Open innovation at Sidewalk Labs is a fascinating idea. However, to your question, the applications are limited. Certain aesthetic choices about a city are easy for crowds to determine. For example, decisions on whether a certain area needs a parking garage or bathrooms could be made by the crowd. However, evaluating more complicated city planning concerns like sewers, utilities, and civil engineering is likely better served without crowdsourced input given the level of complexity and sophistication of the problems.
I think this technology shows tremendous promise. I am interested by the regulatory risk question you pose. Specifically, I imagine litigation becomes a much bigger issue when implants are custom to one person’s body. It is almost easier to accuse Stryker of improperly printing an implant since it is specific to an individual and other users success stories can’t be used to minimize the plaintiff’s case. Although this product shows tremendous potential for improving many lives, I am sure the proper boundaries will need to be set for it to be used in clinical settings.
A very interesting read, thanks for sharing! I was astounded by the fact that this is a real program. Despite the low capital costs of custom razors, there is an associated cost of R&D (figuring out which colors, handles, and molds should be available) that really doesn’t seem worth it. In an environment of decreasing razor prices (and competition from direct-to-consumer players like Harry’s and DSC), I doubt that there is market appetite for paying for a razor that looks and feels exactly how one would like it to look. Typically, those looking for a higher end shaving experience are already buying up to straight razors / safety razors.
This is a fun idea for sure, but appears to be more of a skunkworks project than anything truly revolutionary.
Tailored content recommendations are already a big part of the digital media and information system. We are constantly being bombarded by recommendations of news articles, TV shows, and movies. When algorithms recommend us certain content, they are by definition inhibiting our ability to consume other content through omission. Society more or less feels ok about this today. Given this, why shouldn’t algorithms also censor fake news that spreads misinformation and lies? It seems to be a similar logical construct as personalization in tech.
The pain points associated with searching and booking plane rides are legitimate. However, I am curious whether this could actually lower revenue rather than increase it. Say certain flights were recommended based on past travel history, typical destinations, connection preferences, etc. If consumers begin utilizing this recommendation feature to book cheaper flights on average, then revenue will likely not be maximized. JetBlue has to be careful to balance customer interests with fiduciary responsibility in utilizing machine learning.
Machine learning has obviously disrupted public investing to a large extent. However, CircleUp is one of the few companies to bring this disruption to the private investing market. This is intriguing, primarily because private investing relies heavily on operational improvement post-investment. Given this dynamic, I am curious to see how CircleUp’s investment recommendations co-exist with the relationships and decision-making in the board room. Perhaps as a growth opportunity, CircleUp should see whether it can carve out a role in the portfolio operations space using machine learning in the budgeting and forecasting decision-making process.
I find it interesting that Amazon chose to shut down this program. Given Amazon’s focus on the customer, you would think that they would love to hear what users would like to see produced in the studio. However, I think this program would have benefited Amazon more had scripts been available for voting by the Amazon user community. This way, you would avoid the costs associated with actually making a pilot episode and could test demand via popular opinion of crowdsourced scripts.