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![IN THE WAY THAT THE FLASHING CURSOR
BECAME THE STARTING POINT FOR
[DESKTOP], WE BELIEVE THAT THE
CAMERA SCREEN WILL BE THE STARTING
POINT FOR…SMARTPHONES.”
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Images in the Era of the Algorithm
The document discusses the impact of algorithms and machine learning on image creation, perception, and decision-making. It emphasizes the importance of designing for imperfection and uncertainty, urging users to critically engage with technology and broaden the conversation around data representation. The author advocates for collaborative input from diverse fields to mitigate bias and ensure technology reflects a more inclusive reality.
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Images in the Era of the Algorithm
- 1. Images in the Eraof the Algorithm Josh Clark Principal, Big Medium
- 2. IMAGES IN THE ERAOF THE ALGORITHM josh clark @bigmediumjosh bigmedium.com
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- 10. MACHINE LEARNING IS THENEW DESIGN MATERIAL
- 11. MACHINES THAT SEE MACHINESTHAT CREATE MACHINES THAT DECIDE images + algorithms
- 12. THE CAMERA IS THEINTERFACE 1. machines that see
- 13. PHOTOS ARE THE CREATIVEUNIT OF MOBILE
- 14. IN THE WAYTHAT THE FLASHING CURSOR BECAME THE STARTING POINT FOR [DESKTOP], WE BELIEVE THAT THE CAMERA SCREEN WILL BE THE STARTING POINT FOR…SMARTPHONES.” Snapchat public offering “
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- 18. WHAT CAN WE THEIMAGE? INFER FROM
- 19. WHAT CAN WE THEIMAGE? IMPOSE UPON
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- 31. YOU DON’T HAVE TOBE A SCIENTIST
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- 43. USE THE CAMERAAS UI PLAY WITH THE APIS EMBRACE UNCERTAINTY do this today
- 44. THE ARTIST ASA YOUNG ROBOT 2. machines that create
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- 51. Google Pixel BudsTranslate youtu.be/kWb1ysqtc4o
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- 54. EVERYONE IS GOINGTO HAVE THEIR OWN SUBJECTIVE REALITY FOR WHAT THE WORLD SOUNDS LIKE.” Fritz Lanman “ https://qz.com/870552/doppler-labs-wants-to-put-two-extra-brains-in-your-ears/
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- 72. EVERYONE IS GOINGTO HAVE THEIR OWN SUBJECTIVE REALITY FOR WHAT THE WORLD SOUNDS LIKE.” Fritz Lanman “ https://qz.com/870552/doppler-labs-wants-to-put-two-extra-brains-in-your-ears/
- 73. CAN WE NO LONGERTRUST IMAGES?
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- 77. SPLASH IN PUDDLES BETRANSPARENT BE CRITICAL do this today
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- 80. THE MACHINES KNOW ONLYWHAT WE FEED THEM
- 81. I WANT TOGET MY HEART WITH YOU. YOU ARE SO BEAUTIFUL THAT YOU KNOW WHAT I MEAN. YOU MUST BE A TRINGLE? CAUSE YOU’RE THE ONLY THING HERE. YOU LOOK LIKE A THING AND I LOVE YOU. A neural network’s pickup lines “ http://lewisandquark.tumblr.com/post/159302925452/the-neural-network-generated-pickup-lines-that-are
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- 84. WHAT IF NORMAL ISGARBAGE?
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- 90. IMPOSE BIAS THAT FAVORSTHE WORLD WE WANT
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- 98. I WANT MOREPHILOSOPHERS & PSYCHOLOGISTS & POETS & ARTISTS & POLITICIANS & ANTHROPOLOGISTS & SOCIAL SCIENTISTS & CRITICS OF ART.” Genevieve Bell “ https://www.oreilly.com/ideas/genevieve-bell-on-moving-from-human-computer-interactions-to-human-computer-relationships
- 99. MAKE IT EASY TOCONTRIBUTE (ACCURATE) DATA
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- 101. THE MACHINES KNOW ONLYWHAT WE FEED THEM
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- 103. YOU ARE THEPRODUCT
- 104. YOU ARE THEPRODUCT YOU ARE THE TRAINING DATA
- 105. BE LOYAL TO THEUSER
- 106. ROOT OUT BIAS BROADENYOUR DATA BROADEN YOUR TEAM TAKE RESPONSIBILITY do this today
- 107. THIS IS ATIME FOR WILD IDEAS
- 108. IF WE DON’TDECIDE FOR OURSELVES, THE TECHNOLOGY WILL DECIDE FOR US
- 109. THE FUTURE SHOULD NOTBE SELF-DRIVING
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