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IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018

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This session focuses on the questions we need to ask to create good, ethical experiences for our users.
Information Architects must push to…
- Keep people at the center of our work.
- Lead with our user’s goals.
- Ease of use, usability, findability, effectiveness, efficiency…

We must work to mature organizations approach
- Push back on “technology first” ideas.
- Lead on ethics - for our users, humanity.

Published in: Design
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IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018

  1. 1. IA in the Age of AI: Embracing Abstraction and Change Carol Smith @carologic IA Summit 2018, Chicago March 23, 2018 Advanced Technologies Group
  2. 2. No point making AI that doesn’t…
  3. 3. IA in the Age of AI: Embracing Abstraction and Change / @carologic Help humans...
  4. 4. IA in the Age of AI: Embracing Abstraction and Change / @carologic Technology is Imperfect • Data made and curated by humans – Flawed. – Inconsistent. – Limited. – Biased. – Constantly changing. – Messy!
  5. 5. IA in the Age of AI: Embracing Abstraction and Change / @carologic Information Architects must push… • Keep people at the center of our work. – Lead with our user’s goals. – Ease of use, usability, findability, effectiveness, efficiency… • Work to mature organizations approach – Push back on “technology first” ideas. – Lead on ethics - for our users, humanity.
  6. 6. IA in the Age of AI: Embracing Abstraction and Change / @carologic Humans Teach and Monitor AI • Water – add new information and teach (continuous) • Thin – pluck poor performing models, bad patterns • Prune – as AI matures, continuous monitoring, adding and removing functionality. • Cull – remove/stop broken/biased models.
  7. 7. Never set it and forget it.
  8. 8. "Microsoft silences its new A.I. bot Tay, after Twitter users teach it racism [Updated]" by Sarah Perez@sarahintampa / Mar 24, 2016, TechCrunch. https://techcrunch.com/2016/03/24/microsoft-silences-its-new-a-i-bot-tay-after-twitter-users-teach-it-racism/
  9. 9. Everything changes quickly.
  10. 10. What is AI?
  11. 11. AI is present when computers/machines – Exhibit intelligence – Perceive their environment – Take actions/make decision to maximize chance of success at a goal Our Road to Self-Driving Vehicles | Uber ATG https://youtu.be/27OuOCeZmwI
  12. 12. IA in the Age of AI: Embracing Abstraction and Change / @carologic Cognitive computers are • Made with algorithms • Limited domain knowledge • Control ONLY what we give them control of • Aware of nuances and can continue to learn https://www.analyticsvidhya.com/blog/2015/08/common-machine-learning-algorithms/
  13. 13. AI may know a lot about something, but not everything
  14. 14. IA in the Age of AI: Embracing Abstraction and Change / @carologic Happy Spring! • Use Case: Lawn care treatment selection. • Users: Lawn technicians and sales people. • Goal: More quickly and effectively customize solutions for customers and minimize costs (time, effort, amount of chemicals, cost to customer, etc.).
  15. 15. IA in the Age of AI: Embracing Abstraction and Change / @carologic Hire a Consulting Firm • Understand users, goals. • Review existing data – Knowledge about lawn care products. – Great data from a few technicians. – Create ground truth and teach AI (few weeks).
  16. 16. IA in the Age of AI: Embracing Abstraction and Change / @carologic This looks familiar? • Information Architecture! • Organizing huge amounts of information • Requires deep understanding of the content
  17. 17. IA in the Age of AI: Embracing Abstraction and Change / @carologic Taxonomies and Ontologies Come to Life (NOT like humans learn) Photo: https://commons.wikimedia.org/wiki/File:Baby_Boy_Oliver.jpg
  18. 18. IA in the Age of AI: Embracing Abstraction and Change / @carologic AI Systems • Data and Ground Truth • AI • UX
  19. 19. IA in the Age of AI: Embracing Abstraction and Change / @carologic Create UX – User Needs • Patterns across customers • Effectiveness of treatments. • Extent of problems, pests, etc. • Levers – Types of grass. – Conditions (sun exposure, etc.). – Customer attitude about lawn care. – Etc.
