Miho Sakuma

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BetterUp: Finding the best coach for you at the right moment
Miho Sakuma
Last modified on April 11, 2020 at 12:02 pm
BetterUp’s algorithm can predict your needs, match a coach, and measure effectiveness of your development. Sounds terrific, but should we rely so much on algorithm?

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On April 12, 2020, Miho Sakuma commented on Nudging your way to the top? :

Mimi, thank you for this post! I was in SF last year and heard a lot about Humu from my friends so it was very cool to know how their product is used.

I love Humu’s integrative approach (e.g. data science, behavioral science, and human intelligence) and how they are providing solutions to employee’s normal business flow in less intrusive way. Two questions came to my mind.

First, related with your point about measurement of success, I wonder how the employees are motivated to actually do the actions that they are nudged to do. For instance, I have heard the power of small actions every day, but I tend to forget it because it is hard to see its impact.

Second, I wonder how much they are tailoring their algorithm to each industry or work situation. I think this solution has potential not just to the service industry like sweetgreen, but I assume that nudges they recommend and the measurement of success might be different.

On April 12, 2020, Miho Sakuma commented on AI in Predicting Candidate Potential :

Katherine, thank you for your thoughtful post!

Your point about bias reminded me of GROW case, where we discussed the gender bias inherent in data. The fact that MC used the existing talents as a way to predict best hires likely resulted in reinforcing gender bias since they only have 20% of women in the entire organization, 10% at managerial level, and 0% at the executive level.

To prevent us from falling prey to these gender bias, I think it is important for humans to have sufficient understanding about the dangers behind analytics. Otherwise, we may want to rely too much on analytics, as your former client suggested to replace analytics with humans. In fact, I connected with the team at MC after the class about their current practices (I knew them as I helped them find female talents before), and they told me that all the team members are taking People Analytics course on coursera, as they felt that they were not being able to harness the power of analytics in the best way. (https://www.coursera.org/learn/wharton-people-analytics)

On April 12, 2020, Miho Sakuma commented on Books and Movies in the era of AI :

Haerin, this is such an interesting topic! (I also loved your sense of humor ?)
I used to think that no matter how sophisticated AI gets, it won’t be able to match human’s creativity, but it seems like AI is getting closer and closer in that realm too.
That said, I think the area where AI will still not be able to deliver is the impact the art has on humans. Even though the output may me similar quality, the art created by AI will not have the stories behind the art as the art created by humans. For instance, if I listen to two pieces of beautiful classical music, one created by Beethoven and one created by AI, knowing that Beethoven created the music while he was struggling with deafness would have much more impact on me. Therefore, when we think about AI and creativity, I think we should not forget about for whom the art is created for, and not just about how good the output is.