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Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019

How can we, as designers, create artificially intelligent systems that don’t hurt humans? What should we think about to make these systems transparent? What information needs to be available to users to engender trust? This talk proposes a model for talking about the major decision points in building an AI.

Carol will tackle the biggest challenges inherent with AI including issues of ethics and the implications for your work. Wondering why you keep hearing about the Trolley Problem? Has someone claimed that your AI is nearly sentient? Bring your questions and curiosity for this engaging evening, and she’ll warn you before spoilers of The Good Place (©2019 NBCUniversal Media, LLC).

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Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019

  1. 1. Designing Trustable AI Experiences Carol Smith @carologic IxDA Pittsburgh, January 24, 2019 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License except where noted otherwise.
  2. 2. Designing Trustable AI Experiences / @carologic Humanity…
  3. 3. AI is as imperfect as the humans making it
  4. 4. Designing Trustable AI Experiences / @carologic What is AI?
  5. 5. AI is present when computers/machines – Exhibit intelligence – Perceive their environment – Take actions/make decision to maximize chance of success at goal
  6. 6. Designing Trustable AI Experiences / @carologic AI/Cognitive computers are Algorithms Know ONLY what you teach Control ONLY what given control of Aware of nuances and can continue to learn
  7. 7. Designing Trustable AI Experiences / @carologic Types of AI Image: Best Artificial Intelligence Software, © 2019 G2 Crowd, Inc. All rights reserved
  8. 8. Dynamic Data + training - Apply to new situations
  9. 9. Designing Trustable AI Experiences / @carologic Taxonomies and Ontologies coming to life (NOT like humans learn) Photo:
  10. 10. Not sentient Not unknowable black box
  11. 11. “We need AI for that!”
  12. 12. Designing Trustable AI Experiences / @carologic Like Any Good Design Understand people and problem deeply Build right AI system Different problems require different systems
  13. 13. Designing Trustable AI Experiences / @carologic Major Decision Points Content and curation TrainingManagement
  14. 14. Designing Trustable AI Experiences / @carologic Ethics and Morals
  15. 15. Trolley Problem Trolley Car 36, Rockford, Illinois Does the Trolley Problem Have a Problem? What if your answer to an absurd hypothetical question had no bearing on how you behaved in real life? By Daniel Engber. June 18, 2018. Image of anxious hypothetical trolley car lever operator by Lisa Larson-Walker
  16. 16. NSF…
  17. 17. Designing Trustable AI Experiences / @carologic Designing for Trust
  18. 18. Designing Trustable AI Experiences / @carologic Provide Transparency Who What When* Why How *Where isn’t typically applicable
  19. 19. Designing Trustable AI Experiences / @carologic Content and Curation Content and curation TrainingManagement
  20. 20. Designing Trustable AI Experiences / @carologic Content Source Exists Available Quantity Quality Photo by sunlightfoundation
  21. 21. Designing Trustable AI Experiences / @carologic Number Five “Needs Input” Short Circuit (1986 film) Ally Sheedy and Number Five (Tim Blaney)
  22. 22. all Content all Data all AI = Biased
  23. 23. Social class, resource availability Race, Gender, Sexuality Culture, Theology, Tradition More…
  24. 24. Designing Trustable AI Experiences / @carologic Who: Creation and Curation Respected experts Diverse backgrounds
  25. 25. Designing Trustable AI Experiences / @carologic Humans required to teach and monitor AI Water Prune/Shape Cull
  26. 26. Only as good as data and time spent improving it
