Jesse Bendit's Profile

I agree with the other comments that additive manufacturing will be very important in the medical industry and also agree that Stryker should focus on partnerships and thought leadership to continue advancing the technology. These seem like the most cost efficient and impactful ways to improve their product development without requiring their company to spread itself too thin and outside its expertise. You raise a good question about the additional costs of manufacturing through additive manufacturing and I hope that this cost does not slow down the rate of innovation – hopefully researchers and key interest groups are able to separate the short term costs from the long term opportunity to continue investment in the area.

I agree that medical devices is definitely one of the best areas for additive manufacturing in the future – the fact that we can potentially create implants or prosthetics that are made perfectly for the person in need is extremely exciting. I do question your point that there are low barriers to entry and low capital investment requirements – from my understanding, these machines are relatively expensive compared to other forms of manufacturing (especially for smaller companies with less certain cash flows). Also, to perfect the design of given devices likely takes significant investment in the right types of 3D-printers and product design information. However, I agree that the investment should be made since there is such a great opportunity to improve health through AM.

I agree that the government suffers from serious inefficiencies and a lack of creativity when looking at important issues – the more good ideas they get, the better! However, I think that I would prefer to get better talent into government jobs, rather than relying on ideas from the general population – it is difficult to imagine that contributions will not be significantly politically charged (especially concerning difficult issues like Social Security), which would seem to somewhat breakdown the democratic process by potentially shifting decisions away from elected officials. I guess that it depends more on how these ideas are organized, considered, and potentially implemented though and hopefully it could be done in a way that avoids these conflicts because I do think it is important to consider alternative perspectives when looking at difficult issues.

I feel like using OI to get customer preferences might actually have some negative impact in preventing the company from thinking differently and independently. Instead of coming up with new, healthier foods with improved tastes and brand images, Mondelez might instead rely too much on customer response to existing products and become complacent in its own development. I like the fact that the company is encouraging people to contribute to their decisions and product choices, but don’t want this to replace their own industry leadership and innovation. Often consumers unfortunately don’t know best and the company should feel ownership over providing better foods and choices to those consumers.

I have little (no…) background in the military, but I would wonder whether there is enough data (more importantly, enough similar data) for machine learning to properly predict and analyze specific situations. I would be concerned that each situation is so unique that you might risk projecting what happened in the past on what you think might happen in the future, even if there may be a better alternative. I think the more information and data points, the better the predictions will be and hope that continued improvements in technology can help save lives and avoid more challenging conflicts, but would wonder how long it takes to get there and how accurate the information can ever be independently. I agree with your point that the technology should remain as a support to human intelligence rather than replacing it, and am not sure at what point that could potentially change (if ever).

I think this technology is very interesting for addressing an important issue, but I’d be concerned if a person knowing they have Mindstrong on their phone impacts how they use their phone. Similar to your point that individuals act differently in psychological examinations, would they act differently on their phone to impact a potential diagnosis? If so, this could cause the machine learning technology to believe the wrong data is or is not correlated to mental health issues and misdiagnose individuals – I would be concerned about relying too fully on this data as you could miss important diagnoses and negatively impact individuals’ lives.

Also, as you mentioned in the case I think there are a lot of data concern and privacy issues that would come along with this technology, but believe the potential upside (if the data can accurately diagnose) is worth these risks if they are handled correctly.