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How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017

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While artificial intelligence for self-driving cars and virtual assistants gets a lot of the notion of communicating the needs, effectiveness and measurements is complicated when speaking “geek”! The work of an analyst, however, does not just involve conducting data analysis within but communicating, championing and speaking simply when talking to the organization, clients and management.

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How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017

  1. 1. How To Talk about A.I. to Non-Analysts Jesse Wolfersberger Senior Director, Decision Sciences Maritz Motivation Solutions
  2. 2. 2 Maritz Motivation Solutions What does Maritz do? Conferences and Incentive Travel Maritz Global Events Customer Experience Survey Research Maritz CX Loyalty Programs, Sales Effectiveness, and Employee Engagment
  3. 3. Why does this matter? Couldn’t we keep this to ourselves? A.I. is too important. Exclusion breeds contempt. Don’t be the mean girls in high school.
  4. 4. “A.I. is the new electricity. Just as electricity transformed industry after industry 100 years ago, I think A.I. will do the same.” - Andrew Ng, Computer Science Pioneer
  5. 5. 5 • Explain the stakes • Six Tips • Five Do’s and Five Don’ts Today’s Agenda
  6. 6. 6 Tip #1 Gage the A.I. sophistication level of your audience
  7. 7. 7 Communication is Non-trivial
  8. 8. 8 Communication is Non-trivial
  9. 9. 9 Tip #2 Use tangible examples. The human brain is wired for stories.
  10. 10. 10 You’re already using A.I.
  11. 11. 11 Tip #3 The future is scary, the present is not.
  12. 12. 12 Targeting using A.I. in auto industry Probability Range No. of Participants 90-100% 1,848 80-89% 855 70-79% 996 60-69% 3,453 50-59% 10,026 40-49% 21,067 30-39% 38,077 20-29% 78,590 10-19% 256,634 9% 66,660 8% 69,719 7% 87,339 6% 124,268 5% 186,588 4% 278,998 3% 459,931 2% 976,121 1% 1,605,443 0% 1,126,638 TOTAL 5,393,251 5 Million Program Members Who will buy a car this year? 95.5% Accuracy
  13. 13. 13 Tip #4 Focus on the use, not the methodology.
  14. 14. 14 A Tale of Two Client Meetings
  15. 15. 15 A Tale of Two Client Meetings “The majority of Kaggle winners use XGBoost.”
  16. 16. 16 Tip #5 Don’t try to explain algorithms.
  17. 17. 17 The Complexity Tradeoff Simple Quick Understandable Complex Thorough Accurate “For every $1k you spend on this campaign, retention rises by one percent” “The algorithm can predict with 99.6% accuracy who will leave the program” “Last year our retention was 80%, so we expect 80% next year too.” Basic Averages Linear Regression Machine Learning
  18. 18. 18 The Complexity Tradeoff Simple Quick Understandable Complex Thorough Accurate Error Rate
  19. 19. 19 Tip #6 Have a discussion about the Complexity Tradeoff up front.
  20. 20. 20 Simple Quick Understandable Complex Thorough Accurate Error Rate Once you get here, finding a new variable will have more impact than running another model.
  21. 21. Do’s and Don’ts
  22. 22. 22 DON’T: Worry about A.I. vocabulary
  23. 23. 23 DO: Spark curiosity and create more experts
  24. 24. 24 DON’T: Focus on Watson, Hal 9000, Jarvis, or Commander Data
  25. 25. 25 DO: Give tangible, in-use-today examples experiments.withgoogle.com/ai
  26. 26. 26 DON’T: Shock and awe with doomsday scenarios
  27. 27. 27 DO: Convey how quickly A.I. will become commonplace
  28. 28. 28 DON’T: Assume everyone is excited about A.I.
  29. 29. 29 DO: Present results and promote your wins
  30. 30. 30 DON’T: Give people homework
  31. 31. 31 DO: Give people a version they can tell their boss.
  32. 32. Thank You Jesse.Wolfersberger@maritz.com @jesseberger

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