THE AI THAT WENT OUT TO DESTROY MANKIND

Slides for my Talk about AI at Code.Talks 2019 in Hamburg.

Transcript

1. THE AI
   THAT WENT
   OUT TO DESTROY
   MANKIND
   Carsten Sandtner \\ @casarock
   Photo by Franck V. on Unsplash
   

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2. „ “
   @casarock
   Hi, I am Carsten, I’m a father of two, a
   technical director and always curious
   about new technologies since the 80s!
   

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4. 68 YEARS AGO
   

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5. AI WINTER IN 70S
   

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7. CURRENTLY THERE IS NO
   DEFINITION OF AI AVAILABLE
   

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8. „ “
   https://en.wikipedia.org/wiki/Artificial\_intelligence
   In computer science, artificial intelligence
   (AI), sometimes called machine
   intelligence, is intelligence demonstrated
   by machines, in contrast to the natural
   intelligence displayed by humans.
   

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9. „ “
   https://www.techopedia.com/definition/190/artificial-intelligence-ai
   Artificial intelligence (AI) is an area of
   computer science that emphasizes the
   creation of intelligent machines that work
   and react like humans.
   

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10. „ “
    https://www.britannica.com/technology/artificial-intelligence
    Artificial intelligence (AI), the ability of a
    digital computer or computer-controlled
    robot to perform tasks commonly
    associated with intelligent beings.
    

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11. „ “
    https://www.merriam-webster.com/dictionary/artificial%20intelligence
    the capability of a machine to imitate
    intelligent human behavior
    

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12. AI
    Machine
    Learning
    Deep
    Learning
    

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13. NEURON
    Neuron
    Activation
    Function
    Output
    Input Weight
    Offset
    z = ∑wixi
    w0
    x0
    +b
    y = f(z)
    y0
    x1
    xn
    w1
    wn
    y1
    yn
    LAYER
    

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14. . . . .
    Input Layer Output Layer
    Hidden Layers
    

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15. . . . .
    Input Layer Output Layer
    Hidden Layers
    Forward pass
    Init with random weights and offsets
    

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16. . . . .
    Input Layer Output Layer
    Hidden Layers
    Back propagation
    Propagate the error into every neuron
    err
    err
    err
    err
    err
    err
    err
    err
    err
    err
    err
    

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17. AND THERE ARE CONVOLUTIONAL
    NEURAL NETWORKS…
    

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18. CONVOLUTIONAL NEURAL NETWORK
    Conv
    ReLu
    Pool
    Conv
    Conv
    Conv
    Conv
    Conv
    ReLu
    ReLu
    ReLu
    ReLu
    ReLu
    Pool
    Pool
    Dog
    Cat
    Mouse
    FC
    

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19. REINFORCEMENT LEARNING
    

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20. Photo by arland https://flic.kr/p/7zY4yo
    

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21. © by Deepmind: https://deepmind.com/blog/article/alphago-zero-starting-scratch
    

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22. BRAIN VS. AI
    

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23. BRAIN VS. AI
    Neurons
    Cockroaches: ~1 Million
    Cats: ~1 Billion
    Elephants: ~23 Billion
    Humans: ~86 Billion Neurons
    

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25. DATA, DATA, DATA!
    

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26. G-MAFIA
    Image by Vitabello from Pixabay
    

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27. BAT
    Photo by Todd Cravens on Unsplash
    

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28. „ “
    –Amy Webb
    The G-MAFIA is beholden to capitalist
    market forces; the BAT serves the will of
    the Chinese government.
    

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29. „ “
    –Amy Webb
    The robots will come and kill us all, but not
    before they take all our jobs.
    

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30. REALLY?
    

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31. „ “
    –Frithjof Bergmann
    The aim of the new work is not to free
    people from work, but to transform work to
    produce free, self-determined human
    beings.
    

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32. TUMOR DETECTION
    

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33. QUALITY ASSURANCE
    

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34. SELF DRIVING CARS
    

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35. CRIME PREDICTION
    
    

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36. . . . .
    Input Layer Output Layer
    Hidden Layers
    

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37. Photo by Katie Salerno
    https://www.pexels.com/photo/love-people-romance-engagement-18396/
    

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38. MICROSOFT TAY
    https://twitter.com/geraldmellor/status/712880710328139776
    

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39. BOTS CREATED AN OWN LANGUAGE!
    https://ai.googleblog.com/2016/09/a-neural-network-for-machine.html
    

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40. INTERVIEW WITH A
    MACHINE…
    

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41. …DON’T BE UNIQUE!
    

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42. https://www.youtube.com/watch?v=TWWsW1w-BVo
    

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43. WHO IS RESPONSIBLE?
    

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44. GETTING MORE DATA!
    

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45. Photo by sebastiaan stam from Pexels
    

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46. VOICES - I HEAR VOICES
    https://ai.googleblog.com/2018/05/duplex-ai-system-for-natural-conversation.html
    

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47. https://twitter.com/zeynep/status/994236536072953856
    

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48. https://www.nytimes.com/2019/05/22/technology/personaltech/ai-google-duplex.html
    

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49. By Carafe at English Wikipedia, CC BY-SA 3.0,
    https://commons.wikimedia.org/w/index.php?curid=7860391
    

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50. HUMANS ARE
    THE WEAK SPOT!
    

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51. WHAT COULD POSSIBLY
    GO WRONG?
    

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52. https://www.youtube.com/watch?v=dPkK8iohYLE
    

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53. https://www.youtube.com/watch?v=5rPKeUXjEvE
    

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54. NEW DIMENSION OF FAKE NEWS,
    MOBBING AND HARASSMENT
    

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55. WYSINWYG
    

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56. U.S. Air Force photo by Bobbi Zapka [Public domain]

    https://commons.wikimedia.org/wiki/File:Global_Hawk_1.jpg
    

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57. https://www.youtube.com/watch?v=9CO6M2HsoIA
    

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58. Photo by Cade Roberts on Unsplash
    https://unsplash.com/photos/H0Aud5lhupc
    

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60. AZURE COGNITIVE SERVICES
    https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/
    

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61. AUDIO TRANSCRIPTION
    https://aws.amazon.com/de/transcribe/
    

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62. AND VICE VERSA
    https://aws.amazon.com/en/polly/
    

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63. AND MANY MANY MORE
    https://cloud.google.com/products/ai/
    https://azure.microsoft.com/en-us/services/cognitive-services/
    https://aws.amazon.com/en/machine-learning/
    

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64. Photo by Martin Shreder on Unsplash
    https://unsplash.com/photos/5Xwaj9gaR0g
    

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65. BUT? WHAT ABOUT
    DESTROYING MANKIND?
    

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66. POSSIBLE MASTERPLAN
    Analyze politics/mood of humans
    Manipulate with deep fakes & fake news
    Organise „terrorist attacks“ with
    autonomous drones/weapons
    Wait until humans destroyed themselves!
    Alternative: Wait for the climate collapse…
    

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67. WHATEVER WE USE, WE
    HAVE TO USE IT WISELY!
    

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68. THANK YOU.
    @casarock

    http://sandtner.net
    NOW LET’S PARTY!
    

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