The author raises an interesting question regarding the impact of machine learning and AI on privacy. To what degree is it acceptable for a company to gather data on their customers? The answer to this question depends on many factors, including the types of data a company is gathering, the country in which the company is operating (privacy laws vary significantly between countries), and the loyalty of its customers.
Recent events (i.e. Facebook and Cambridge Analytica) highlight the reputational risk that companies take when collecting customer data and the safeguards they must put in place around the types of data they are collecting, how they are collecting it, and with whom they are sharing it. These considerations are especially important for a company such as Disney, whose brand it build on consumer trust and a “family friendly” image. When integrating AI and machine learning into its strategy, Disney should carefully evaluate potential customer risk as well as political and regulatory risk.
In addition to providing a fascinating glimpse into the inner workings of NASA, this article asks a critical question – how will this open innovation impact employees? As open innovation, machine learning, additive manufacturing and other technological trends are harnessed by companies, the required skillsets of the companies’ internal workforces will shift. In this case, the author recommends a change to hiring criteria to focus more on skillful management vs. technical competence.
I agree with this recommendation but believe that this is representative – on a micro level – of a macro shift in the types of skills that employers will seek in their employees over the next decade. A crucial outstanding question is how governments, educational institutions, and job training organizations will help an existing workforce build these skills?
This article recommends manager restraint in deciding which new technologies to adopt and how quickly to adopt them. Additive manufacturing has been instrumental to improving Siemens’ supply chain and can be similarly transformative for other companies. The author raises a good point; however, that managers should not embrace new technology for its own sake but should conduct cost/benefit analyses for each implementation. Traditional financial figures will naturally dominate these analyses, but human capital and cultural impacts should also be evaluated.
Hype surrounding new technologies often drives managers (and investors) to over-index early in a technology’s lifecycle during a period of inflated expectations, onl to experience a period of disillusionment when promised benefits do not materialize as quickly as expected. Gartner describes this process as the “Hype Cycle.” To avoid this Hype Cycle, companies should thoroughly evaluate investment in new technologies (AI, VR, 3D Printing, etc.) before committing resources.
This is a very interesting look at the inner workings of a successful incumbent in an industry that is ripe for disruption. Transformative trends in beauty include a shift to DTC, a movement toward diversity and inclusion in beauty lines, and an emphasis on sustainability. Health and Beauty focused incubators and accelerators, such as Seed Beauty – home of ColourPop and Kylie Cosmetics – are helping new brands enter the market. Health and Beauty startups have sprung up at a rapid rate with new entrants such as Glossier, Milk Cosmetics, and StyleSeat changing not only what health and beauty products consumers are purchasing but also how and where they are purchasing them.
This article provides a fascinating glimpse into the way L’Oreal has responded to this industry evolution by using open innovation. While the company has done an admirable job of engaging employees and nascent startups, an untapped resource is the company’s customers. While more filtering of ideas may be required, engaging customers in open innovation could widen the top of the beauty giant’s innovation funnel and produce out-of-the-box ideas worth pursuing.
This is a fascinating look at one of the most impactful potential uses of 3D Printing. The author outlines one of the key challenges when pursuing truly cutting-edge applications of new technologies – the need to fund expensive, lengthy, and risky projects. To incentivize this investment (for companies, private investors, or public investors) there must be a commensurate payout. In the past, patents for pharmaceuticals and medical devices have ensured that potential payoffs were large enough to incentivize risky investments in medical compounds or technologies. How will IP law apply to bio-printed organs?
Another outstanding legal question is that of liability. If there is an issue with a bio-printed organ, would Organovo be liable? These questions highlight a broader need for the regulatory and legal environments to catch up with new technology and the potential gap that will exist while they do.
This is an interesting look at the use of innovative technology to help solve a broader societal issue. This article made me consider impact opportunities for machine learning and other new technologies beyond simply improving business outcomes. An additional technology that could play a pivotal role in wildlife protection is open innovation through social media and digital engagement. Using these tools, the Ugandan Wildlife Authority and other groups can tap into the ideas and support of a broad international population.
These same technologies can be applied by other nonprofits or social groups. For example, the Red Cross utilizes open innovation to coordinate disaster response efforts. The next step in the dissemination of technologies such as machine learning, AI, open innovation, and additive manufacturing is to explore ways in which they can be used not only to improve business outcomes but also global societal development.