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Facebook, Fake News, and AI: Yet Another “HUGE” Problem in the Digital Era
Ty
Posted on January 28, 2019 at 3:50 pm
The proliferation of misinformation, or fake news, on social media platforms has become a serious problem. Facebook - largely considered to be the main culprit in this controversy - is leaning heavily on machine learning to fight off this issue.

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Healthcare is plagued by high costs. This is especially true in the pharma industry, and we’ve seen more and more instances of bad actors taking advantage of the system. However, this all makes sense in the context of massive R&D spend that goes into the development of such drugs. This is where I think the OOID Program at Lilly has major upside – by utilizing the power of external forces (i.e. minds) to continue to drive innovation in big pharma. I would emphasize the risks highlighted above as well – IP is a major issue. Not only that, but also the regulatory / accountability aspect of drug development – my main question being: If you don’t have full control / accountability over product development (as I would argue the case is here to some extent), are you opening yourself (Lilly, in this case) to incremental liability / exposure that could potentially have negative consequences – e.g., major fines and PR risk?

On November 15, 2018, Ty commented on Open Innovation at NASA: Impact in Culture :

Very interesting perspective! I wonder about the efficacy of open innovation for solving problems as important and as complex as the ones that NASA is working on and how the real R&D professional at NASA feel about this. I agree that open innovation promotes learning and a differentiated approach – and in certain instances I think it’s very effective. But, to think that someone could contribute meaningfully to help solve actual “rocket science” seems somewhat far-fetched, and I would think the extra “noise” this creates in a NASA employee’s life at work would serve as more of an annoyance than a positive contribution – not to mention the privacy / security issues that might come along with this type of open forum.

Great article! My main curiosity revolves around the actual application of machine learning in a space dominated by “mind share”, or brand awareness. The highest market share beer is Bud Light, but I can guarantee that Bud Light is not the beer recognized for best taste – rather brand awareness and relative ubiquity. So my point is… although I understand how machine learning is helping Carlsberg test consumer tastes / reactions effectively and efficiently, but I would postulate that most beer consumers already have a perception on Carlsberg’s taste, and so improving the taste to be more geared toward consumer preference would not be as effective as “buying” new tastes – i.e., buying up smaller craft- and microbreweries. This would be faster and is a way to completely differentiate from the existing brand’s taste. Also, how much of the beer-drinking population knows the difference between “acidity” vs. “hoppy” vs. [other beer measurement]? As we have seen in our multiple beer cases, a majority of beer brands are owned by a conglomerate – namely AB InBev and SABMiller. However, this could also be a marketing tool – e.g., “Carlsberg beer has reinvented the product by defining the ‘perfect’ beer by using machine learning.” Gimmicky? Yes. Effective? Maybe.

I agree that wearables have become somewhat of a commodity, and although they have garnered relative success, they still don’t possess the functionality to drive widespread adoption. WHOOP, however, seems like it might be a game-changer, given it is based in machine learning and thus has higher potential for functionality. This is especially interesting given the broader movement toward a healthier, more active lifestyle. As it seems like this product would warrant a high sticker price, I think the initial target would be high-performance athletes or those with health issues – e.g. diabetes. However, once initial adoption takes place, I could see word spreading to a more general population that recognizes the higher functionality / reliability of the product.

On November 14, 2018, Ty commented on Safilo: 20/20 Vision, Or In Need of Better Sight? :

I had no idea 3D-printing could apply to more complex products such as eyeglasses. This is very interesting, especially given the increased competition in the eyeglasses space – between luxury brand manufacturers like Safilo, direct-to-consumer models like Warby Parker, and specialty purpose models like Felix Gray. This could present a unique opportunity for Safilo, but I also agree that it could threaten the luxury aspect that they have already established. However, the customization option that 3D-printing allows for could create a unique competitive advantage. I don’t know of any well-known eyeglass brands that offer wide customization options with any sort of speed / efficiency, which could be an opportunity if Safilo fully leverages this model.

On November 14, 2018, Ty commented on 3D Printing…we should ‘Just Do It’! :

This is a very interesting article, especially in light of the recent Nike case in marketing! My main question: Does the consumer really care how its shoes are produced or is it more of a gimmick? As a consumer, my only concern would revolve around quality control – just make sure my shoes are as functional / comfortable as non-3D-printed shoes. The obvious benefit is to the manufacturer. R&D becomes more powerful, making innovation more attainable, and mass production allows for major cost synergies – and would also allow Nike to further distance itself from suspicious employment practices.