  20. 20. IA in the Age of AI: Embracing Abstraction and Change / @carologic Ready for Use • Experts begin reviewing results – Too many recommendations for heavy chemical use. – Need to replace models that aren’t working. • But what went wrong
  21. 21. IA in the Age of AI: Embracing Abstraction and Change / @carologic Hire a Consulting Firm • Understand users, goals. • Review existing data – Knowledge about lawn care products. – Great data from a few technicians. – Create ground truth and teach AI (few weeks).
  22. 22. IA in the Age of AI: Embracing Abstraction and Change / @carologic Data Source • Few technicians who are great at documenting. • Prefer using chemicals to treat lawns. • Limited data biased towards chemical use. • Most technicians, take horrible notes. • Prefer “all natural” treatments. Neither are wrong. Limited data created a bias.
  23. 23. Only as good as data and time spent improving it. Biased based on what taught.
  24. 24. IA in the Age of AI: Embracing Abstraction and Change / @carologic All data is biased - what is bias? • Human condition - we all bring our history. • Affected by: – Social class, resource availability. – Race, Gender, Sexuality. – Culture, Theology, Tradition. – Other factors we aren’t even aware of.
  25. 25. “We often have no way of knowing when and why people are biased.” - Sandra Wachter Q&A: Should artificial intelligence be legally required to explain itself? By Matthew Hutson, May. 31, 2017. Interview with Sandra Wachter, data ethics researcher at Univ. of Oxford and Alan Turing Institute. http://www.sciencemag.org/news/2017/05/qa-should-artificial-intelligence-be-legally-required-explain-itself
  26. 26. Know any WEIRD people?
  27. 27. IA in the Age of AI: Embracing Abstraction and Change / @carologic WEIRD People Western, Educated, Industrialized, Rich, and Democratic Behavioral science disproportionately relies on studies of US university undergraduates. Joseph Henrich, Steven J. Heine and Ara Norenzayan. ‘The weirdest people in the world?’ and “Most People are not WEIRD” discussed in “We agree it’s WEIRD, but is it WEIRD enough?” Posted on July 10, 2010 by gregdowney https://neuroanthropology.net/2010/07/10/we-agree-its-weird-but-is-it-weird-enough/
  28. 28. IA in the Age of AI: Embracing Abstraction and Change / @carologic WEIRD (Western, Educated, Industrialized, Rich, Democratic) • Outliers on a range of measurable traits: – Sense of fairness – Cooperation – Spatial reasoning – Visual perception Joseph Henrich, Steven J. Heine and Ara Norenzayan. ‘The weirdest people in the world?’ and “Most People are not WEIRD” discussed in “We agree it’s WEIRD, but is it WEIRD enough?” Posted on July 10, 2010 by gregdowney https://neuroanthropology.net/2010/07/10/we-agree-its-weird-but-is-it-weird-enough/
  29. 29. IA in the Age of AI: Embracing Abstraction and Change / @carologic Data created by those who write • History written by victors. • Lawn care specialists.
  30. 30. IA in the Age of AI: Embracing Abstraction and Change / @carologic Better Content • Who is working on the collection? – Respected experts in the industry? – Diverse, socio-economic, cross cultural, international team? • Where is content sourced from? – What bias does it already have? – How will it be organized? – What are potential unintended consequences? “3 guiding principles for ethical AI, from IBM CEO Ginni Rometty” by Alison DeNisco. January 17, 2017, Tech Republic http://www.techrepublic.com/article/3- guiding-principles-for-ethical-ai-from-ibm-ceo-ginni-rometty/
  31. 31. Whose problem are we solving?
  32. 32. IA in the Age of AI: Embracing Abstraction and Change / @carologic Who will use the system and why? • What are their goals? • What problems are they trying to solve? – Is this a problem a computer can solve? – Is AI the right solution? – What is out of scope? • Are they working independently or together? – How might they collaborate?
