Mission-Driven Machine Learning
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Mission-driven MLers love customers more than code, results more than research, and values more than value.
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Mission-Driven Machine Learning
- 1. Mission-Driven Machine Learning David Murgatroyd ( @dmurga) May 28, 2019 (please don’t sue me for copyright violation, Flight of the Conchords!)
- 2. @dmurga
- 3. @dmurga
- 4. @dmurga
- 5. @dmurga Mission: to unlock the potential of human creativity
- 6. @dmurga Mission: to unlock the potential of human creativity Vision: a million creative artists living off their art and billions of fans enjoying and being inspired by it.
- 7. @dmurga Vision: a million creative artists living off their art and billions of fans enjoying and being inspired by it.
- 8. @dmurga Vision: a million creative artists living off their art and billions of fans enjoying and being inspired by it.
- 10. @dmurga 1. Love customers even more than code Characteristics of Mission-Driven MLers
- 11. @dmurga Hypotheses machine learning enables: ● “We could move our metrics if we could predict …” ○ Which way is this stock price likely to move? ○ Is it going to rain in the next hour? ● “We could move our metrics if we could perceive …” ○ Who is in this picture? ○ What did the user just say? ○ What places are mentioned in this document? ● “We could move our metrics if we could personalize …” ○ Which new legislation is most likely to affect this company? ○ What new songs are most likely to be liked by this user? Product Discovery
- 17. @dmurga Design
- 18. @dmurga ML’s output is often wrong, unintuitive, off- brand, and varying by user. Design
- 19. @dmurga ML’s output is often wrong, unintuitive, off- brand, and varying by user. Design
- 20. @dmurga ML can elicit unexpected behavior or unintended incentives in users. Design
- 21. @dmurga ML can elicit unexpected behavior or unintended incentives in users. Design
- 22. @dmurga ML’s output is often wrong, unintuitive, off- brand, and varying by user. ML can elicit unexpected behavior or unintended incentives in users. Design
- 23. @dmurga Mission: to unlock the potential of human creativity Vision: a million creative artists living off their art and billions of fans enjoying and being inspired by it.
- 24. @dmurga
- 25. @dmurga
- 26. @dmurga
- 27. @dmurga
- 28. @dmurga
- 33. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World
- 34. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World
- 35. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Fundamental
- 36. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Fundamental Applied
- 37. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Fundamental Applied Discovery
- 38. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Fundamental Applied Delivery Discovery
- 39. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Industrial Lab Findings ML Product Lifecycle
- 40. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Academic Findings Industrial Lab Findings ML Product Lifecycle
- 41. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Proto ML Product Academic Findings Industrial Lab Findings ML Product Lifecycle
- 42. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Proto ML Product Academic Findings Industrial Lab Findings M.V. ML Product ML Product Lifecycle
- 43. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Proto ML Product Academic Findings Industrial Lab Findings Mature ML Product M.V. ML Product ML Product Lifecycle
- 44. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Proto ML Product Academic Findings Industrial Lab Findings Mature ML Product v2 and beyond M.V. ML Product ML Product Lifecycle
- 45. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Mature ML Product v2 and beyond M.V. ML Product ML Product Lifecycle
- 46. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Mature ML Product v2 and beyond Proto ML Product M.V. ML Product ML Product Lifecycle
- 47. @dmurga Sureit’svaluable? Experi- mental DevelopmentResearch Hypoth- esized Known Unknown Known to Our Org.Known to World Sure it’s possible? Unknown to World Mature ML Product v2 and beyond No New ML Proto ML Product M.V. ML Product ML Product Lifecycle
- 48. @dmurga 1. Love customers even more than code Characteristics of Mission-Driven MLers
- 49. @dmurga 1. Love customers even more than code 2. Love results even more than research Characteristics of Mission-Driven MLers
- 52. @dmurga
- 53. @dmurga Mission: to unlock the potential of human creativity Vision: a million creative artists living off their art and billions of fans enjoying and being inspired by it.
