Di Dang  #Interaction20   Milan

@dqpdang

Emerging Tech Design Advocate at . Interaction designer, active listener, improv actor. Recovering philosophy major. She/her.

Seattle, WA
Vrijeme pridruživanja: listopad 2014.

Medijski sadržaj

  1. Odgovor korisniku/ci
  2. please enjoy this tech zen koan, unearthed from a 3-month old interview transcript

    "And in the app there is your head. There is another path."
  3. Odgovor korisniku/ci

    Oh did we all dream for this??

  4. Odgovor korisniku/ci
  5. 4 steps for politely, but firmly, ending a disagreement: 1️⃣ Acknowledge how the other person feels 2️⃣ Express regret without apologizing 3️⃣ Stand your ground; no explanations, no excuses 4️⃣ Offer a suitable amount of control back h/t u/tundar

  6. Odgovor korisniku/ci

    Originally from 30 Rock. Bonus points for it sounding like an expletive

  7. 🥳 A moment of personal celebration 🥳 In Sept 2017, I booked a meeting room at my old job to livestream the and invited coworkers to join. I remember thinking then, dang, I'd love to be working on something like that. Never would've thought... 2 years later 🙏

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  8. Josh's thoughtful thinking face

  9. . : "Explanations [in ML] goes two ways—in terms of what the machine conveys to the user to be intelligible, and how we meaningfully convey user feedback back into the model."

  10. . on the value of speculative design for helping us understand systemic implications over time

  11. . highlights potential use cases for AI in government: 📈 Predict energy consumption over time ⛽ Forecast which regions may suffer from fuel poverty 💻 Simulate policy impacts in controlled environments

  12. . on fairness: "It seems simple and binary, but as soon as we try to apply it, we realize how difficult 'fairness' is. It requires tradeoffs, but which differences are relevant? ML forces us to be specific about what is an ethical and fair outcome."

  13. Loved 's point that the accessibility and low barrier to entry of JavaScript is essential to Tensorflow.js supporting true .

  14. transfer learning refers to retraining ML models for new use cases

  15. . of overviews 7 key questions their teams consider before moving forward with an AI solution for scaled social impact. Not surprisingly, the criticality of stakeholder acceptance in the larger context/system in which you're working.

  16. Fascinating talk by , mapping common UI elements to ML system terms For instance, this example from Spotify: - When a user ♥️ a song, that's a true-positive reinforcement - When a user ⏩ a song, that's signaling a false-positive

  17. "Technology decisions may pretend to be value-neutral but will inevitably play out in a value-laden context." — in conversation with at the

  18. We're live, y'all! 💁‍♀️ Tune in now into the . kicking things off with the significance of . Agenda here ➡️ and live stream link below ⬇️

  19. Odgovor korisniku/ci
  20. This is. A swimsuit? 🧐

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