  27. 27. Designing Trustable AI Experiences / @carologic Training and Accuracy Content and curation TrainingManagement
  28. 28. Designing Trustable AI Experiences / @carologic Experts to train system Vetting Availability Process Maintain quality
  29. 29. who doesn’t bring cookies Accuracy Similar to cloning a colleague no-bake cookies photo by Melissa Hillier - recipe blogged at mXw1- cgk3ow-6kzJog-6kA5oZ-aYqEpT-MMkVVV-7aQLnM-ecL6fm-6kEd67-5ykEkC-2bsTnp3-dCh7J9-T4tu4i-8HdYNJ-73SMVr-6uwEGT-6kE34b-MMkEqr-6kEFws-6kEjVu-25rwHBc-6kA42g-6kzTi4-T36Moj-7Bx3rf-7vPVhb-6YNEHC-amariC-neddpV-ZNpJHE
  30. 30. Designing Trustable AI Experiences / @carologic Priority of accuracy across industries Higher Priority 90-99%+ Lower Priority 60-89% accuracy is acceptable Financial Ecommerce
  31. 31. Designing Trustable AI Experiences / @carologic Management Content and curation TrainingManagement
  32. 32. Designing Trustable AI Experiences / @carologic Responsible, Intentional Design Some rights reserved by Rocky VI - License:
  33. 33. Who gets to use our tools? Don’t be ableist How People with Disabilities Use the Web: Overview /
  34. 34. Designing Trustable AI Experiences / @carologic Privacy What must a user reveal? Who owns the data? Life expectancy of data? PAPA (Privacy, Accuracy, Property, Accessibility) Ethical Issues in IS by Richard Mason.
  35. 35. Designing Trustable AI Experiences / @carologic Bias Show awareness Acknowledge issues Overcommunicate
  36. 36. “Be uncomfortable” - Laura Kalbag Ethical design is not superficial.
  37. 37. Designing Trustable AI Experiences / @carologic Take Responsibility Desk Set (1957), Twentieth Century Fox How to Keep Your AI from Turning into a Racist Monster By Megan Garcia.
  38. 38. Designing Trustable AI Experiences / @carologic Code of Conduct / Ethics What do you value? Helping people? What lines won’t your AI cross? How will you track your progress? Inspired by “3 guiding principles for ethical AI, from IBM CEO Ginni Rometty” by Alison DeNisco. January 17, 2017, Tech Republic
  39. 39. Designing Trustable AI Experiences / @carologic Guidance UXPA Code of professional conduct ACM Code of Ethics and Professional Conduct
  40. 40. Designing Trustable AI Experiences / @carologic Hire/work with people affected by bias
  41. 41. Designing Trustable AI Experiences / @carologic Make it your business to keep people safe Monitor system Identify warning signs Use plain language
  42. 42. Designing Trustable AI Experiences / @carologic Black Mirror Brainstorms Create Black Mirror episode about misuse of your product Pair with @brownorama's "abusability testing" Tweet by @aaronzlewis:
  43. 43. Designing Trustable AI Experiences / @carologic Unintended consequences Becomes a Nazi? Who can report? To whom? Method for turning it off? Who notified? Unintended consequences of turning off? Google’s tensor processing units:
  44. 44. Designing Trustable AI Experiences / @carologic “If it’s not usable, it’s not secure.” – Jared Spool, IAS17 “Ensure humans can unplug the machines” – Grady Booch, Ted Talk Unintuitive and Insecure: Fixing the Failures of Authentication, Jared Spool, IA Summit 2017 Grady Booch, Scientist, philosopher, IBM’er
  45. 45. Designing Trustable AI Experiences / @carologic How might we engender trust? Content and curation TrainingManagement
  46. 46. Designing Trustable AI Experiences / @carologic Provide Transparency Who What When* Why How *Where isn’t typically applicable pintura - paint /blue/azul by Alexander Andrade.
  47. 47. Designing Trustable AI Experiences / @carologic Who Experience, knowledge – Content creator and curator – System trainer and manager – Report issues to – Shuts down the system
  48. 48. Designing Trustable AI Experiences / @carologic My content - Image Recognition Carol’s search for “cat” on her Google Photos account.
