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Who Automates the Automators? (Quis Automatiet Ipsos Automates?)

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Who Automates the Automators? (Quis Automatiet Ipsos Automates?)

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Who automates the automators? For a lot of people the future seems uncertain: automation may eat their jobs. Old and new industries are ripe for disruption: transportation, healthcare, education, finance, law and even the culinary industry are being automated as we speak. When chauffeurs and truck drivers fear that they won't be able to hitch a ride into the future, should the automators perhaps wonder... when is it our turn to be automated? Who automates the automators?

Martijn Dashorst takes a look at the future of the programmer: are we also without a job when the last doctor, lawyer, 3-star chef and driver have been automated?

Who automates the automators? For a lot of people the future seems uncertain: automation may eat their jobs. Old and new industries are ripe for disruption: transportation, healthcare, education, finance, law and even the culinary industry are being automated as we speak. When chauffeurs and truck drivers fear that they won't be able to hitch a ride into the future, should the automators perhaps wonder... when is it our turn to be automated? Who automates the automators?

Martijn Dashorst takes a look at the future of the programmer: are we also without a job when the last doctor, lawyer, 3-star chef and driver have been automated?

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Who Automates the Automators? (Quis Automatiet Ipsos Automates?)

  1. 1. QUISAUTOMATIETIPSOS AUTOMATES?
  2. 2. MARTIJN DASHORST Martijn Dashorst has been involved with Apache Wicket since it was made open source over ten years ago. He is a proud developer for over 18 years. At Topicus he helps maintain and create Wicket applications for the majority of educational professionals in the Netherlands. Martijn has evangelised Wicket at numerous conferences, including JavaOne, Devoxx
  3. 3. TOPICUS
  4. 4. THISISTHE DROIDYOU'RE LOOKINGFOR!
  5. 5. BEFOREIBEGIN...
  6. 6. FUTURISTIC BUZZWORDBINGO
  7. 7. FUTURISTIC BUZZWORD BINGO
  8. 8. WATSON DEEP LEARNING INTERNET
 OF
 THINGS SINGULARITY JEOPARDY STAR TREK
 ECONOMY SELF DRIVING
 CARS JOBLESS
 FUTURE NATURAL
 LANGUAGE
 PROCESSING FUTURISTIC BUZZWORD BINGO
  9. 9. WATSON DEEP LEARNING INTERNET
 OF
 THINGS SINGULARITY JEOPARDY STAR TREK
 ECONOMY SELF DRIVING
 CARS JOBLESS
 FUTURE NATURAL
 LANGUAGE
 PROCESSING FUTURISTIC BUZZWORD BINGODRINKING GAME 🍺 🍻🍾 🍹 🍸🍼🍷 ☕ 🍻
  10. 10. WHOAUTOMATESTHE AUTOMATORS?
  11. 11. FOTO: MARKUS SPISKE
  12. 12. "IN 5-10 YEARS THERE WILL BE NO MORE PROGRAMMERS: USERS WILL BUILD SOFTWARE THEMSELVES" – MY PROFESSOR IN 1990 FOTO: MARKUS SPISKE
  13. 13. WORLD POPULATION AND
 SOCIAL DEVELOPMENT INDEX Abraham Buddha Confucius Jesus 7000 6000 5000 4000 3000 2000 1000 0 2000 1500 1000 500 0 500 1000 1500 2000 100 0 200 300 400 500 600 700 800 900 1000 Mohammed Roman Empire Mongol Empire Ottoman Empire Steam Engine Renaissance source: "The Second Machine Age", Andrew McAfee and Erik Brynjolfsson
  14. 14. "THE INDUSTRIAL REVOLUTION MADE MOCKERY OF ALL THAT HAD GONE BEFORE." –Ian Morris
  15. 15. THE FIRST MACHINE AGE AMPLIFIED MUSCLE POWER INFINITELY
