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This article represents a very interesting perspective on open innovation that combines the sharing economy with healthcare. While the sharing economy has disrupted the transportation industry as well as the hospitality industry (e.g., Uber and AirBnB), healthcare has taken a back seat until recently. [1] Patient health information is highly confidential and has various security concerns, both personal and legal. PLM’s process to de-identify patient information is critical for its operations and each patient’s trust that they will remain anonymous is required for this platform to scale.

While open expression of symptoms may be comforting, I am concerned with certain biases that patients have. For example, when people are not feeling well, they often seek support from their community. In this case, their community could be this online platform that may lead them to think they have certain symptoms or diseases that they, in fact, do not. When patients begin to self-diagnose, the practice of medicine breaks down completely. WebMD sees this with their diagnostic engine, which leads people to believe that they may have horrible diseases when it’s truly a simple cold. Health-based paranoia and hypochondriasis could manifest itself in this platform, which could lead to spreading fear rather than support.

[1] Leaders, O. T. (2017, June 22). Why Now Is The Time For Healthcare To Tap The Sharing Economy. Retrieved from https://hitconsultant.net/2017/06/22/healthcare-sharing-economy/

On November 15, 2018, Hermione commented on Additive Manufacturing in Construction :

Large-scale 3D printing represents an excellent opportunity to create affordable housing options in a short amount of time. I’ve read about 3D printed houses providing temporary relief post natural disasters. I do wonder, however, whether quality and longevity will become problematic in the long-term. How will repairs and updates be made to these homes? Will the 3D printer need to remain in the local area in case the need for replacement walls arises?

While some might be concerned about job replacement within the construction industry, a significant portion of construction jobs are quite risky. Deploying 3D printing could reduce construction-related injuries and even create jobs in supporting roles.

Also, 3D printing allows the construction industry, typically very conservative with respect to innovate, to be on the cutting edge of technological advancement. [1] These advances could help boost productivity across all stages of the design process through a digitization of the entire process.

[1] “Will 3D Printing Remodel the Construction Industry?” https://Www.bcg.com, http://www.bcg.com/en-us/publications/2018/will-3d-printing-remodel-construction-industry.aspx.

On November 15, 2018, Hermione commented on Made In Space. Literally. :

This is an excellent application of additive manufacturing, perfectly positioned in an environment where physical space is limited and the cost to carry supplies is massive. I envision a future world where our recycled materials and waste can be melted down to create the materials used in 3D printing. This would allow for essentially any product to be printed assuming we had the materials through the recycling program (e.g., plastics, metals).

While it common to see such uses of 3D printing in many science fiction adaptations, the reality is not far behind! I can envision a future state where a space station prints and assembles itself and eventually people can live inside using smaller scale 3D printing to generate necessary tools and supplies during their stay.

On November 15, 2018, Hermione commented on Great Scott! What’s next for open innovation at LEGO? :

I had no idea Lego was using open innovation! Now it all makes sense! I still purchase Legos every year for my younger brother (he’s not that young, but he loves Legos) and each time I go into the store, I see new playsets that appeal to all ages. I assume parents are also voting!

While I do think that Lego’s original use of open innovation was truly a way to estimate demand, as you mentioned in the article, I do think that crowdsourcing could lead to ideas that might not be aligned with Lego’s core product. Given that Lego was founded in 1932 and it is still successful today, clearly the iconic bricks have some appeal. [1] I would caution Lego against moving too quickly into the digital space and forgetting their roots.

[1] “What next for LEGO?” Robertson Innovation, robertsoninnovation.com/what-next-for-lego/.

Yes!!! This is exactly what the beauty industry needs! As someone who always struggles with finding the right makeup or clothing, I would love to have a computer scan my face and body and suggest ideal products to purchase. My concern is that is it one thing to simulate color shades and completion, but it’s impossible to recreate the feel of certain types of makeup. I’ve tried lip stains, for example, that my friends absolutely loved, but when it came down to my own personal use, the color looked great, but the stain itself was drying and irritated my skin. I suppose it would be as easy as a free return if the product did not satisfy your needs, but I still find it important to try makeup on in person before purchasing.

On November 15, 2018, Hermione commented on Dream On: An Exploration of Neural Networks Turned Inside Out :

Examining neural nets is an interesting way for humans to learn about themselves through a tool that we created. While machine learning has many other applications, this specific use is a highly advanced form of self-discovery and reflection. The questions raised at the end of the article are important and reveal significant limitations. Given the physical differences between neural nets and our own brains, it may be impossible for machines to shed light on something that is fundamentally different, with certain organic restrictions. For example, there are limitations with respect to electrochemical information processing (e.g., the speed at which humans can receive and interpret information, chemically) that machines do not have. Also, the brain changes as we age, starting with ~100 billion neurons as children and eventually reducing to ~86 billion neurons.[1] The physical design of the human brain, including degradation of information (e.g., memory loss, non-perfect recall, etc.) is also something that a machine would not be impacted by. These differences and more lead me to have a bit of skepticism around machine learning truly shedding light on the functionality of the human brain.

[1]Tim Dettmers, et al. “The Brain vs. Deep Learning vs. Singularity.” Tim Dettmers, 10 Feb. 2016, timdettmers.com/2015/07/27/brain-vs-deep-learning-singularity/.