Brian O'Neill

@rhythmspice

I help orgs design innovative data products powered by data science & . . Host of podcast. Prof. musician:

Cambridge, MA
Vrijeme pridruživanja: lipanj 2009.

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  1. prije 10 sati

    “I see that this is a slightly broader movement where people are understanding the value of and they see that it is something that they can't avoid or they can't prioritize it lower anymore.“ — Ganes Kesari () 🎧 to :

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  2. 3. velj

    This approach to building or solutions leads us to building solutions in search of a problem. leaders: u don't have to do the "build and pray" method, just because something uses in a new way + users don't spoon feed you their needs.

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  3. 3. velj

    One way for teams designing machine-learning data products w/ AI experiences is using the acronym PiCAA: Predict, Classify, Augment, Automate. "How might we [verb] [X] so that [we enable Y outcome?]" The "i"? It reminds us the solution may be to "Ignore" AI.

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  4. 31. sij

    “While we have done a few hundred consulting engagements and help with bespoke solutions, there is still an element of commonality.” — Ganes Kesari () 🎧 to here:

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  5. proslijedio/la je Tweet
    29. sij

    I had a great time chatting with Brian on how analytics and design can deliver business value. Listen to this and let us know what you think!

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  6. 28. sij

    Can good help , , and projects be more successful? How does storytelling fit in, particularly when that story is deployed within a software ? 🎧 to my chat w/ from on Ep. 31 of at

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  7. 27. sij

    Should new & products start with a vision…or data prep 🧹? We all know there's plumbing and cleaning that likely needs to get done to enable new services, but what should come first? What are the pros and cons of data-first vs. vision-first?

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  8. 27. sij

    Everyone who visits Poland should visit Auschwitz (Oświęcim) + Birkenau. Anti-semitism existed before WW2...and still survives now despite the Holocaust atrocities. Jewish or not, everyone should take a moment today for since is not guaranteed

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  9. 27. sij

    Assist or automate? If you're using , I would think the risk of failing on one more more levels is pretty high if you haven't done any -driven research before deciding to automate. Of course, failure depends on clear definition of what success = for users & the org.

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  10. 24. sij

    “Before anything, we ask ourselves this: Does it fit into the workflow of people that already have maybe one of the most demanding jobs in the world?” — Joost 🎧 to here:

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  11. 22. sij

    Does create business impact? Yes, according to , and top quartile orgs. w/ exec support for design significantly outperformed the lower 3 quartiles: 32pp higher + 56pp higher total returns to shareholders over 5 years.

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  12. 21. sij

    Looking forward to giving a Keynote talk this wk 's "Spring 2020 Welcome Event" for the Master of Science in Applied on ways that human-centered helps increase the value of data-driven products & solutions.

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  13. 20. sij

    Concerned about low engagement with your enterprise data product, analytics service, or decision support tool? You might be focusing on the wrong problem. Focus on an engaging experience, not the quantity of engagement.

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  14. 20. sij

    “Data alone isn’t the ground truth. Data isn’t the thing that we should be reacting to. Data are artifacts. They’re breadcrumbs that help us reconstruct what might have happened.” — Angela Bassa () 🎧 to here:

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  15. proslijedio/la je Tweet
    9. sij

    Really enjoyed the latest data podcast on human centered ML. Love the idea that we need to focus more on when it is right to use ML— it shouldn’t be used to solve all problems! Thanks and !

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  16. 17. sij

    “There's a very big gap between what is scientifically medically interesting and what's practical in a system.” — Joost 🎧 to here:

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  17. 15. sij

    You can—and should—be designing the reward function in your explicitly if you have humans in the loop. Designing for probabilistic outcomes means u really have to build for your users. Can't just know how they'll respond to 1 output: now it's a range.

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  18. 14. sij

    Via “I’m willingly trading my for the services I’m getting like at ...what could they do with this? The jury is out on that...this is where we need smarter thinking.”

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  19. 14. sij

    Re: in education “we can now get data on learning and algorithms informing where students are at...my fear is that this is a big ask...for example, it may be hard to ask my dean to install a bunch of cameras in my classroom so I can track my mba students!” Cc:

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  20. 14. sij

    Going on now - and book release from - “Competing in the Age of ” “Barriers to innovate have dropped dramatically....the old ways (of doing business) won’t work”—Karim Glad to hear & questioning “is this good for society?” – mjesto: Klarman Hall - Harvard School Of Business

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