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Understanding AI with IBM Developer - Digital Discrimination: Cognitive Bias in Machine Learning

Understanding AI with IBM Developer - Digital Discrimination: Cognitive Bias in Machine Learning

Center for Open Source Data and Ai Technologies:
AI Fairness 360 Toolkit: http://aif360.mybluemix.net/
AI Explainability 360 Toolkit: http://aix360.mybluemix.net/
Watson OpenScale: https://www.ibm.com/cloud/watson-openscale/
Model Asset Exchange: http://ibm.biz/model-exchange
Data Asset Exchange: http://ibm.biz/data-exchange
LFAI Trusted AI Committee: https://bit.ly/lfai-trust
EU Guidelines for Trustworthy AI: https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai

Talk Sources:

Cognitive Bias Definition:

Podcasts/Tweets referenced/used:
Ezra Klein Show interview with Anil Dash: https://art19.com/shows/the-ezra-klein-show/episodes/663fd0b7-ee60-4e3e-b2cb-4fcb4040eef1


Data for Black Lives
2019 Conference Notes: https://docs.google.com/document/d/1E1mfgTp73QFRmNBunl8cIpyUmDos28rekidux0voTsg/edit?ts=5c39f92e

Gender Shades Project
MIT Media Lab Overview for the project: https://www.youtube.com/watch?time_continue=1&v=TWWsW1w-BVo
FAT* 2018 Talk about outcomes: https://www.youtube.com/watch?v=Af2VmR-iGkY

Other resources referenced in this talk:

Maureen McElaney

April 21, 2020

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  1. A cognitive bias is a systematic pattern of deviation from

    norm or rationality in judgment. People make decisions given their limited resources. Wilke A. and Mata R. (2012) “Cognitive Bias”, Clarkson University 3 @Mo_Mack
  2. BLACK VS. WHITE DEFENDANTS ◦ Falsely labeled black defendants as

    likely of future crime at twice the rate as white defendants. ◦ White defendants mislabeled as low risk more than black defendants ◦ Pegged Black defendants 77% more likely to be at risk of committing future violent crime 12 @Mo_Mack
  3. 13

  4. “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.” 16 - Joy Boulamwini @jovialjoy
  5. “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.” 26 - Candice Morgan @Candice_MMorgan @Mo_Mack
  6. EU Ethics Guidelines for Trustworthy Artificial Intelligence According to the

    Guidelines, trustworthy AI should be: (1) lawful - respecting all applicable laws and regulations (2) ethical - respecting ethical principles and values (3) robust - both from a technical perspective while taking into account its social environment Source: ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai
  7. #1 - Human agency and oversight. #2 - Technical robustness

    and safety. #3 - Privacy and data governance. #4 - Transparency . 29 @Mo_Mack #5 - Diversity, non- discrimination and fairness. #6 - Societal and environmental well-being. #7 - Accountability
  8. Machine Learning Pipeline In- Processing Pre- Processing Post- Processing 35

    Modifying the training data. Modifying the learning algorithm. Modifying the predictions (or outcomes.) @Mo_Mack
  9. 49 IBM’s AI Portfolio Everything you need for Enterprise AI,

    on any cloud Watson Studio Watson Machine Learning Watson AI OpenScale Build Deploy Manage Interact with Pre-built AI Services Watson Application Services Unify on a Multicloud Data Platform IBM Cloud Private for Data AI Open Source Frameworks
  10. © 2018 IBM Corporation 30 April 2019 IBM Data Science

    Elite 50 Need help? IBM Data Science & AI Elite team. Find them: community.ibm.com/DSE
  11. 51 Photo by rawpixel on Unsplash No matter what it

    is our responsibility to build systems that are fair.
  12. Thank you! Any questions for me? @Mo_Mack Find my team:

    @ibmcodait Trusted AI Projects: ibm.biz/codait-trusted-ai 52