THE AI THAT WENT OUT TO DESTROY MANKIND

Transcript

1. THE AI THAT WENT OUT TO DESTROY MANKIND Carsten Sandtner

   \\ @casarock Photo by Franck V. on Unsplash

2. „ “ @casarock Hi, I am Carsten, I’m a father

   of two, a technical director and always curious about new technologies since the 80s!
3. None

4. 68 YEARS AGO

5. AI WINTER IN 70S

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7. CURRENTLY THERE IS NO DEFINITION OF AI AVAILABLE

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.

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.

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.

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

    intelligent human behavior

12. AI Machine Learning Deep Learning

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

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

15. . . . . Input Layer Output Layer Hidden Layers

    Forward pass Init with random weights and offsets

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

17. AND THERE ARE CONVOLUTIONAL NEURAL NETWORKS…

18. CONVOLUTIONAL NEURAL NETWORK Conv ReLu Pool Conv Conv Conv Conv

    Conv ReLu ReLu ReLu ReLu ReLu Pool Pool Dog Cat Mouse FC

19. REINFORCEMENT LEARNING

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

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

22. BRAIN VS. AI

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!

26. G-MAFIA Image by Vitabello from Pixabay

27. BAT Photo by Todd Cravens on Unsplash

28. „ “ –Amy Webb The G-MAFIA is beholden to capitalist

    market forces; the BAT serves the will of the Chinese government.

29. „ “ –Amy Webb The robots will come and kill

    us all, but not before they take all our jobs.

30. REALLY?

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.

32. TUMOR DETECTION

33. QUALITY ASSURANCE

34. SELF DRIVING CARS

35. CRIME PREDICTION

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

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

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

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

40. INTERVIEW WITH A MACHINE…

41. …DON’T BE UNIQUE!

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

43. WHO IS RESPONSIBLE?

44. GETTING MORE DATA!

45. Photo by sebastiaan stam from Pexels

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

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

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

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

50. HUMANS ARE THE WEAK SPOT!

51. WHAT COULD POSSIBLY GO WRONG?

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

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

54. NEW DIMENSION OF FAKE NEWS, MOBBING AND HARASSMENT

55. WYSINWYG

56. U.S. Air Force photo by Bobbi Zapka [Public domain]
 https://commons.wikimedia.org/wiki/File:Global_Hawk_1.jpg

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

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/

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

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

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/

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

65. BUT? WHAT ABOUT DESTROYING MANKIND?

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…

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

68. THANK YOU. @casarock
 http://sandtner.net NOW LET’S PARTY!