  33. 33. IA in the Age of AI: Embracing Abstraction and Change / @carologic What are potential unintended consequences? • Understand user’s fears. • Those fears should be well known. • Figure out how to address fears. • Fears lead to potential unintended consequences. – Preparing for these will protect your users.
  34. 34. IA in the Age of AI: Embracing Abstraction and Change / @carologic AI Management Matches Org Ecosystem • Microcosm of organization – Not independent of organization – Same issues • Need similar support – Need people curating content – Watching for issues, etc. – Who is responsible for managing, training, and oversight?
  35. 35. IA in the Age of AI: Embracing Abstraction and Change / @carologic Can’t Just Turn AI systems on • Subject matter experts (SME’s) knowledge needed – Lawyers – Machinists – Insurance adjusters – Physicians • Working with experts in AI systems.
  36. 36. IA in the Age of AI: Embracing Abstraction and Change / @carologic Teaching Terms, Relationships and More… employedBy employedBy Model created by Angela Swindell, Visual Designer, IBM Amanda works at Uber. She has worked for the company for 2 years.
  37. 37. Enormous amount of work.
  38. 38. IA in the Age of AI: Embracing Abstraction and Change / @carologic Which experts will train the system? • How are they vetted? • How frequently will they be available? • How will quality be maintained? • Where will they work? • What process will they use? • When something goes wrong, how do you respond?
  39. 39. IA in the Age of AI: Embracing Abstraction and Change / @carologic Like Any Good UX • Understand problem deeply. • Build right AI system to solve problem. – Different problems require different systems.
  40. 40. IA in the Age of AI: Embracing Abstraction and Change / @carologic Strategic Thinking • 1997 Chess, IBM • 2016 Go, Google • Intelligence? • Perception? • Action/Decision? Floor goban, 2007, By Goban1 https://commons.wikimedia.org/wiki/File:FloorGoban.JPG
  41. 41. IA in the Age of AI: Embracing Abstraction and Change / @carologic Analyzing Text for patterns (personality, sentiment, etc.) IBM Watson Personality Insights applied to @Carologic on Twitter IBM Watson Developer Cloud: https://personality-insights-livedemo.mybluemix.net/
  42. 42. IA in the Age of AI: Embracing Abstraction and Change / @carologic Safer Roads: Self-Driving (autonomous) vehicles https://www.uber.com/info/atg/
  43. 43. IA in the Age of AI: Embracing Abstraction and Change / @carologic Image Pattern Detection: Recognize healthy body parts • Glaucoma is the second leading cause of blindness worldwide –50% of cases go undetected Seeing is preventing. https://twitter.com/IBMWatson/status/844545761740292096
  44. 44. IA in the Age of AI: Embracing Abstraction and Change / @carologic The System Strong Bad Email #45 – Techno - Strong Bad makes a techno song. https://youtu.be/JwZwkk7q25I Homestarrunnerdotcom Published on Mar 31, 2009
  45. 45. IA in the Age of AI: Embracing Abstraction and Change / @carologic AI System • Data and Ground Truth • AI • UX
  46. 46. IA in the Age of AI: Embracing Abstraction and Change / @carologic What questions are most likely to be asked about data? • What… – Comes next? – Outliers? – Changed? How can I tell what changed? – New? Unexpected? – Validates assumptions? – Increased/decreased frequency?
  47. 47. IA in the Age of AI: Embracing Abstraction and Change / @carologic How trusting are the users of AI? • Work to gain trust? • What might engender trust via the UI? • Add “fun” to show it is working
  48. 48. IA in the Age of AI: Embracing Abstraction and Change / @carologic Anticipated changes with AI system? • Not just throwing AI in, because we can. • What is intention? What kind of improvements? • What might a machine do better or faster? • What is not going to be improved (out of scope)?
