IBM Twitch - Digital Discrimination: Cognitive Bias in Machine Learning

Tools:
AI Fairness 360 Toolkit: http://aif360.mybluemix.net/
Model Asset Exchange: http://ibm.biz/model-exchange
Image Segmenter Web App: https://github.com/IBM/MAX-Image-Segmenter-Web-App
Diversity in Faces Dataset: https://www.research.ibm.com/artificial-intelligence/trusted-ai/diversity-in-faces/#acces

Sources:

Podcasts
https://leanin.org/podcast-episodes/siri-is-artificial-intelligence-biased
https://art19.com/shows/the-ezra-klein-show/episodes/663fd0b7-ee60-4e3e-b2cb-4fcb4040eef1

Amazon
https://www.aclu.org/blog/privacy-technology/surveillance-technologies/amazons-face-recognition-falsely-matched-28
https://www.openmic.org/news/2019/1/16/halt-rekognition

Google
https://motherboard.vice.com/en_us/article/j5jmj8/google-artificial-intelligence-bias

COMPAS
https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
https://www.technologyreview.com/s/612775/algorithms-criminal-justice-ai/

Data for Black Lives
Conference Notes: https://docs.google.com/document/d/1E1mfgTp73QFRmNBunl8cIpyUmDos28rekidux0voTsg/edit?ts=5c39f92e

Gender Shades Project
http://news.mit.edu/2018/study-finds-gender-skin-type-bias-artificial-intelligence-systems-0212
https://www.youtube.com/watch?time_continue=1&v=TWWsW1w-BVo
https://www.ajlunited.org/fight

Other resources referenced in this talk:
https://www.nytimes.com/2018/02/12/business/computer-science-ethics-courses.html
https://www.vox.com/science-and-health/2017/4/17/15322378/how-artificial-intelligence-learns-how-to-be-racist
https://www.engadget.com/2019/01/24/pinterest-skin-tone-search-diversity/

Transcript

1. Digital Discrimination:
   Cognitive Bias in
   Machine Learning
   Maureen McElaney
   Developer Advocate, Center for
   Open-Source Data and AI Technologies
   (CODAIT)
   @Mo_Mack
   December 19, 2018 / © 2018 IBM Corporation
   

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2. HELLO!
   I am Maureen McElaney
   You can find me at:
   @Mo_Mack
   2
   

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3. Digital Discrimination
   Cognitive Bias in Machine Learning
   3
   

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4. “
   A cognitive bias is a systematic pattern of
   deviation from norm or rationality in
   judgment. Individuals create their own
   "subjective social reality" from their
   perception of the input.”
   - Wikipedia
   4
   

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5. 5
   https://twitter.com/alexisohanian/status/1087973027055316994
   

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6. Examples of Cognitive
   Bias in Machine
   Learning
   

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7. Google’s Cloud
   Natural Language
   API
   7 Image Credit: #WOCinTech
   

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8. October 2017 - Google Natural Language API
   https://cloud.google.com/natural-language/
   8
   Source: https://motherboard.vice.com/en_us/article/j5jmj8/google-artificial-intelligence-bias
   

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9. October 2017 - Google Natural Language API
   https://cloud.google.com/natural-language/
   9
   Source: https://motherboard.vice.com/en_us/article/j5jmj8/google-artificial-intelligence-bias
   

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10. October 2017 - Google Natural Language API
    https://cloud.google.com/natural-language/
    10
    Source: https://motherboard.vice.com/en_us/article/j5jmj8/google-artificial-intelligence-bias
    

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11. “
    We will correct this specific case,
    and, more broadly, building more
    inclusive algorithms is crucial to
    bringing the benefits of machine
    learning to everyone."
    11
    

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12. NorthPointe’s
    COMPAS
    Algorithm
    12 Image Credit: #WOCinTech
    

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13. May 2016 - Northpointe’s COMPAS Algorithm
    http://www.equivant.com/solutions/inmate-classification
    13
    Source:
    https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
    

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14. May 2016 - Northpointe’s COMPAS Algorithm
    http://www.equivant.com/solutions/inmate-classification
    14
    Source:
    https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
    

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15. May 2016 - Northpointe’s COMPAS Algorithm
    http://www.equivant.com/solutions/inmate-classification
    15
    Source:
    https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
    

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16. May 2016 - Northpointe’s COMPAS Algorithm
    http://www.equivant.com/solutions/inmate-classification
    16
    Source:
    https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
    

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17. 17
    Source:
    https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
    

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18. 18
    Source:
    https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
    

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20. Amazon
    Rekognition
    20 Image Credit: #WOCinTech
    

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21. July 2018 - Amazon Rekognition
    https://aws.amazon.com/rekognition/
    21
    Source: https://www.aclu.org/blog/privacy-technology/surveillance-technologies/amazons-face-recognition-falsely-matched-28
    

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22. January 2019 - Amazon Rekognition
    https://aws.amazon.com/rekognition/
    22
    Source: https://www.openmic.org/news/2019/1/16/halt-rekognition
    

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23. Joy Buolamwini,
    Algorithmic Justice League
    Gender Shades Project
    Released February 2018
    23
    

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25. “
    We have entered the age of automation
    overconfident, yet underprepared. If we fail
    to make ethical and inclusive artificial
    intelligence we risk losing gains made in civil
    rights and gender equity under the guise of
    machine neutrality.” - @jovialjoy
    25
    

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26. SOLUTIONS?
    26
    What can we do to combat bias in AI?
    