  49. 49. Designing Trustable AI Experiences / @carologic What Content – Source – Method of curation – AI generated vs. other – Changes – Known inherent biases Type of training Confidence Management practices Examples of potential building bias
  50. 50. Designing Trustable AI Experiences / @carologic Understanding human speech IBM Watson developed for quiz show Jeopardy Won against champions in 2011 Video: “IBM's Watson Supercomputer Destroys Humans in Jeopardy | Engadget”
  51. 51. Designing Trustable AI Experiences / @carologic When Content age System created Updated Audited Changed Mysore Clocktower - clock face By Christopher Fynn
  52. 52. Designing Trustable AI Experiences / @carologic American Tax Day (2017) H&R Block worked with IBM Watson for 2017 Tax Season
  53. 53. Designing Trustable AI Experiences / @carologic Why Decisions made Content of communications Data changed
  54. 54. Designing Trustable AI Experiences / @carologic Strategic Games 1997 Chess, IBM 2016 Go, Google Floor goban, 2007, By Goban1 Graphic, Science Magazine: versus-machine-go-match-doesn-t-matter-and-what-does
  55. 55. Designing Trustable AI Experiences / @carologic Chatbots? IA Mapping Expected language
  56. 56. Designing Trustable AI Experiences / @carologic How Address common fears Manage unintended consequences Report issues Control balance Image: 2001: A Space Odyssey (1968) “Odyssee im weltraum” – German DVD disc cover. From IMBD.
  57. 57. Designing Trustable AI Experiences / @carologic Automating labeling of birdsongs Photo by Gallo71 (Own work) [Public domain], via Wikimedia Commons
  58. 58. Designing Trustable AI Experiences / @carologic Pattern recognition Natural Language Processing Image Analysis IBM Watson
  59. 59. AI matures: Update management approach
  60. 60. Create ethical, transparent and fair AI Toward ethical, transparent and fair AI/ML: a critical reading list By Eirini Malliaraki, Feb 19 via tweet from @robmccargow transparent-and-fair-ai-ml-a-critical-reading-list-d950e70a70ea
  61. 61. Designing Trustable AI Experiences / @carologic Create ethical, transparent and fair AI Content and curation TrainingManagement
  62. 62. Designing Trustable AI Experiences / @carologic Continue the conversation... UX Breakfast! LinkedIn: CarolJSmith Twitter: @Carologic Slideshare: carologic
  63. 63. Designing Trustable AI Experiences / @carologic AI, UX – you pick
  64. 64. Designing Trustable AI Experiences / @carologic Appendix Additional Information and Resources
  65. 65. Designing Trustable AI Experiences / @carologic Explore AI - Don’t fear AI Try out tools (appendix and notes) Pair with others Teach others about AI
  66. 66. Designing Trustable AI Experiences / @carologic AI Tools • A list of artificial intelligence tools you can use today — for businesses, by Liam Hanel, July 11, 2017 on Lyr.AI %E2%80%8Afor-businesses/ and intelligence-tools-you-can-use-today-for-personal-use-1-3-7f1b60b6c94f • Best AI and machine learning tools for developers, By Christina Mercer, Sep 26, 2017 in Techworld from IDG wearables/best-ai-machine-learning-tools-for-developers-3657996/ • 15 Top Open Source Artificial Intelligence Tools by Cynthia Harvey, September 12, 2016 on Datamation top-open-source-artificial-intelligence-tools.html • IBM Watson Developer Tools (free trials):
  67. 67. Designing Trustable AI Experiences / @carologic 10 Major Milestones in the History of AI
  68. 68. Designing Trustable AI Experiences / @carologic Types of Machine Learning
  69. 69. Designing Trustable AI Experiences / @carologic Supervised Learning Specialists involved in content creation and training Programmer and/or GUI Most common Artificial Intelligence Demystified by. Rahul December 23, 2016. Analytics Vidhya
  70. 70. Designing Trustable AI Experiences / @carologic Annotating Content Image created by Angela Swindell, Visual Designer, IBM
