Sept 27, Matthew Holt
The new Supreme Court, in all likelihood including just nominated Justice Amy Coney Barrett, will be hearing the California v Texas suit against the ACA on November 10th, seven days after the election. There is nothing the Democrats can realistically do to prevent Barrett filling RBG’s seat on the court, but assuming Biden wins and the Democrats take back the Senate, the incoming Administration can give the Supremes something to think about regarding the ACA. I would not suggest this level of confrontation before the election but, if Biden wins, the gloves must come off. Assuming he wins and that the Dems win the Senate, this is the speech Biden should give on November 9th. (The TL:DR spoiler is, “Keep the ACA or I’ll extend Medicare to all ages”)
Sept 28, Hayward Zwerling
Do physicians have an obligation to discuss the political ramifications of science with their patients? While politics has become hyperpolarized, most patients still believe their physicians tell the truth about science and medicine; thus physicians are in a unique position to educate their patients about the ramifications of science. Every day physicians teach their patients the scientific truths they must understand to enable them to make informed healthcare decisions. Is it not also a physician’s responsibility to teach their patients the science underlying relevant public health policy and explain that there is a linear connection between political choices, public health policies, and their health and longevity?
Sept 29, Kim Bellard
You may have missed it, but the Association for the Advancement of Artificial Intelligence (AAAI) just announced its first annual Squirrel AI award winner: Regina Barzilay, a professor at MIT’s Computer Science and Artificial Intelligence Laboratory. The difficulty with AI, though, is that we may not always understand why the AI mde the decisions it did. Barzilay firmly believes, though, that we can’t wait for “the perfect AI,” one we fully understand and that will always be right; we just have to figure out “how to use its strengths and avoid its weaknesses. To really make AI succeed in healthcare, we’re going to have to make radical changes in how we view data, and in how we approach mistakes.