  49. 49. IA in the Age of AI: Embracing Abstraction and Change / @carologic Indicators of ethics • Richard Mason's ethical discussion of security and controls • PAPA Policy – Privacy – Accuracy – Property – Accessibility (access to information, not #a11y) Ethical Issues in IS by Richard Mason’s H/T to Andrea Resmini https://www.gdrc.org/info-design/4-ethics.html
  50. 50. IA in the Age of AI: Embracing Abstraction and Change / @carologic Safety and Security (Privacy)
  51. 51. IA in the Age of AI: Embracing Abstraction and Change / @carologic Intentional Design • Keep people and data safe. • When unintended consequences arise, how do we deal with them? http://www.flickr.com/photos/rockyvi/6451635085/sizes/m/in/photolist-aQ7jkF/ Some rights reserved by Rocky VI - http://www.flickr.com/photos/rockyvi/ License: http://creativecommons.org/licenses/by-nc-nd/2.0/
  52. 52. IA in the Age of AI: Embracing Abstraction and Change / @carologic Make it your business to keep people safe • Make contingency plans. – Warning signs? – How do we deal with unintentional consequences? – What is the worst potential outcome?
  53. 53. IA in the Age of AI: Embracing Abstraction and Change / @carologic Make a Plan • No need to imagine every single situation • Focus on how you’ll react to worst situations: – What happens when it becomes a Nazi? – What happens when it does XYZ unexpectedly?
  54. 54. IA in the Age of AI: Embracing Abstraction and Change / @carologic What will you do? • What is the method for “turning it off”? – Who turns it off? How? – Who has access? • Who is notified immediately? • Unintended consequences of turning it off? Google’s new tensor processing units: https://www.nytimes.com/2018/02/12/technology/google-artificial-intelligence-chips.html
  55. 55. Remember: “We can unplug the machines!” Grady Booch, Scientist, philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
  56. 56. IA in the Age of AI: Embracing Abstraction and Change / @carologic Back doors and brakes • A way to get into the system and shut it down. • Secured from inside and outside. • “If it’s not usable, it’s not secure.” – Jared Spool, IAS17 Unintuitive and Insecure: Fixing the Failures of Authentication, Jared Spool, IA Summit 2017
  57. 57. IA in the Age of AI: Embracing Abstraction and Change / @carologic Data and Accuracy
  58. 58. IA in the Age of AI: Embracing Abstraction and Change / @carologic Data Sources • Data exist? • Available? High quantity? • Quality? – Multiple databases - harmonized. – Inconsistent fields. – Alignment of terms. Photo by sunlightfoundation https://www.flickr.com/photos/sunlightfoundation/2385174105
  59. 59. IA in the Age of AI: Embracing Abstraction and Change / @carologic Accuracy of system • How important is accuracy? • Consider a reverse card sorting exercise Image: Gerry Gaffney. (2000) What is Card Sorting? Usability Techniques Series, Information & Design. http://www.infodesign.com.au/usabilityresources/design/cardsorting.asp
  60. 60. IA in the Age of AI: Embracing Abstraction and Change / @carologic Across Industries – Priority of Accuracy Varies Higher Priority 90-99%+ Lower Priority 60-89% accuracy is acceptable Financial Ecommerce
  61. 61. IA in the Age of AI: Embracing Abstraction and Change / @carologic What is good enough? • Accuracy - set a bar (a goal) • Keep going until attain goal • More accurate, exponential effort
  62. 62. IA in the Age of AI: Embracing Abstraction and Change / @carologic Property • Who owns the data? – User owns what and when? – Organization owns what and when? • What must a user reveal? – Life expectancy of data? – Transitional phases?
  63. 63. IA in the Age of AI: Embracing Abstraction and Change / @carologic Accessibility of Data • What do we have a right to access? • Barriers – Literacy and awareness. – Connection to internet – economics and location. – Access to pertinent data.