- 54. @dmurga Mission: to unlock the potential of human creativity Vision: a million creative artists living off their art and billions of fans enjoying and being inspired by it. Culture
- 55. @dmurga Mission: to unlock the potential of human creativity Vision: a million creative artists living off their art and billions of fans enjoying and being inspired by it. Values: Sincere, Passionate, Innovative, Collaborative, Playful Culture
- 56. @dmurga 1. Love customers even more than code 2. Love results even more than research 3. Love values even more than value Characteristics of Mission-Driven MLers
- 57. @dmurga Unfair Characteristics Unfair Focus (See pubs by my colleagues Henriette Cramer, Jean Garcia-Gathright, and Sravana Reddy for more!) Fairness
- 58. @dmurga Fairness (See pubs by my colleagues Henriette Cramer, Jean Garcia-Gathright, and Sravana Reddy for more!)
- 59. @dmurga Metric All Dark F Dark M Light F Light M Error % 6.3 20.8 6.0 1.7 0.0 (See pubs by my colleagues Henriette Cramer, Jean Garcia-Gathright, and Sravana Reddy for more!) Unfair Focus Fairness
- 60. @dmurga Metric All Dark F Dark M Light F Light M Error % 6.3 20.8 6.0 1.7 0.0 (See pubs by my colleagues Henriette Cramer, Jean Garcia-Gathright, and Sravana Reddy for more!) Unfair Characteristics Unfair Focus Fairness
- 61. @dmurga Legal compliance Why be diverse & inclusive?
- 62. @dmurga Values responsibility Legal compliance Why be diverse & inclusive?
- 63. @dmurga Market understanding Values responsibility Legal compliance Why be diverse & inclusive?
- 64. @dmurga Strategic advantage Market understanding Values responsibility Legal compliance Why be diverse & inclusive?
- 65. @dmurga How to be diverse & inclusive? Ally Affected Individual(s) Source (Source: Kenji Yoshino, NYU)
- 66. @dmurga How to be diverse & inclusive? Ally Affected Individual(s) Source Am I being an ally to them, separating intent from impact? (Source: Kenji Yoshino, NYU)
- 67. @dmurga How to be diverse & inclusive? Ally Have I reflected on my role? Affected Individual(s) Source Am I being an ally to them, separating intent from impact? (Source: Kenji Yoshino, NYU)
- 68. @dmurga How to be diverse & inclusive? Ally Have I reflected on my role? Affected Individual(s) Am I helping in a way they want? Source Am I being an ally to them, separating intent from impact? (Source: Kenji Yoshino, NYU)
- 69. @dmurga Mission: to unlock the potential of human creativity Vision: a million creative artists living off their art and billions of fans enjoying and being inspired by it. Values: Sincere, Passionate, Innovative, Collaborative, Playful Culture
- 70. @dmurga 1. Love customers even more than code 2. Love results even more than research 3. Love values even more than value Characteristics of Mission-Driven MLers
- 71. Thanks! Questions? David Murgatroyd (@dmurga) Suggestions: How does culture manifest in the Boston office? What about folks who just want to code? How do you help non-engineers align with this? How do you balance alignment and autonomy in practice? We’re hiring!
Editor's Notes
- ML has a lot of potential to do good for the world but it can also do bad. We need mission-driven machine learning folks to help ensure it’s the former. How do you know if you’re one?
- Mission-driven Machine Learning Mission Product Design Metrics Org Values Culture Fair
- But why?
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Customer-focused, not customer-obsessed
- Customer-focused, not customer-obsessed
- What user needs can ML address? Assisting Automating Aggregating Anticipating
- What user needs can ML address? Assisting Automating Aggregating Anticipating
- What user needs can ML address? Assisting Automating Aggregating Anticipating
- What user needs can ML address? Assisting Automating Aggregating Anticipating
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- Like McKinsey’s three horizons for growth
- What kinds of ways can global and local models combine? Serial serve time : High recall (scale), high precision Serial train time: Pre-built and adapt Parallel serve & train: Ensemble How do you train Product, Design, etc., for ML Product development? Distinguish how to build ML from how to interact with ML What relation does org size have to tool source? Bigger the org the more in house, smaller org the less