  16. 16. "Nowcomesthesecondmachineage.Computers andotherdigitaladvancesaredoingtomental powerwhatthesteamengineandits descendantsdidformusclepower." –McAfee&Brynjolfsson
  17. 17. THESECOND MACHINEAGE
  18. 18. 2004
  19. 19. "Executingaleftturnacrossoncomingtraffic involvessomanyfactorsthatitishardto imaginediscoveringthesetofrulesthatcan replicate[a]driver’sbehavior." —2004,Levy&Murnane
  20. 20. 2010
  21. 21. "Conversationscriticalto effectiveteaching, managing,sellingand manyotheroccupations requirethetransferand interpretationofabroad rangeofinformation.In thesecases,thepossibility ofexchanginginformation withacomputer,rather thananotherhuman,isa longwayoff" —2004,Levy&Murnane
  22. 22. WHYNOW?
  23. 23. 3HORSEMENOF THEAUTOCALYPSE
  24. 24. EXPONENTIAL TECHNOLOGICAL PROGRESS 1 10 100 1K 10K 100K 1M 10M 100M 1G 1
  25. 25. "Butjustasittookgenerationsto improvethesteamenginetothe pointthatitcouldpowerthe IndustrialRevolution,it'salso takentimetorefineourdigital engines."
  26. 26. CRAMMINGMORE COMPONENTSONTO INTEGRATEDCIRCUITS
 SINCE1959 "The complexity for minimum component costs has increased at a rate of roughly a factor of two per year" –Gordon Moore
  27. 27. 2015-1958=32 DOUBLINGS
  28. 28. WE'RENOWENTERINGTHE SECONDHALFOFTHE CHESSBOARD
  29. 29. DIGITALISATIONOF INFORMATIONAND GOODS 2
  30. 30. When[these]thingsaredigitised—whenthey're convertedintobitsthatcanbestoredona computerandsentoveranetwork—theyacquire someweirdandwonderfulproperties.
  31. 31. Fromlocal,timelimited, resourceconstrainedavailability Toglobal,anytime,unlimited availability
  32. 32. Digitisationisinitially expensive,butthen the digitalpropertieskickin...
  33. 33. Digitalgoodsaresubjectto differenteconomics,where abundanceisthenormratherthan scarcity.
  34. 34. GLOBALINTERNETTRAFFIC2016
  35. 35. GLOBALINTERNETTRAFFIC2016 1,3ZB
  36. 36. RECOMBINATORIAL
 INNOVATION 3
  37. 37. ISINNOVATION DEAD?
  38. 38. deepnewideasortechniquesthathave thepotentialforimportantimpactson manysectorsoftheeconomy GeneralPurposeTechnologies
  39. 39. "INNOVATIONS DON'TGETUSEDUP"
  40. 40. Thetrueworkofinnovationisnot comingupwithsomethingbig andnew,butinsteadrecombining thingsthatalreadyexist.
  41. 41. GOOGLECHAUFFEUR
  42. 42. GOOGLECHAUFFEUR IPHONE
  43. 43. GOOGLECHAUFFEUR IPHONE KAHNACADEMY
  44. 44. GOOGLECHAUFFEUR IPHONE KAHNACADEMY PCR
  45. 45. CASUALTIESOFTHE SECONDMACHINEAGE
  46. 46. ENABLING
 SELFSERVICE
  47. 47. ROBOTISATION
  48. 48. Want to share your Quill Connect report with your followers? The following report is based upon an analysis of your Twitter traffic and the traffic of your recent followers. It was produced by Quill Connect, an application powered by Narrative Science Quill™. Quill Connect examined your tweet history to open a window into your own Twitter performance as well as a picture of what you and your followers are talking about and sharing. Quill examined a total of 12,016 tweets from you and your most recent followers. We can start with your standing in the "Twitterverse" in general. Your Twitter career spans eight years and you tweet more than most of your followers. You tweet 22 tweets a week while your followers average 4 per week. Further, you have 752 followers listening to you, which is very close to all Twitter users. You are in the 94th percentile of Twitter users measured by followers. Your Twitter activity this week You sent out 33 tweets this week, 15 fewer than last week, but above your weekly average. What do you and your followers