  64. 64. IA in the Age of AI: Embracing Abstraction and Change / @carologic Who gets to use our tools? • “When we do not design for people with disabilities we are being ableist” – Anne Gibson @perpendicularme #ias18 Roundtable on Ethics • Physical disabilities • Cognitive, learning, and neurological How People with Disabilities Use the Web: Overview https://www.w3.org/WAI/intro/people-use-web /
  65. 65. IA in the Age of AI: Embracing Abstraction and Change / @carologic Who owns ethics in AI?
  66. 66. IA in the Age of AI: Embracing Abstraction and Change / @carologic Communication and responsibility • How is communication about the AI handled? – How do you report issues? • To whom? – Everyone needs to be bought in. – Not everyone can fix it.
  67. 67. IA in the Age of AI: Embracing Abstraction and Change / @carologic Transparency
  68. 68. IA in the Age of AI: Embracing Abstraction and Change / @carologic Data and Training Transparency • What data was it based on? – Sources referenced? – Access to overall collection? • Who trained AI? – Experience? Background? Vetting? – Who will update it? How often?
  69. 69. IA in the Age of AI: Embracing Abstraction and Change / @carologic Potential Bias • Show awareness; acknowledge issues. – What are potential signs of building bias? – Over communicate about potential bias. • Acknowledge potential for bad decisions based on data. – Who is responsible?
  70. 70. IA in the Age of AI: Embracing Abstraction and Change / @carologic How do users know when something is wrong? • Show examples. – Bias has changed. – Accuracy has decreased. • Where do these examples live? • How can a user contest something and report it? – When should they expect a response?
  71. 71. Crazy and Evil? Reduce their power.
  72. 72. IA in the Age of AI: Embracing Abstraction and Change / @carologic Confidence in Content • Rating? Scale? • How is ‘ABC’ comparable to other entries? – “Top” entry”? – Potential new discovery in the data? – Outside of the AI’s normal purview? – Really just a guess? – No idea at all?
  73. 73. IA in the Age of AI: Embracing Abstraction and Change / @carologic Displaying Information • AI generated content – separate from other content? – marked as AI generated? – more clearly referenced? – does it matter?
  74. 74. IA in the Age of AI: Embracing Abstraction and Change / @carologic Continue to Teach and Monitor AI • Water regularly • Thin • Prune • Cull
  75. 75. IA in the Age of AI: Embracing Abstraction and Change / @carologic IA Ethics for AI
  76. 76. IA in the Age of AI: Embracing Abstraction and Change / @carologic If we don’t ask tough questions, who will?
  77. 77. Do we want users to trust AI as much as a well-trained human?
  78. 78. Humans teach what we feel is important… teach them to share our values. Grady Booch, Scientist, philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
  79. 79. IA in the Age of AI: Embracing Abstraction and Change / @carologic Help humans...
  80. 80. IA in the Age of AI: Embracing Abstraction and Change / @carologic Creating Ethical AI • Less-biased content. • Transparency of data sources and training. • Intentional design: Build in safety. • Build practices around: – PAPA (Privacy, Accuracy, Property, Accessibility)
  81. 81. IA in the Age of AI: Embracing Abstraction and Change / @carologic Create a code of conduct/ethics • What do you value? • What lines won’t your AI cross? – What is too far? – What are you including? • How will you track your progress?
  82. 82. IA in the Age of AI: Embracing Abstraction and Change / @carologic Take Responsibility • Keep humans in control. • Hire people affected by bias (non-WEIRD, women, POC, LGBTQ, etc.). • Conduct auditing (algorithmic, data, UI, etc.). How to Keep Your AI from Turning into a Racist Monster by Megan Garciahttps://www.wired.com/2017/02/keep-ai-turning-racist-monster/
  83. 83. IA in the Age of AI: Embracing Abstraction and Change / @carologic Learn about making 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 https://medium.com/@eirinimalliaraki/toward-ethical-transparent-and-fair-ai-ml-a-critical- reading-list-d950e70a70ea
  84. 84. IA in the Age of AI: Embracing Abstraction and Change / @carologic Teach others about AI • Demystify – use plain language. • Teach people how to utilize and benefit from the system. • Provide easy way to raise concerns (anonymous if appropriate).
