Data Natives 2015: Predictive Applications are Going to Steal Your Job: this is what you need to know
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Fears of robots taking away blue collar jobs have been coming and going over the last decade. But this time it’s different: a new breed of predictive applications, or white-collar robots are going after knowledge-worker and managerial jobs. Using automated data-driven decisions, they speed up and improve critical business processes and leave employers and employee’s scratching their heads what is coming next. Lars Trieloff, who is building predictive applications for a living at Blue Yonder explains what happens, why it happens and what it means for you (and your boss).
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Data Natives 2015: Predictive Applications are Going to Steal Your Job: this is what you need to know
- 1. Predictive Applications are going to steal your job Lars Trieloff | @trieloff @byanalytics_en
- 3. Data-Driven Decisions in Retail Pricing Replenishment Targeting
- 4. Artificial Intelligence, Real Results
- 5. Open the valves of knowledge and let wisdom flow!
- 7. IPredictive Apps are the most powerful way to use data
- 9. — Abraham Maslov – probably never said this. It’s true anyway. “Data has Human Needs, too”
- 12. More than half of the apps on a typical iPhone home screen are predictive applications.
- 13. IIMachines are working faster and cheaper than humans
- 14. Example Pricing 0 4500 9000 13500 18000 Before After Cost per 1000 price changes
- 15. Example Pricing 0 12500 25000 37500 50000 Before After Cost per 1000 price changes Prices set per night
- 16. IIIThey are not just faster and cheaper, they are also better at making decisions
- 17. Decision Quality Status Quo Predictive Prescriptive Automation
- 18. — The Economist, May 2015 “The best chess players in the world are‘centaurs’, amalgamated teams of humans and algorithms.”
- 19. Decision Quality Status Quo Predictive Prescriptive Automation 'Centaurs'
- 20. — Arthur Schopenhauer “Talent hits a target no one else can hit; Genius hits a target no one else can see.”
- 21. IVAutomation used to be a“blue collar problem”, now it is becoming a“white collar problem”
- 23. I don’t work in an assembly line.
- 25. And I don’t play table tennis.
- 26. — Daniel Susskind, co-author“The Future of the Professions” “I feel deeply uncomfortable with that, but it may be that for some tasks machines can make these decisions more effectively and efficiently”
- 28. 21% of my time is spent with communication & scheduling. No way a robot could do that.
- 30. — Charles Duhigg,“The Power of Habit” “More than 40 percent of the actions people performed each day aren’t actual decisions, but habits.”
- 31. VIt’s officially time to FREAK OUT!
- 39. VIMost of our decisions are not rational
- 40. Human Decision Making has two systems – and only one is rational.
- 41. Not quite Almost there That’s it.
- 42. Quick: What do you see here?
- 44. VIIMost of our fears are not rational either
- 47. — Daniel Kahneman “Humans tend to infer the general from the particular but are reluctant to deduce the particular from the general.”
- 48. VIIIExpect huge inequality in job losses
- 50. — Carl Benedikt Frey, Oxford University “According to our estimates, about 47 percent of total US employment is at risk [of replacement by automation]”
- 52. — William Gibson “The future is already here — it's just not very evenly distributed.”
- 53. IXThe boring jobs are the first to go
- 54. No fun, lots of risk Loan officers Receptionists Paralegals Retail salespeople Taxi drivers Security guards Fast food cooks Bartenders Personal financial advisors Reporters 0 25 50 75 100
- 55. No fun, lots of risk Kreditech ChihiraAico eBrevia E-Commerce Google Self-Driving Cars iRobot Momentum Machines Monsieur Pefin Narrative Sciences 0 25 50 75 100
- 56. XSome things can’t be taken away
- 58. — Dan Pink “People are now spending about 40 percent of their time at work engaged in persuading, influencing, and convincing others. Across a range of professions, we are devoting roughly twenty-four minutes of every hour to moving others.”
- 59. Strategic Impact 0 12,5 25 37,5 50 0 20 40 60 80 Revenue Only Mostly Revenue Both Mostly Profit Profit Only
- 60. Conclusion
- 61. Predictive Applications are already here …
- 62. They will change the way we work
- 63. And let us do what we can do best: be human.