This is a great example of how machine learning does lead to smarter products with not-so-smart outcomes. To address the gender bias, I would think the teams are trying to compensate and attract a more evenly split amount of listeners to have more representative data. While gender seems to bias the information, imagine all the other elements and factors that inform music preferences…and whether or not those are being misrepresented! Furthermore, the high reliance on machine learning for Spotify may be a liability in the long term, especially given the rising competition in the space. In order to remain competitive, I wonder how Spotify will grow its business to remain relevant — will it look into building hardware? or expand into other forms of media like movies?
Machine learning is proving to be a huge asset for companies like Airbnb because it offers an opportunity to scale faster and more importantly, create a good experience for those on the platform — the guests and hosts. I am fascinated by Airbnb because they are led by designers and find that even in solving technical challenges, also address experience design challenges. As a frequent user of the service, I am worried that with the continued growth of the company and more hosts coming onto the platform that there will be more opportunities to abuse the platform. More specifically, it makes it easier for property managers to list more and more properties, which of course, has greater implications for the housing market and local tourism.
This was fascinating to hear how Amazon has adapted open innovation to iterate on its home devices as well as engage with users to built features that matter most. It truly highlights how and why they’ve been able to lead the market in this space. As they continue to expand, I imagine they need to invest more heavily in natural language processing and voice recognition. While this investment requires technical skills, I also think there’s an opportunity to involve the community to help improve the product and build on the existing success of the product. I also wonder how and if emerging markets will care about the design or voice options that Google and Apple index on for their products — if they do not, I anticipate Amazon will continue leading the charge.
I am curious as to whether or not the investment in open innovation for snack flavors is actually a technological advance or a marketing campaign. This approach brings more visibility to the brand, engages with consumers in a whole new way, and attracts new consumers to try the limited edition / new flavors. Regardless, the open innovation approach works in the company’s favor and helps the company bring ideas to life that they already know will be received by a broad audience (which is pretty brilliant). I wonder, however, whether or not there is anything else the company can do beyond crowdsourcing to continue to innovate in the space. What about the packaging? Or where you can purchase the chips?
Thanks for raising this topic and offering more insight into what additive manufacturing offers for chocolate! I remain a bit skeptical on how this would be reasonably monetized in this industry and therefore, make it a worthwhile investment for the business. Is there a large and specialized demand for personalized chocolates or a line of chocolate with specific dietary restrictions. I definitely could be wrong because personalized M&Ms are popular but would take a further step by from this and try to understand why and how this approach aligns with Hershey’s broader strategy before deciding to scale.
It is incredible to see the opportunities additive manufacturing has for the automobile industry, especially as society moves to a shared economy where ride-share apps are being used more often. Paired with automation, I wonder if there will be opportunities for BMW to scale tweaked versions of their vehicles for these technological endeavors. I was also particularly struck by the ways in which this approach can address many of the sustainability challenges faced in the industry — particularly in optimizing material use for cars. As the investment in this field grows, will be interesting to see how we measure the environmental impact of this manufacturing and eventual scalability!