  85. 85. IA in the Age of AI: Embracing Abstraction and Change / @carologic Don’t fear AI - Explore AI Try out tools (see Appendix and footer) Pair with others
  86. 86. IA in the Age of AI: Embracing Abstraction and Change / @carologic Uber is Hiring! https://www.uber.com/careers/ Advanced Technologies Group
  87. 87. IA in the Age of AI: Embracing Abstraction and Change / @carologic Contact Carol LinkedIn – CarolJSmith Twitter - @Carologic Slideshare – carologic SpeakerRate - CarolJSmith
  88. 88. IA in the Age of AI: Embracing Abstraction and Change / @carologic Additional Information and Resources
  89. 89. IA in the Age of AI: Embracing Abstraction and Change / @carologic AI Tools • A list of artificial intelligence tools you can use today — for businesses, by Liam Hanel, July 11, 2017 on Lyr.AI https://lyr.ai/a-list-of-artificial-intelligence-tools-you-can-use-today%E2%80%8A- %E2%80%8Afor-businesses/ and https://medium.com/imlyra/a-list-of-artificial- 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 https://www.techworld.com/picture-gallery/apps- wearables/best-ai-machine-learning-tools-for-developers-3657996/ • 15 Top Open Source Artificial Intelligence Tools by Cynthia Harvey, September 12, 2016 on Datamation https://www.datamation.com/open-source/slideshows/15- top-open-source-artificial-intelligence-tools.html • IBM Watson Developer Tools (free trials): https://console.ng.bluemix.net/catalog/?category=watson
  90. 90. IA in the Age of AI: Embracing Abstraction and Change / @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: https://www.forbes.com/sites/janakirammsv/2018/02/22/the-rise-of-artificial-intelligence-as-a-service-in-the-public-cloud/#11aa85a8198e Courses at http://www.fast.ai/
  91. 91. IA in the Age of AI: Embracing Abstraction and Change / @carologic Additional Resources • “How IBM is Competing with Google in AI.” The Information. https://www.theinformation.com/how-ibm-is- competing-with-google-in-ai?eu=2zIDMNYNjDp7KqL4YqAXXA • “The business case for augmented intelligence” https://medium.com/cognitivebusiness/the-business-case-for- 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). http://conference.scipy.org/proceedings/scipy2016/pdfs/david_nicholson.pdf • “Staples’ “Easy Button” Comes to Life with IBM Watson” in Business Wire, October 25, 2016. http://www.businesswire.com/news/home/20161025006273/en/Staples%E2%80%99-%E2%80%9CEasy- Button%E2%80%9D-Life-IBM-Watson • “How Staples Is Making Its Easy Button Even Easier With A.I.” by Chris Cancialosi, Forbes. https://www.forbes.com/sites/chriscancialosi/2016/12/13/how-staples-is-making-its-easy-button-even-easier- with-a-i/#4ae66e8359ef • “Inside Intel: The Race for Faster Machine Learning” http://www.intel.com/content/www/us/en/analytics/machine-learning/the-race-for-faster-machine-learning.html
  92. 92. IA in the Age of AI: Embracing Abstraction and Change / @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 http://www.sciencemag.org/news/2016/03/update-why-week-s- 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. https://techcrunch.com/2017/02/27/for-ibms-cto- 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. http://fortune.com/2017/03/02/google-ibm-artificial-intelligence/ • “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 https://www.theregister.co.uk/2017/02/22/facebook_ai_fail/ • “Microsoft is deleting its AI chatbot's incredibly racist tweets” by Rob Price. Mar. 24, 2016. Business Insider UK. http://www.businessinsider.com/microsoft-deletes-racist-genocidal-tweets-from-ai-chatbot-tay-2016-3 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
