BRM programs looking to mature.

In this episode, I talk about Hacking Healthcare, a recent read by Tom Lawry. We're going to digest his thoughts on AI-driven leadership in healthcare, thinking about "value" and "shareholders" a little differently, and encourage a tolerance for learning systems.

In this episode Erik Swanson and I dig in on #ai and #analytics in health systems. Erik shares his expertise on choosing problems and good KPIs rather than being swayed by a cool solution, as well as focusing on the science of #healthcare delivery.

In this episode I interview collaborator, AI master, and book-recommender extraordinaire Jasbir Kooner. We talk about her experiences with gender bias in STEM, and I ask for her advice for all folks in STEM who want a more equal playing field. Books referenced: Good Guys: How Men Can Be Better Allies for Women in the Workplace, by David G Smith Invisible Women: Data Bias in a World Designed for Men, by Caroline Criado Perez The End of Bias, A Beginning: The Science and Practice of Overcoming Unconscious Bias, by Jessica Nordell

In this episode, I cover AMA's recent report on the Future of Health, in which they summarize the current #ai landscape, and argue persuasively for the use of "augmented intelligence" rather than "artificial intelligence." They close with stats on the desire of physician stakeholders to be involved early and often in AI use case definition, evaluation, and implementation. Report: https://www.ama-assn.org/system/files/future-health-augmented-intelligence-health-care.pdf

In this episode, I discuss my attempts to learn about business strategy. I use both a classic history of business strategy and a recent financial report on the healthcare sector to probe whether AI is good for hospital business. Book: https://www.goodreads.com/en/book/show/6214316 Report: https://www.kaufmanhall.com/sites/default/files/2024-02/KH%20-%20NHFR%20%282024-02%29_FINAL.pdf

In this week's episode I talk about a recent article about trust in genAI. I started listening to a fascinating podcast with Yann LeCun about the consolidation of AI in just a few companies. For a healthcare system, there are interesting tensions between the desire to work with a Microsoft or a Google, a smaller start up, and the urge to build ai expertise in house - all while keeping patient outcomes as highest priority. It's a good one. I hope you'll take a listen. Article: https://www.linkedin.com/pulse/trust-generative-ai-plummeting-michael-spencer-vfwxc/ Podcast: https://youtu.be/5t1vTLU7s40 Paper: Haring, M., Freigang, F., Amelung, V. et al. What can healthcare systems learn from looking at tensions in innovation processes? A systematic literature review. BMC Health Serv Res 22, 1299 (2022). DOI: 10.1186/s12913-022-08626-7

In this week's episode, I review The Worlds I See by Fei-Fei Li - a delightful, creative, warm portrait of both the emergence of artificial intelligence from its intellectual winter, and Fei-Fei's own life story. I talk about creativity and science, and about using approaches from multiple disciplines to think about AI problems.

In this week's podcast episode - I summarize thinking and learning so far on how to evaluate an ai tool in the healthcare space. I talk about using AI to do things that AI does well and humans do poorly.

In this week's Health Data Ethics podcast episode, I talk about healthcare-specific methods of evaluating LLM output - a recent paper on HumanELY, a web tool for evaluating LLM output across five separate axes, is a great lens for thinking about your ai tools. I also discuss a recent evaluation of GPT-4 Vision in which our AI friend ends up with the right answer to a medical case but can't quite tell us why.

In this episode I review The Code Breaker, a biography of Jennifer Doudna by Walter Isaacson. I talk about previous moral panics about new technology (recombinant DNA!) and compare with artificial intelligence today.

In this episode of the Health Data Ethics podcast I dive into a recent paper in Lancet Digital Health about GPT-4 perpetuating racial and gender biases when asked to diagnose patients. After a victory lap, we settle in to talk about what this means for the use of LLMs as a diagnostic tool and what healthcare teams might want to consider if they implement this technology.

In this episode I begin laying out a framework for how to evaluate AI tools in the healthcare environment, starting with short vs long term impact, the value of a Super Bowl commercial, and figuring out tasks that AIs are good at.

in this episode I talk about my day job as an IT Business Relationship Manager, and give a hypothetical example of a project that benefits from having a person to speak both "clinician" and "IT" languages.

I'm back with an episode in which I discuss patient attitudes towards human scribes, revisit some 2018 predictions about digital scribes, and make a new recommendation when your healthcare IT group pilots a new digital documentation tool: Publish about it!

In this episode I talk about "objective" data and training AI from a patient perspective as well from a healthcare data perspective.

In my podcast episode this week I talk about a recent article on "skill rot", misattributed Cicero quotes, the total amount of skill being conserved, and more.

In this episode I get a little teary about the Mars Rover while talking through some thoughts on what AI does best and what humans do best.

In this episode I give a brief overview of the blueprint of the AI Bill of Rights set out by the White House and the Office of Science and Technology. We'll be discussing each of these rights in greater detail in the coming episodes. Come along for the ride!

I continue discussing the blueprint for an AI Bill of Rights in this episode centered on safe and effective artificial intelligence in healthcare. I'll discuss a sepsis predictor that did not work as intended, and suggest some specific ways health systems can implement the guidance suggested by OSTP and the White House.