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27. 27
    https://art19.com/shows/the-ezra-klein-show/episodes/663fd0b7-ee60-4e3e-b2cb-4fcb4040eef1
    

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28. “
    Coders are the most empowered
    laborers that have ever existed."
    - @anildash
    28
    

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29. EDUCATION IS
    KEY
    29 Image Credit: #WOCinTech
    

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30. 30
    https://www.nytimes.com/2018/02/12/business/computer-science-ethics-courses.html
    

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31. QUESTIONS POSED TO
    STUDENTS
    ○ Is the technology fair?
    ○ How do you make sure that the data is not
    biased?
    ○ Should machines be judging humans?
    31
    

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32. 32
    https://twitter.com/Neurosarda/status/1084198368526680064
    

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33. FIX THE
    PIPELINE?
    33 Image Credit: #WOCinTech
    

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34. Rediet Abebe, Black in AI
    “Cognitive bias in machine learning is human bias on
    steroids.” - @red_abebe
    34
    

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35. January 2019 - New Search Feature on
    https://www.pinterest.com/
    35
    Source: https://www.engadget.com/2019/01/24/pinterest-skin-tone-search-diversity/
    

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36. “
    "By combining the latest in machine
    learning and inclusive product
    development, we're able to directly
    respond to Pinner feedback and
    build a more useful product."
    - Pinterest
    36
    

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37. TOOLS TO
    COMBAT BIAS
    37 Image Credit: #WOCinTech
    

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38. TOOL #1:
    AI Fairness 360 Toolkit
    Open Source Library
    

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39. http://aif360.mybluemix.net/
    

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41. TYPES OF METRICS
    ○ Individual vs. Group Fairness, or Both
    ○ Group Fairness: Data vs Model
    ○ Group Fairness: We’re All Equal vs What
    You See is What You Get
    ○ Group Fairness: Ratios vs Differences
    41
    

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44. Machine Learning Pipeline
    In-
    Processing
    Pre-
    Processing
    Post-
    Processing
    44
    Modifying the
    training data.
    Modifying the
    learning
    algorithm.
    Modifying the
    predictions (or
    outcomes.)
    

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46. DEMO
    http://aif360.mybluemix.net/
    

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47. https://github.com
    /IBM/AIF360
    AI Fairness 360 Toolkit Public Repo
    47
    

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48. http://aif360.mybluemix.
    net/community
    AI Fairness 360 Slack Community
    48
    

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49. TOOL #2:
    Model Asset Exchange
    Open Source Pre-Trained Deep Learning
    Models
    

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50. http://ibm.biz/model-exchange
    

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51. http://ibm.biz/model-exchange
    

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52. https://github.com/IBM/MAX-Image-Segmenter-Web-App
    

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53. https://github.com/IBM/MAX-Image-Segmenter-Web-App
    

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54. http://ibm.biz/
    model-exchange
    Model Asset eXchange
    54
    

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55. TOOL #3:
    Diversity in Faces
    Dataset
    Diverse dataset available to the global
    research community.
    

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56. Diversity in Faces Dataset
    Studying diversity in faces is complex. The dataset
    provides a jumping off point for the global research
    community to further our collective knowledge.
    56
    

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57. https://www.research.ib
    m.com/artificial-intellige
    nce/trusted-ai/diversity-i
    n-faces/#access
    Diversity in Faces Dataset
    57
    

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58. UPDATE TO THE
    GENDER SHADES
    PROJECT
    58 Image Credit: #WOCinTech
    

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59. 59
    http://www.aies-conference.com/wp-content/uploads/2019/01/AIES-19_paper_223.pdf
    

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60. 60
    https://www.ajlunited.org/fight
    

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61. 61
    Photo by rawpixel on Unsplash
    

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62. Links to Sources:
    Podcasts
    ○ https://leanin.org/podcast-episodes/siri-is-artificial-intelligence-biased
    ○ https://art19.com/shows/the-ezra-klein-show/episodes/663fd0b7-ee60-4e3e-b2cb-4fcb4040eef1
    Amazon
    ○ https://www.aclu.org/blog/privacy-technology/surveillance-technologies/amazons-face-recognition-falsely-matched
    -28
    ○ https://www.openmic.org/news/2019/1/16/halt-rekognition
    Google
    ○ https://motherboard.vice.com/en_us/article/j5jmj8/google-artificial-intelligence-bias
    COMPAS
    ○ https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
    ○ https://www.technologyreview.com/s/612775/algorithms-criminal-justice-ai/
    Data for Black Lives
    ○ Conference Notes:
    https://docs.google.com/document/d/1E1mfgTp73QFRmNBunl8cIpyUmDos28rekidux0voTsg/edit?ts=5c39f92e
    Gender Shades Project
    ○ http://news.mit.edu/2018/study-finds-gender-skin-type-bias-artificial-intelligence-systems-0212
    ○ https://www.youtube.com/watch?time_continue=1&v=TWWsW1w-BVo
    ○ https://www.ajlunited.org/fight
    ○ https://www.nytimes.com/2018/02/12/business/computer-science-ethics-courses.html
    ○ https://www.vox.com/science-and-health/2017/4/17/15322378/how-artificial-intelligence-learns-how-to-be-racist
    ○ https://www.engadget.com/2019/01/24/pinterest-skin-tone-search-diversity/
    62
    

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63. THANKS!
    Slides and Links:
    http://bit.ly/ibm-twitch-bias
    Any questions?
    You can find me at:
    @Mo_Mack
    63
    

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