  93. 93. IA in the Age of AI: Embracing Abstraction and Change / @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. https://www.technologyreview.com/s/600706/ibms-automated- 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. http://fortune.com/2017/03/07/data-sheet-ibm-salesforce/ • "Google can now tell you're not a robot with just one click" by Andy Greenberg. Dec. 3, 2014. Security: Wired. https://www.wired.com/2014/12/google-one-click-recaptcha/ • “Essentials of Machine Learning Algorithms (with Python and R Codes)” by Sunil Ray, August 10, 2015. Analytics Vidhya. https://www.analyticsvidhya.com/blog/2015/08/common-machine-learning-algorithms/ • IBM on Machine Learning https://www.ibm.com/analytics/us/en/technology/machine-learning/ • “At Davos, IBM CEO Ginni Rometty Downplays Fears of a Robot Takeover” by Claire Zillman, Jan 18, 2017. Fortune. http://fortune.com/2017/01/18/ibm-ceo-ginni-rometty-ai-davos/ • “Google and IBM: We Want Artificial Intelligence to Help You, Not Replace You” by Michelle Toh. Mar 02, 2017. Fortune. http://fortune.com/2017/03/02/google-ibm-artificial-intelligence/
  94. 94. IA in the Age of AI: Embracing Abstraction and Change / @carologic Yes, even more resources • Video: “IBM Watson Knowledge Studio: Teach Watson about your unstructured data” https://www.youtube.com/watch?v=caIdJjtvX1s&t=6s • “The optimist’s guide to the robot apocalypse” by Sarah Kessler, @sarahfkessler. March 09, 2017. QZ. https://qz.com/904285/the-optimists-guide-to-the-robot-apocalypse/ • “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 https://www.ibm.com/blogs/watson/2017/02/ai- 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 http://www.techrepublic.com/article/3-guiding-principles-for-ethical-ai-from-ibm-ceo-ginni-rometty/ • "Transparency and Trust in the Cognitive Era" January 17, 2017 Written by: IBM THINK Blog https://www.ibm.com/blogs/think/2017/01/ibm-cognitive-principles/ • "Ethics and Artificial Intelligence: The Moral Compass of a Machine“ by Kris Hammond, April 13, 2016. Recode. http://www.recode.net/2016/4/13/11644890/ethics-and-artificial-intelligence-the-moral-compass-of-a- machine
  95. 95. IA in the Age of AI: Embracing Abstraction and Change / @carologic Last bit: I promise • "The importance of human innovation in A.I. ethics" by John C. Havens. Oct. 03, 2015 http://mashable.com/2015/10/03/ethics-artificial-intelligence/#yljsShvAFsqy • "Me, Myself and AI" Fjordnet Limited 2017 - Accenture Digital. https://trends.fjordnet.com/trends/me-myself-ai • "Testing AI concepts in user research" By Chris Butler, Mar 2, 2017. https://uxdesign.cc/testing-ai- concepts-in-user-research-b742a9a92e55#.58jtc7nzo • "CMU prof says computers that can 'see' soon will permeate our lives“ by Aaron Aupperlee. March 16, 2017. http://triblive.com/news/adminpage/12080408-74/cmu-prof-says-computers-that-can- see-soon-will-permeate-our-lives • “The business case for augmented intelligence” by Nancy Pearson, VP Marketing, IBM Cognitive. https://medium.com/cognitivebusiness/the-business-case-for-augmented-intelligence- 36afa64cd675#.qqzvunakw
  96. 96. IA in the Age of AI: Embracing Abstraction and Change / @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: https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-Intelligent_agents-1
  97. 97. IA in the Age of AI: Embracing Abstraction and Change / @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: https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-Intelligent_agents-1
  98. 98. IA in the Age of AI: Embracing Abstraction and Change / @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. • https://en.wikipedia.org/wiki/Machine_learning More Definitions: • Algorithm: a process or set of rules to be followed in calculations or other problem- solving operations, especially by a computer. https://en.wikipedia.org/wiki/Algorithm • Natural Language Processing (NLP): https://en.wikipedia.org/wiki/Natural_language_processing

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