  71. 71. Designing Trustable AI Experiences / @carologic Supervised Machine Learning - GUI Watson Knowledge Studio, Supervised Machine Learning:
  72. 72. Designing Trustable AI Experiences / @carologic Types of Machine Learning Unsupervised learning – Machine defines patterns Reinforced learning – Games – rules and rewards Artificial Intelligence Demystified by Rahul December 23, 2016. Analytics Vidhya
  73. 73. Designing Trustable AI Experiences / @carologic Deep Learning Classify objects based on features Can be applied to other types of AI Toward ethical, transparent and fair AI/ML: a critical reading list By Eirini Malliaraki, Feb 19 via tweet from @robmccargow transparent-and-fair-ai-ml-a-critical-reading-list-d950e70a70ea
  74. 74. Designing Trustable AI Experiences / @carologic Want to Know More? • The Rise Of Artificial Intelligence As A Service In The Public Cloud Rise Of Artificial Intelligence As A Service In The Public Cloud by Janakiram MSV , Forbes Article: Courses at
  75. 75. Designing Trustable AI Experiences / @carologic Humans love robots
  76. 76. Designing Trustable AI Experiences / @carologic Resources • AI​ ​Now​ ​2017​ ​Report, New York University, and AI Now 78/_AI_Now_Institute_2017_Report_.pdf • “How IBM is Competing with Google in AI.” The Information. competing-with-google-in-ai?eu=2zIDMNYNjDp7KqL4YqAXXA • “The business case for augmented intelligence” augmented-intelligence-36afa64cd675 • “Comparison of machine learning methods applied to birdsong element classification” by David Nicholson. Proceedings of the 15th Python in Science Conference (SCIPY 2016). • “Staples’ “Easy Button” Comes to Life with IBM Watson” in Business Wire, October 25, 2016. Button%E2%80%9D-Life-IBM-Watson • “How Staples Is Making Its Easy Button Even Easier With A.I.” by Chris Cancialosi, Forbes. with-a-i/#4ae66e8359ef • “Inside Intel: The Race for Faster Machine Learning”
  77. 77. Designing Trustable AI Experiences / @carologic More Resources • “Update: Why this week’s man-versus-machine Go match doesn’t matter (and what does)” by Dana Mackenzie. Science Magazine. Mar. 15, 2016 man-versus-machine-go-match-doesn-t-matter-and-what-does • “For IBM’s CTO for Watson, not a lot of value in replicating the human mind in a computer.” by Frederic Lardinois (@fredericl), TechCrunch, Posted Feb 27, 2017. for-watson-not-a-lot-of-value-in-replicating-the-human-mind-in-a-computer/ • “Google and IBM: We Want Artificial Intelligence to Help You, Not Replace You” Most Powerful Women by Michelle Toh. Mar 02, 2017. Fortune. • “Facebook scales back AI flagship after chatbots hit 70% f-AI-lure rate - 'The limitations of automation‘” by Andrew Orlowski. Feb 22, 2017. The Register • “Microsoft is deleting its AI chatbot's incredibly racist tweets” by Rob Price. Mar. 24, 2016. Business Insider UK. Special Thanks: Soundtrack to 'Run Lola Run', 1998 German thriller film written and directed by Tom Tykwer, and starring Franka Potente as Lola and Moritz Bleibtreu as Manni. Soundtrack by Tykwer, Johnny Klimek, and Reinhold Heil
  78. 78. Designing Trustable AI Experiences / @carologic Even More Resources • “IBM’s Automated Radiologist Can Read Images and Medical Records” by Tom Simonite, February 4, 2016. Intelligent Machines, MIT Technology Review. radiologist-can-read-images-and-medical-records/ • “The IBM, Salesforce AI Mash-Up Could Be a Stroke of Genius” by Adam Lashinsky, Mar 07, 2017. Fortune. • "Google can now tell you're not a robot with just one click" by Andy Greenberg. Dec. 3, 2014. Security: Wired. • “Essentials of Machine Learning Algorithms (with Python and R Codes)” by Sunil Ray, August 10, 2015. Analytics Vidhya. • IBM on Machine Learning • “At Davos, IBM CEO Ginni Rometty Downplays Fears of a Robot Takeover” by Claire Zillman, Jan 18, 2017. Fortune. • “Google and IBM: We Want Artificial Intelligence to Help You, Not Replace You” by Michelle Toh. Mar 02, 2017. Fortune.
