This is a very thought-provoking article!
Given many of Alibaba’s recommendations are based on past purchases from individuals of a specific profile, I often wonder whether these algorithms are actually stifling evolutionary behavior and product adoption…if past behavior is always fueling future behavior, do individuals have a fair opportunity to find new products? What incentive do product development teams to create a drastically new product if its unique characteristics will actually prevent it from being purchased?
Regarding your question of whether computers actually know us better than ourselves, I think the answer is no. I would argue that these computers aren’t so much identifying our existing preferences as they are influencing our preferences.
When companies such as Alibaba have such a large span of influence over our purchasing decisions, it raises the question of whether the government should intervene to prevent an effective monopoly.
As I read your article, the same question of whether consumers will accept 3D printed jewelry as “art” came to mind and I think this question can be applied widely to the retail industry as 3D printing takes a larger role. As computers adopt the ability to design art without human intervention, will there be any need for an artist in this process at all? I think there will always be a role for human artists for a portion of the market, but it may become a very small role and will likely reside at the top of the market where discretionary income can afford an individual the ability to be less efficient with their capital allocation.
I wonder to what extent cheaper manufacturing of rings (in terms of labor costs, etc.) will cause consumers to demand nicer/larger jewels (making total cost of the ring to the consumer equal). Increasing the demand for precious stones could have impacts far beyond the retail industry.
I agree with the stance that additive manufacturing is the way of the future, but I cannot help but wonder whether it takes away from the “art” of a Nike shoe. In the Nike case, we saw individuals often have an emotional connection to their athletic shoes and I fear that removing human labor from most of the production process and replacing it with the face of technology will make the relationship far more cold. Aspiring athletes want to feel as though their favorite athlete produced their shoe, not a machine. When the shoes are produced in-house I think it’s easier to imagine this, but with 3D printing at home, it is more of a transaction.
In addition, I wonder how Nike as a company grapples with the prospects of replacing a large number of human jobs with a machine. Through the history of Nike, it is apparent that they take human working conditions seriously. For such a large company fueling such a large number of jobs, is it the company’s social responsibility to find other ways to employ the individuals that this technology is replacing?
This is a very unique take on crowdsourcing. I have been personally reluctant to use 23andMe for the exact privacy issues you highlight above.
One thing I find particularly concerning about this type of innovation is the influence it may have on an individual without any doctor intervention. For example, certain deficiencies or predispositions that may be highlighted by the results of this test can drive individuals to change their behavior in a way that is even more harmful. I believe in the value of using the results of these tests alongside the consultation of a doctor as I believe professional human judgement should always be a component of medical/health decisions. By completely removing a medical professional from the chain, is 23andMe actually empowering uneducated consumers with too much information?
I also find the potential downsides of misreporting to potentially be too high in this case. Humans have a tendency to misreport their own fitness, digestive and mental health activities and if this data is then fed into algorithms or studies that are used for future medical advice, we could be fueling a faulty system. As they say, “bad data in, bad data out.”
I too am a huge fan of Glossier; however, I find their significant growth to be concerning. Glossier has been able to capitalize on our generation’s preferences “to be heard” through both the crowdsourcing you describe and through their impeccable customer service that aims to go above and beyond the industry standard. However, this has been in a time in which Glossier is funded by VC’s (e.g., Forerunner) that are comfortable with a company generating zero to minimal profits. As the company continues to scale and mature in investment stage, I foresee larger (and less patient) investors demanding Glossier begin to prioritize different metrics (e.g., increasing labor efficiency, increasing physical distribution) and it concerns me that the company will lose the very value proposition with which they have found success. I also wonder what Emily Weiss’s role will continue to be moving forward and whether the business can sustain a potential future departure.
Very interesting article.
Given these algorithms largely rely on past data to predict future performance, I wonder whether they will end up rejecting many more companies than a human would have otherwise simply because there have not been similar companies raise capital in the past. I wonder to what extent these algorithms will reduce the upper bound of investment success (i.e., fail to approve the biggest unicorns) in turn for taking on less risk. If the industry moves towards this, I could see the venture industry suffer from a lack of capital for the most risky or unproven concepts…the ones that may be backed today based on someone’s “gut”.