Jane Deere

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On November 15, 2018, Jane Deere commented on Ford: Using Machine Learning To Humanize Vehicles :

Unexpected application of facial/emotional recognition by Ford! I think that combined with information on driving speed/pattern, the technology could have a lot of cool applications. (One great implementation would be in the prevention of drunk driving.) While I think it has potential for more good than harm, you’re right that Ford will have to get over consumers’ negative visceral reaction to having their emotions monitored. Especially for negative emotions, such as anger or sadness, it is hard to predict how an individual will react to different kinds of intervention, and so that poses a challenge for design as well.

Really exciting innovations happening at L’Oreal, thanks for sharing! With the increasing move to e-commerce, I think that the augmented reality technology that allows you to “try on” products has a lot of potential to drive online demand and reduce costs of holding inventory in brick and mortar stores. The smart hairbrush and other measurement- type technology could also be an interesting way to track progress and encourage regular use of a product, to help users recognize gradual results (especially in skincare). I do think that a big risk that L’Oreal will need to overcome is the trust aspect of ML and data collection. I assume that people trust a human much more to recommend products than a program (though I may be wrong!) and the idea of scanning something as personal as your face, can be scary, with implications for facial tracking, identity theft, etc.

On November 15, 2018, Jane Deere commented on Machine Learning – In Theatres Now :

Interesting article about how ML can predict demand for types of movies! You brought up an important missing piece for studios, which is the ability to bucket types of consumers and monitor externalities such as social influence on the decision making process. This article made me think a lot about MoviePass and its ability to provide granular, consumer level data on movie watching trends. While many wonder how they will sustain their current subscription business model, I actually think their end goal is to build up a diverse set of data across many theaters, geographies, and demographics, and then sell it to movie studios or theaters to feed into programs such as Merlin. With the flexibility of an app, it would be easy to tweak the kinds of data being collected. So for example, adding a social aspect to see patterns in groups of friends and perhaps information on the tipping point for users watching an “unexpected” genre of movie. Studios can then cater their marketing or production to these trends.

On November 15, 2018, Jane Deere commented on Chanel’s Foray Into 3D Printing :

Interesting article on an unexpected use of 3D printing! Aside from the concern about counterfeit goods, I think there is a danger in diluting the “luxury’ brand of Chanel with preconceptions about lesser quality of 3D printed goods (whether this is true or not). I think luxury is associated with high labor, hand-crafted goods, and while forward thinking design and innovation are important for the company, customers may begin to question the high markup on a good that can be so easily reproduced. To combat this and strike a balance, I wonder if they can use 3D printing for fast prototyping, but then more traditional processes for the full manufacturing process.

Interesting article about a brand that I love! I think Emily Weiss did a great job of spotting a gap in the beauty market and fulfilling it for consumers.
As someone who had to manually read through samples of feedback from customers at my old job, I agree with your recommendation to invest in ML for parsing through feedback and aggregating it. Having highly skilled labor such as data scientists (or PMs in my case) sifting through droves of feedback can be very costly for the company when the analysis and recommendations are what they should be spending time on. I do not think that ML detracts from the “personalized” customer experience, but actually helps further that mission. By going through feedback more efficiently, Glossier will be able to tackle a larger volume of it and drive further insights for product development.

Great article! I think Task Rabbit is a good example of the “Gig Economy” trend we are seeing with companies such as Uber, Rover, etc that allow independent contractors to work more flexibly on their own schedule. You bring up a lot of the biggest challenges with lack of benefits and pressure to lower prices. While providing a source of new jobs and potential for empowerment, many of these services are so centered on customer service that it comes at the detriment of these service providers. From a moral perspective, I also think that services like task rabbit can dehumanize workers who you interact with on a one-time basis as a maching/means to an end, and who you may never have to see in person, which further amplifies the issue.

For the question about Ikea- I’d be curious to see what percentage of tasks are currently in the hardware/furniture assembly category. If it is a large enough percent, branding it under Ikea, and driving more traffic towards the service may actually be a net positive.