Thank you for the great article! Public transportation in the US is certainly under increasing stress due to re-urbanization and weather-related stresses. The US public transportation industry as a whole seems to be undergoing an open innovation revolution as new ideas pop up every day from Elon Musk’s hyper loop to autonomous taxi driving services within cities.
For the MBTA specifically, the challenges they face are similar to most other major metropolitan areas, including New York and Chicago. I would recommend opening their open innovation platform to “peer cities” and engaging in workshops to take the ideas and hone in on particularly promising solutions to the problems they face. The assistance of peer cities would help the MBTA test and legitimize any open innovation proposals, and learn from the experiences of other public transportation agencies.
To your point on where the submissions are coming from, I think it is actually to the MBTA’s benefit that the majority of solutions are sourced from the for-profit world as a key challenge to any public transportation implementation is scalability and feasibility: two elements that a for-profit will be acutely aware of and able to solve for. That said, in partnership with the peer cities, I think it would be helpful to test any finalist concepts with a team of economists and engineers from a respected academic institution to ensure the MBTA has conducted ample due diligence on the open innovation concept.
Thank you for your article! I completely agree that open innovation can unlock tremendous potential in space exploration, as exemplified by the economies of scale and technology introduced by private companies like SpaceX. That said, your question about confidentiality is crucial, and a true challenge with any open innovation platform. In order to tackle the confidentiality question, I would recommend delving deeper into your first question and reframing it: what is NASA’s mission?
NASA excelled when it had a clear mission (e.g. land a man on the moon), however today there seems to be a myriad of opportunities – from expanding satellite networks to landing people on Mars -, each requiring substantial sums of money and lacking strong political support. As a result, operationalizing any initiative at NASA has been met with resistance, leading to ineffective execution. Confidentiality has exacerbated this lack of vision by surrounding missions with uncertainty and confusion.
In order to excel at open innovation, I believe NASA will have to clearly outline commercializable objectives, similar to SpaceX, that will help it regain momentum on non-confidential projects and build an open innovation community upon which it can rely for future, more sensitive projects. Such commercial opportunities could include expanding satellite networks, growing public space tourism or even exploring space mining opportunities. Open innovation would allow for substantial input in these initiatives without significant confidentiality concerns or a need for a strong mission.
Thank you, Holly for this article! I completely agree with the risk of using machine learning to assess resident risk profiles, as emphasized in the previous two comments. However, I also would like to bring attention to two other threats that Holly mentioned: 1) that there is limited faith in the integrity of the system and 2) that members of the “heat list” are no more or less likely to be involved in a crime. These threats indicate to me that the CPD has a more pressing issue than implementing machine learning to predict criminal propensity: they have a trust problem.
Without trust, no level of machine learning insights will suffice to enable CPD to operationally and proactively reduce crime outcomes. It would therefore make sense to me for the CPD to run a resident (not academic) competition on trust. Conduct deep interviews of South- and West-side, crime-prone neighborhoods. Get to know why residents mistrust the police and figure out how to rectify that relationship. Once residents view the police as an ally, rather than a threat, then the police and residents will be able to proactively partner together towards a safer community. Maybe then, the #1 source of information will come directly from responsible neighbors, rather than an expensive machine learning algorithm with information asymmetry challenges.
Great report, thanks for sharing! As social media becomes an ever more important news source for the average voter, operationalizing an effective and trustworthy content review system is critical for the health of a democracy. I agree with your recommendations on how to practically implement a scalable solution: by blending machine learning with user flagging. Although I believe that at the end of the day, a judgment call will always need to be made on what to do with content.
To Melcolm’s comment on whether to remove or simply de-prioritize fake news, I wonder if we have to ask a larger operations question: is Facebook’s platform approaching the status of journalism / free press? If so, the protections afforded via freedom of expression within the US might jeopardize Facebook’s ability to exercise their own discretion on reviewing content. Rather than risking an expensive judicial backlash on Facebook’s judgment calls, I wonder if it would be better for Facebook to explicitly partner with the government and other free press institutions to explore how to best tackle the challenge of judging what to do with posts deemed “fake news”? This partnership could help Facebook make what I believe to be the most difficult operations decisions they have: what to do with fake news.
Excellent article! I agree with your assessment of the value and potential of AM on Bechtel’s construction activities, particularly to simplify and automate repetitive tasks. Increasing safety on the job site can have significant ripple effects such as improved employee morale, talent acquisition and profitability. As argued in your Gaffar et al. citation, 3D printing can also result in significant material and carbon emissions savings, further improving profitability.
To your suggestion to focus on partnerships in the short term, I completely agree with you and Burdell that partnership will be essential to success. However, I wonder if Bechtel might be better off pursuing one partnership with an extremely successful AM – similar to Nike with HP – rather than attempting many small partnerships? To Sinclairs’ comment, a technology like this one will require heavy upfront investment, so it may be prudent to invest in a tried and true AM.
Great article! I agree that additive manufacturing for Nike’s shoes is a logical evolution in Nike’s strategy that hits all three pillars of 2X Innovation, 2X Speed and 2X Direct and anticipates the direction of the market. However, to expand on ABP’s democratization comment, I fear that the gains derived from this 3D printing technology will result in short term gains and long term losses. As 3D printing becomes more ubiquitous, it will become harder and harder for Nike to protect the IP of their designs, exposing them to potential generics sold at half price with the same quality. We have already seen the risks of 3D printing with generic, plastic firearm designs.
To mitigate this risk, I would recommend that Nike focus substantial R&D on developing a hard-to-reproduce thread or printing material that can protect their design. Nike would also need to invest in Coca Cola levels of secrecy surrounding both their 3D printing design and thread manufacturing process. If Nike is unable to protect this IP, they run the risk of innovating themselves out of existence.