Mike O'Neill's Profile
Thanks for sharing, Alex. I agree on the potential to harness data for good in operating efficiently and reducing waste, and think that having human interpretation of the results would be a best practice for both operational and clinical use cases. The notion of malpractice is an interesting one when it comes to using AI for clinical decisions. If the decision rights remain with the clinician, I think it make sense for them to remain the responsible party.. if the decision is made between alternatives presented from an AI algorithm, however, a clinician may not have the opportunity to even make the right choice if the algorithm is buggy or doesn’t work as expected.
Thanks for sharing, really enjoyed reading this. It’s hard to determine the long-term effects on patient health and I think that’s a very valid point to raise considering medical devices can theoretically stay with a person for the rest of their life. I think Alex raises good points above, so I’ll look at the second question you raise re: effects on global health and systems. The trade-off, or lack of a trade-off in this case, between cost and customization is one of the great benefits to 3-D printing. An additional benefit that I hope can arise out of this megatrend is the idea of on-site production of these devices in locations in cities and remote areas. Having access to this type of technology without burdening smaller hospitals with high-cost inventory (a lot of implants, etc. are sold in kits because size is unknown until the patient is identified) could be a game-changer both in China and in the rest of the world.
Agree with you here, Jackson…
Thanks for sharing, Ennis.. really enjoyed this article. Having used sites like Coursera/Edx in the past before, I can’t help but echo Jackson’s concerns re: content development and competition from larger educational brands. It’ll also be interesting to see if any of these groups go “downstream” a bit and try to win in the middle-school / early high-school age ranges. It seems like in many cases the “lowest-level” of content is for AP courses, but the opportunity to disrupt the way younger students learn is one of the more interesting, relatively un-touched parts of the education system/ed-tech out there. Can “open innovation” at companies like General Assembly create a suitable course-load for this age range, or is it better sticking to the secondary/post-secondary/professional development stages of learning?
Thanks for sharing, this is very interesting and a great use-case for 3-D printing! I agree that investing in local talent to become users of the technology would be very valuable in expanding the company’s reach. One of the prime benefits of additive manufacturing is the fact that in many cases it enables manufacturing to become almost hyper-localized (on a small scale). It will be interesting to see how the Field Ready team tries to scale / help with more humanitarian need for high volumes / large items as your essay states… perhaps they can start out as a more niche offering and then try to build a more robust manufacturing presence either organically or through partnership in a few key locations? Regardless of what they do, this is a great use of additive manufacturing and I’m happy to read about the positive impact made due to this megatrend!
Enjoyed reading this, it’s always good to learn more about something like Netflix that I spend more time than I’d like to admit using! As for your questions on positive bias and potential racial bias, I definitely I think it could be a problem. It would be interesting to see how recommendations differed by state or country to see if there are any trends in the recommendations. Also, there is a bit of a “build on your winners” type of strategy going on here that probably does play a role in helping the company differentiate even its own offerings to customers. There is so much new content – both original and licensed – dropping almost daily at Netflix that the recommendation tool helps guide viewership, but it does make me around whether the company pushes shows they invest more heavily in than those that are more low-budget as well. It’s sort of like other social media where one can live in a bit of a silo and the machine learning at Netflix may do nothing to push the boundaries of what an individual consumes.