tweet about? Looking at your history, you're most focused on Business & Technology, Politics, and Science. Tweets in your top topic, Business & Technology, are mostly positive in tone. Your important topics match those most tweeted about by followers who are similar to you. The chart shows the different topic distributions for you, your followers and the most aggressive retweeters among them. What is the sentiment of your tweets? Your tweets don't skew positive or negative and that neutrality puts you right in line with the sentiments of the rest of your followers. (https://quillconnect.narrativescience.com) Martijn Dashorst @dashorst (https://twitter.com/share) (https://twitter.com/share) (https://twitter.com/share) Your most influential new followers These new followers of yours reach a wide audience and are often retweeted. @weird_sci (http://twitter.com/weird_sci) 188,759 followers Popular topic: Science Twitter bio: @SpaceX Engineer & @MIT PhD Tweeting Weird & Wonderful #Science Author: http://t.co/sdWa5mCX9l New followers focusing on similar topics Out of your most recent followers, these followers tweet about the same topics as you. @aniketvarma12 (http://twitter.com/aniketvarma12) 51 followers Popular topic: Business Twitter bio: Get Crowdspell, the most amazing wordgame, https://www.narrativescience.com/quill
  49. 49. MANUFACTURINGJOBS JOURNALISTS LAWYERS TAXPREPARERS DOCTOR'SASSISTANTS JEOPARDY!PLAYERS TAXIDRIVERS TRUCKCHAUFFEURS DELIVERYGUYS CHEFS TRANSLATORS CEOS
  50. 50. CANWEBE AUTOMATED?
  51. 51. 1940'S
  52. 52. 1950'S
  53. 53. 1957:FORTRAN(FIRSTCOMPILER)
  54. 54. 1959:COBOL
  55. 55. 1972:C 1980:C++
  56. 56. 1990-:HASKELL,PYTHON, RUBY,JAVA,LUA,PHP
  57. 57. http://www.smbc-comics.com/?id=2362
  58. 58. http://www.smbc-comics.com/?id=2362
  59. 59. http://www.smbc-comics.com/?id=2362
  60. 60. http://www.smbc-comics.com/?id=2362
  61. 61. http://www.smbc-comics.com/?id=2362
  62. 62. http://www.smbc-comics.com/?id=2362
  63. 63. http://www.smbc-comics.com/?id=2362
  64. 64. http://www.smbc-comics.com/?id=2362
  65. 65. FOTO: RAPINVENT
  66. 66. FOTO: DIPTANSHU SHARMA
  67. 67. WHOWRITESDATABASE QUERIESINASSEMBLER?
  68. 68. MACHINECODE→ASSEMBLY→2NDGEN→3RDGEN SQL→JDBC→ORM SERVLETS→JSP→JSF CGI→JAVA→JAVAEE→RUBY→NODE CORBA→DCOM/RMI→SOAP→REST HTML→PHP→WORDPRESS→SQUARESPACE MANUALTESTING→JUNIT→COVERAGE→PITEST
  69. 69. HTTPS://XKCD.COM/1319/
  70. 70. CANWEBE AUTOMATED?
  71. 71. YES (WE HAVE BEEN DOING SO SINCE THE INVENTION OF COMPUTERS)
  72. 72. BUT
  73. 73. Thereisnosingledevelopment,ineither technologyormanagementtechnique, whichbyitselfpromisesevenoneorder-of- magnitudeimprovementwithinadecade inproductivity,inreliability,insimplicity. –Frederick Brooks from: 'No Silver Bullet-Essence and Accident in Software Engineering', 1986
  74. 74. Codingiswritingtextfilesinforeign languagescontaininginstructionssuitable foranabsoluteidiottofollow.Unlike humanreaders,computerscannotinfer meaningfromambiguoustext. –Stephen Nichols from: 'Coding Academies Are Nonsense', 2015
  75. 75. WHATARETHREATSTO OURJOBSECURITY?
  76. 76. SELF-SERVICE
  77. 77. ROBOTISATION
  78. 78. +STACKOVERFLOW +GITHUB +AI =?
  79. 79. CODEPHAGE
  80. 80. QUISAUTOMATIETIPSOS AUTOMATES?
  81. 81. NOS (LIBENTIUS FACIMUS)
  82. 82. WE (WILLINGLY)
  83. 83. ONEMORETHING
  84. 84. IGUESSTHEYARE OCCUPIED...
  85. 85. ...FORNOW!
  86. 86. THANKYOU!

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