Christie Klauberg's Profile
Christie Klauberg
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I agree with the above commentary, this is a very interesting topic. I recently attended a panel on “Human Augmentation” as part of the tech conference and one of the topics discussed on the panel was exactly this, the use of 3D printing of tissues. One of the speakers is the co-founder of ApreX Biotech, which uses origami to create artificially enhanced organ tissues for drug development and transplantation. He talked a lot about how this technology can help drastically reduce the development costs of drugs, the need for animal testing and the potential development of more customized medical solutions. I too this this technology has so much potential on a global scale. I do worry that if this technology does become more readily available will people take worse care of their bodies knowing they can replace organs as necessary?
Matt – I think you pose a very interesting debate. In my mind, there are two sides to this market. First is the public participating in the open innovation. On the other side is the government agency who must trust that the crowdsourcing public, a group that has self-selected to participate in the platform, is acting in the best interest of the country. Finding the right incentives to motivate the public to participate and to act as good actors may not be an easy task.
Furthermore, adopting and admitting that crowdsourcing can better predict geopolitical events may be a bit scary for government officials – does this put them out of a job? Where does this leave them?
Talk about customization (!). A 3D printer that can print a shoe to PERFECTLY fit your unique foot. As I think about the use cases, especially in light of Nike’s case today, I agree that this technology could be incredible powerful when it comes to elite athletes. The endorsement of this technology by elite athletes would too promote the aspirational nature of this product and technology, allowing the product to reach far beyond its functional value and tap into the emotional value. I would assume other brands, aside from Adidas, are too investing in this technology but I would also encourage Adidas to think of the best way to integrate this technology into its current system and how to best allow 3D printing to complement and enhance its existing production system.
As a long-time Fitbit wearer, I am always intrigued monitoring my activity patterns as they relate to my health and well-being. I constantly track my steps, heart rate and sleeping patterns with no real conclusions besides I don’t sleep enough…
I would think, to your point, there would be a way to mine this data on an individual basis to make broader conclusions about health, locate precursors to certain diseases, recommend activities and habitual changes that would help make individuals more healthy. I would think too with more and more data there would be a way to partner with hospitals as well as insurance companies to promote a healthy lifestyle. I would think that all these collaborators would be in favor of improved machine learning to learn and make predictions about health based on the data from Fitbit; the machine could serve as such a tremendous partner to physicians in this capacity. Never replacing a physician in my opinion but could certainly serve as a lethal partner.
As you noted, I agree machine learning has a lot of potential in the e-commerce industry, providing a more personalized and customized experience as many RTR customers are likely looking for. I’m thinking a chatbot might help the service tremendously, both on the customer side as well as on the company side. I too agree that machine learning has its limitations. As we discussed with Gap and Big Data, I think the best use of machine learning will be to complement humans rather than replace them in terms of creative design and the next big fashion. Fashion is forward and I am not convinced a machine knows that. I thought it was interesting you noted that the ethical implications of machine learning categorizing a customer as RFR thinks about rentals and likelihood of return. In my mind, as long as a variety of data sources are used to come to the conclusion, it is a fair mechanism to use by the company to prevent issues. It is not dissimilar to how a bank thinks about lending.