Dominic Marrone

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On November 15, 2018, Dominic Marrone commented on “Creepy”: When Big Tech Personalization Goes Too Far :

Thanks for the comment! Great point. I had not thought of a limited roll out as a way to test the risk, but I love it. I think this would definitely be effective above user testing for the reasons you mention. Additionally, the tail risk is another layer to think about. Even if you do all the right things, companies still need an action plan in the event something like the Target example happens.

On November 15, 2018, Dominic Marrone commented on “Creepy”: When Big Tech Personalization Goes Too Far :

Thanks for the comment! Agree that consumers are part of the problem. I read about this in my research for the article. There is an age gap in the way consumers think about privacy. Millenials and younger give away their data freely and don’t see it as much of an issue, while older generations are much more hesitant. This begs the question, as our population ages, will we as a society be too trusting of these large organizations owning and controlling all of our data? If that’s the case, what checks and balances will hold companies accountable? Lots to think about!

On November 15, 2018, Dominic Marrone commented on “Creepy”: When Big Tech Personalization Goes Too Far :

Thanks for the comment! Great though on the opt in/out solution. In fact, this is something my team considered when we rolled out a personalization feature on and in the app. I agree, this can be a great way to mitigate the risk. To address your other concern, I’m skeptical of firms creating a shared set of standards. It will take either a major privacy-loss event or government regulation to spur these companies to collaborate on a solution.

On November 15, 2018, Dominic Marrone commented on A Bridg to Nowhere? :

Thanks for the read! This is my first time hearing of Bridg and I found this very interesting. I do not think Bridg is selling to a dying market. I think there will always be a strong brick and mortar retail space and it sounds like Bridg can help bring this space into the digital future. One concern I do have is Amazon Go and similar solutions existing in Asia. In addition to going cashier-less, Amazon Go and others are working on this exact problem of connecting physical shoppers to digital data. Through a combination of computer vision and machine learning, they are able to identify customers when they walk in the store, connect them to their Prime account, track what they purchase, and charge them on the way out without any friction. I see this as a risk to Bridg as similar technology will likely be purchasable in the future.

On November 15, 2018, Dominic Marrone commented on Does the CIA want your geopolitical input? Yes, it actually does! :

Thanks for the read, Matt. Very interesting to hear the CIA is experimenting with crowdsourcing. One concern I have is the viability of crowdsourcing as a prevention mechanism. In many “lone wolf” scenarios, the perpetrator was already on the authorities radar and in some cases the authorities had even talked with the person. Even in the case where crowdsourcing can identify an at-risk individual, what steps can be taken beyond an initial reach out? The authorities cannot arrest someone for sketchy activity online. I think of the movie Minority Report, where a prediction system enables the police to arrest individuals before they commit the crime (called “pre-crime”). Does employing crowdsourcing lead us down a weirdly similar path? In the event crowdsourcing is successful in this use case, I think there are several ethical questions to consider before it could ever be put to use.

On November 15, 2018, Dominic Marrone commented on vTaiwan: Crowdsourcing Legislation in Technology and Beyond :

Thanks for the great read – very interesting. I’m impressed with Taiwan’s use of technology to enable open innovation in the legislation process. I’m struck with how unique this is among governments. One thing I’m curious about is data security as it relates to this process. In the US, the common push back on digital voting is the security concern and the risk in an election being hacked/rigged. I wonder, is this problem overstated? Or has Taiwan come up with unique solutions to this problem? If no, does data security pose a risk to this process being successful in the future? Regardless, very interesting and inspiring! Would love to see this in the US. Thanks for sharing.

Thanks for the read. I can’t help but compare luxury watches to luxury cars. As car manufacturing is becoming more and more automated, luxury car makers are going the other way. Rolls-Royce mentions “handmade” in their marketing as it is now a differentiator among all the machine-produced cars. For this reason, I see 3D printing as a design and prototyping tool for the luxury watch industry and nothing else. I think the craftsmanship and handmade nature of these products is what makes them valuable. 3D printing can help in the early stages of production, but I think the final product has to be handmade to remain as valuable.

On November 15, 2018, Dominic Marrone commented on Printing a Solution to the Global Housing Crisis :

Thanks for the read. I’m struck by the psychological challenge you mention, where there is a perception that 3D-printed houses are of a lower quality. This is not something I had previously considered, so it is interesting to think through potential remedies. Companies typically employ advertising to address perception issues, but I doubt a non-profit such as New Story would use limited funds for such a purpose. This opens up a couple new questions: How do other non-profit organizations attempt to make perception changes? With limited funds, where is the line where a dollar invested in perception-change advertising outweighs a dollar spent on R&D?

On November 15, 2018, Dominic Marrone commented on GE Digital: Can Machine Learning Be the Key to Turning GE Around? :

Two thoughts come to mind reading this article. First, I think it is a mistake to outsource machine learning for GE. As we move to a more digital future, these competencies will be table stakes to remain competitive as a firm. GE has a true competitive advantage in their data, so they should invest in machine learning to take advantage of this. Second, it is difficult to shift a firm from non-digital to digital and be as effective as digitally-native firms. I think of Walmart as an example of a large, non-digital firm that has been able to make this shift successfully. Walmart did this through a combination of two things: (1) heavy internal investment and (2) acquisitions. Walmart built out a large e-Commerce office in San Francisco to attract the best talent and invest in their e-Commerce capabilities. Additionally, Walmart bought digitally-native firms such as Jet and Bonobos to bring in expertise. GE has engaged in similar activities and it should continue to do so. It will take time and GE should be patient for investments to pay off.