GSGoldstein

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Personalized Styling at Scale: What is the right balance between machine and human input?
GSGoldstein
Posted on November 14, 2018 at 10:25 am
Stitch Fix delivers personalized styling at scale through a combination of machine-learning algorithms and human input. As they continue to scale into new markets and new business lines, what is the right balance of machine vs. human input?

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On November 15, 2018, GSGoldstein commented on Does Additive Manufacturing Pose a Threat to Gun Control? :

Dear Fake Billy,

I’m also terrified about this idea. We already face so many challenges around the regulation of firearms in this country in both the primary and secondary market. Taking this one step further and allowing anyone with a 3d printer to manufacture their own firearm and likely going undetected is very scary. I’d love to say let’s just make this illegal and it won’t happen but unfortunately I believe that won’t be entirely effective. At the same time I worry about working with regulators and the NRA to try and regulate this as it introduces a possibly very slippery slope. So in short, I’m scared. Thanks!

On November 15, 2018, GSGoldstein commented on OpenIDEO’s approach to crowdsource the best ideas from the cloud—engaging the public to tackle the world’s most challenging problems. :

Thank you so much for this read, loved learning more about IDEO! I think using their crowdsourcing tool as a means for democratizing innovation is fantastic. It’s very akin to the open-source developer community that exists on Github, for example. When first exposed to this method of collaboration my immediate thought was there is no way any of this scales and no way people stay on track. But I was wrong! I’ve seen major projects come out of the open-source community and oftentimes the best ideas come from the tinkerers. At the same time, many of these open-source projects eventually have an enterprise company that is able to take it and commercialize and scale the idea. Depending on what you’re trying to solve I think this is also critical. Thank you again and look forward to learning more!

On November 15, 2018, GSGoldstein commented on Building Blocks: Winsun’s Application of 3D Printing in the Construction Industry :

Thank you so much for this very interesting read! I learned so much. To me one of the biggest hurdles in adopting 3D printing technology to construction is the potentially high barrier for change. Construction is an industry that has existed forever and while I’d imagine there have been a lot of technological advancements made, I still see many aspects of it that have remained largely unchanged. Secondly, I do also wonder if this technology will scale big enough to disrupt the entire industry or possibly just lower costs and ease the process around manufacturing parts needed for construction, etc. I look forward to reading more about this!

On November 15, 2018, GSGoldstein commented on Your Personalized Dinner is Served :

Great read, thank you C! I have the same question around the value of their machine learning at possibly low volumes. As a consumer I’m not sure that I can appreciate the calibration period of their machine learning engine and may choose to leave the service prematurely, in that case. As part of the Kraft Heinz family I would also support partnerships to enrich their data set. Thank you!

On November 15, 2018, GSGoldstein commented on Volition: Crowdsourcing Innovation in the Beauty Industry :

Super interesting read on the beauty industry, Tasnia! I love the idea of crowdsourcing new ideas straight from the consumer. Too often do large companies stand in their own way of innovation by sticking to old inflexible ways. I believe consumers know what they want and they’re willing to tell if you ask the right way. At the same time, I do worry about the company becoming too reactive in their thinking vs. presenting consumers with something they didn’t even know they wanted. As for the channels, Ulta and Sephora continue to be leaders in this space and I agree that to be competitive they need to play here in spite of many challenges. Looking forward to seeing how this company continues to grow!

On November 15, 2018, GSGoldstein commented on Exploring the ethics of machine learning at Facebook – where does it draw the line? :

Great article and analysis of the various ways Facebook is leveraging AI and machine learning, Russell! I’ll try and sum up my response in a short paragraph but would love to continue the conversation offline as well!

1. The good and the bad – True, there is a lot of good that I believe Facebook is doing when leveraging AI and machine learning. Suicide prevention and terrorist threats are great examples of this. At the same time, I worry about governments overstepping their boundaries and abusing the wealth of data Facebook has on its users. Facebook’s obligation to its users is to protect the community and their privacy, above all else. While I agree Facebook should be working with governments when it comes to regulation decisions, issues around net neutrality, etc, I very much worry about Facebook partnering with the government around issues specific to criminal activity. Check out what happened in our Brazil office a couple of years ago here (might help to better illustrate my point): https://www.theguardian.com/technology/2016/mar/01/brazil-police-arrest-facebook-latin-america-vice-president-diego-dzodan

2. Are they listening on your conversations – while I won’t really ever know the truth I do believe Zuckerberg when he states that they are not listening in. Facebook is able to predict a lot about you as a person because it essentially knows everything you do online. Most, if not all, websites and apps you visit have a relationship with Facebook and therefore Facebook has access to all of that data, which they are then able to learn from. After Cambridge Analytica there has been a lot of press about the ethics around using your friends’ data to learn more about you. If it is not without consent, the company has stood by not being able to leverage that data, which I very much agree with.

3. User privacy and control – for me this all comes down to transparency and control. Do you as a user know what Facebook is collecting and how they are using it? And do you have the ability to control that? Largely, in my opinion, no. Companies attempting to disrupt this are focused on decentralizing the web in an attempt to restore power back to the individual. Your data is yours to own and I believe we should have the controls to make technology work for us, not the other way around.

All of that being said, I still believe there is a lot of good Facebook has done via their use of AI and machine learning. Facebook’s ad platform has given way to millions of small business owners being able to earn a living in a way that wasn’t possible a couple of years ago. Through the acquisition of Oculus I’m hopeful that we can bring AI to underserved parts of the world and provide them with greater access to education. In places around the world where the free press may be under attack, those media outlets can hopefully still exist on Facebook and connect with their relevant audiences leveraging their sophisticated technology.

Great take on this and loved reading through everyone’s comments!

Gaby