Matthew Ferguson's Profile

Your analogy to McCarthyism here is very interesting. You are right that a look back at history might be called for before this initiative is ever adopted.

This is a valid and well-reasoned criticism of the proposed counter-terrorism application. The risks you have presented are significant challenges to the viability for this project.

Great point here. How authorities respond once they have uncovered the information invokes an entirely new set of challenges. Protocols for addressing these at-risk individuals is definitely something that should be considered, balancing how aggressive the response should be.

Great comment, because this is where I find a little irony in the situation. The CIA is typically perceived as a secretive organization with closely guarded information that is strategically hidden from the public. Does it even make sense for this type of organization to be using open innovation, when dealing with information so sensitive? Are you giving more information about your process to the same people who you may be worried about?

Love this idea for public transport networks. Makes a lot of sense to me, as it would help both commuters get better information for their journeys and allow public services to react more quickly to issues.

And yes, the bias potential here is one of my fears as well.

Hill, thank you for the clarification of the correct terminology here. This is something that many of the articles appear to get wrong, so I appreciate the insight. I also agree with your point that this will never fully replace human involvement. My takeaway is similar to that from the IBM Watson case, where I view this innovation as potentially assisting/augmenting human decision making, not replacing it.

The concept of dedicated users hacking the Mindstorms’ code reminds me a lot of the modding community found in the video games industry, as discussed in our LEAD case on Valve. Occasionally, talented modders are actually hired by video game developers to design future games, therefore also representing a form of crowdsourced innovation.

I see Lego’s process here mimicking that trend, which I think might encourage younger audiences (along with adults) to participate more with the LEGO brand in the future. The entire experience becomes much more interactive, and products like Mindstorms can achieve a significantly longer period of relevance, because they can be used for applications far beyond original intentions. Creating these interactive channels can create a long-lasting loyalty among customers, which may be ideal for LEGO as it considers its strategic vision in lessening the impact of recent financial woes. It may also create some stability by mitigating the risk that new product launches will be losers, since they are already tested.

Rebeca mentioned the challenge of engaging older generations with this innovation. I think that is a critical consideration for this application because the “product”, government legislation, is going to affect everyone in Taiwan. Therefore, excluding populations of people who are not tech savvy enough to use the platform hinders the validity of the platform’s conclusions. The crowdsourced ideas may not be representative of the general public, which is the true customer.

One could argue that traditional voting measures may be exclusive to younger voters who are less familiar with the manual process, and that this technology allows a faster means of gathering political input, which will encourage greater political engagement in the long term for everyone. However, this does not diminish the challenge faced immediately, in acquiring a comprehensive sample of users.

This is an excellent example of how additive manufacturing can reinvigorate even the most traditional of businesses (like P&G). It’s not just for the shiny new startups! Razors are a great product for 3D printing because they are one half permanent (the handle) and one half temporary (the blades). So P&G can enhance its consumer goods sales (the blades) if it provides innovation for the handles. However, this innovation may struggle to enhance other P&G products. I don’t think toilet paper will ever benefit from 3D printing, for example.

Contextually, you highlight P&G’s competition from up and coming companies like Dollar Shave Club. However, P&G has been squeezed from both sides, as extremely low cost private labels are also stealing share (https://money.cnn.com/2018/04/19/news/companies/procter-and-gamble/index.html). This could be the way that they maintain their brand image as a premium product.

Great post! I find it interesting that Alibaba is using its machine learning capability to improve traffic congestion. What does Alibaba get from this relationship? Are they compensated with money, improved delivery times, or awareness? I am also worried that with an integrated system for traffic management, or any other traditional public service, there may be the potential for external hacking, which could severely disrupt the flow of a city.

Great read. I see the parallel between the Marine Corps encouraging rapid and decentralized decision making to the decentralized manufacturing achievable through additive manufacturing. My question would be how much value is there to standardization of equipment?

You mention the goal that each squad of 12 marines would be able to make its own equipment set. What if one squad discovers an innovation or best practice, how would this information be distributed to the rest of the organization to influence other squads? Making replacement parts locally certainly seems advantageous, but how about equipping a unit in the first place, is this a task more suited to traditional manufacturing methods with more standardization?

Great essay! I am thinking a little more about your recommendation to remove some variables from the data set (e.g. Zip codes) to reduce potential biases. Does removing some of these variables potentially negatively impact the quality of the matches produced? For example, you may find what appears to be a great match but then discover that you live hours away from each other. Could this scenario negatively impact the perceived value of the app? Additionally, might the system eventually begin to intuit this information? If a subset of the population for one zip code exhibits similar behaviors internally, then the system may begin categorizing those people together anyway and continuing to make decisions based on this category. The machine may “learn” the zip code relationships informally despite not being fed the information directly.