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Non clickbait headline: Medicine has some data collection biases (if your aim is to represent US demographics). Long existing non-ML methods suffer due to this
by jjcon 6y ago
Non clickbait headline: Medicine has some data collection biases (if your aim is to represent US demographics).
Long existing non-ML methods suffer due to this data collection bias but again for some reason the author seems to put AI in a special mysterious place on a pedestal. They use innuendo and anecdote to make assertions without evidence to back them up as systemic problems unique to AI. Innovation will never happen if new technology has to perform perfectly, it only has to perform better than existing methods.
- BadInformatics 6y agoI'm of two minds about this article. It does a reasonable job of enumerating the issues with naively deploying ML in a healthcare setting. However, these articles are becoming a dime a dozen and there is little actionable talk on how to discover or mitigate these issues at a level that practitioners can use. To your point about the bar for new tech, I agree that singling out AI/ML is a cheap shot and more speculative FUD without concrete evidence. That said, we have seen no shortage of hucksters and self-aggrandizing members of the "move fast and break things crowd" trying to treat medicine as a beginner-level Kaggle challenge. This has become particularly egregious and noticeable during the pandemic [1]. The respective lack of medical and technical literacy among programmers/"data scientists" and healthcare providers/admins is just more fuel for the fire. [1] https://www.reddit.com/r/MachineLearning/comments/fni5ow/d_why_is_the_ai_hype_absolutely_bonkers/ https://www.reddit.com/r/MachineLearning/comments/fni5ow/d_w...