  79. 79. Designing Trustable AI Experiences / @carologic Yes, even more resources • Video: “IBM Watson Knowledge Studio: Teach Watson about your unstructured data” • “The optimist’s guide to the robot apocalypse” by Sarah Kessler, @sarahfkessler. March 09, 2017. QZ. • “AI Influencers 2017: Top 30 people in AI you should follow on Twitter" by Trips Reddy @tripsy, Senior Content Manager, IBM Watson . February 10, 2017 influencers-2017-top-25-people-ai-follow-twitter/ • “3 guiding principles for ethical AI, from IBM CEO Ginni Rometty” by Alison DeNisco. January 17, 2017, Tech Republic • "Transparency and Trust in the Cognitive Era" January 17, 2017 Written by: IBM THINK Blog • "Ethics and Artificial Intelligence: The Moral Compass of a Machine“ by Kris Hammond, April 13, 2016. Recode. machine
  80. 80. Designing Trustable AI Experiences / @carologic Last bit: I promise • "The importance of human innovation in A.I. ethics" by John C. Havens. Oct. 03, 2015 • "Me, Myself and AI" Fjordnet Limited 2017 - Accenture Digital. • "Testing AI concepts in user research" By Chris Butler, Mar 2, 2017. concepts-in-user-research-b742a9a92e55#.58jtc7nzo • "CMU prof says computers that can 'see' soon will permeate our lives“ by Aaron Aupperlee. March 16, 2017. see-soon-will-permeate-our-lives • “The business case for augmented intelligence” by Nancy Pearson, VP Marketing, IBM Cognitive. 36afa64cd675#.qqzvunakw
  81. 81. Designing Trustable AI Experiences / @carologic Definition: Artificial Intelligence • Artificial intelligence (AI) is intelligence exhibited by machines. • In computer science, an ideal "intelligent" machine is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal.[1] Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".[2] • Capabilities currently classified as AI include successfully understanding human speech,[4] competing at a high level in strategic game systems (such as Chess and Go[5]), self-driving cars, and interpreting complex data. Wikipedia:
  82. 82. Designing Trustable AI Experiences / @carologic Definition: The Singularity • If research into Strong AI produced sufficiently intelligent software, it might be able to reprogram and improve itself. The improved software would be even better at improving itself, leading to recursive self-improvement.[245] The new intelligence could thus increase exponentially and dramatically surpass humans. Science fiction writer Vernor Vinge named this scenario "singularity".[246] Technological singularity is when accelerating progress in technologies will cause a runaway effect wherein artificial intelligence will exceed human intellectual capacity and control, thus radically changing or even ending civilization. Because the capabilities of such an intelligence may be impossible to comprehend, the technological singularity is an occurrence beyond which events are unpredictable or even unfathomable.[246] • Ray Kurzweil has used Moore's law (which describes the relentless exponential improvement in digital technology) to calculate that desktop computers will have the same processing power as human brains by the year 2029, and predicts that the singularity will occur in 2045.[246] Wikipedia:
  83. 83. Designing Trustable AI Experiences / @carologic Definition: Machine Learning • Ability for system to take basic knowledge (does not mean simple or non-complex) and apply that knowledge to new data • Raises ability to discover new information. Find unknowns in data. • More Definitions: • Algorithm: a process or set of rules to be followed in calculations or other problem- solving operations, especially by a computer. • Natural Language Processing (NLP):