Cognitive computing and machine learning are not new concepts, but they are new to most UX’ers. Carol Smith addresses questions about artificial intelligence (AI) such as:
- What are these terms and technologies and how do they work?
- How can we take advantage of these powerful systems to help our users?
- Should I be concerned that computers will take over the world soon? Spoiler: It is extremely unlikely.
Once this baseline understanding is established, we’ll look at examples of AI in use and discuss the relevancy of design work in the age of AI. Additionally, we’ll explore the ethical challenges inherent with the use of AI from the user’s perspective, specifically regarding trust and transparency.
This was presented at Fluxible 2017 in Kitchener-Waterloo, Ontario, Canada on 23 Sept 2017.
2. AI is when Machines
– Exhibit intelligence
– Perceive their environment
– Take actions to maximize
chance of success at a goal
https://developer.softbankrobotics.com/us-en/showcase/nao-ibm-create-new-hilton-concierge
3. IBM Watson / UX in the Age of AI / @carologic / Fluxible
In the extreme…
Google Search for “movies with AI”
Copyrights as labeled.
4. IBM Watson / UX in the Age of AI / @carologic / Fluxible
“Most people working in AI have a healthy skepticism for the idea
of the singularity.
We know how hard it is to get even a little intelligence into a
machine, let alone enough to achieve recursive self-
improvement.”
– Toby Walsh
5. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Why is the singularity so far off?
• Sheer amount of effort to build systems
– Huge amounts of related information
– Organizing and annotating
• Training requires deep understanding of the specific content
6. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Cognitive computers are
• Knowledgeable about what taught
• Aware of nuances
• Control ONLY what we give them control of
• Continue to learn with more data
7. Remember: “We can unplug the machines!”
Grady Booch, Scientist, philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
8. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Requires annotation of content
Image created by Angela Swindell, Visual
Designer, IBM’er on Watson Knowledge Studio
9. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Transfer human concepts and relationships
Photo by sunlightfoundation
https://www.flickr.com/photos/sunlightfoundation/2385174105
10. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Number Five “Needs Input”
Short Circuit (1986 film)
Ally Sheedy and Number Five (Tim Blaney)
https://en.wikipedia.org/wiki/Short_Circuit_(1986_film)
11. IBM Watson / UX in the Age of AI / @carologic / Fluxible
AI is taxonomies and ontologies coming to life
(NOT like humans learn)
https://commons.wikimedia.org/wiki/File:Baby_Boy_Oliver.jpg
12. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Supervised (by a human) Machine Learning
Watson Knowledge Studio, Supervised Machine Learning:
https://www.ibm.com/us-en/marketplace/supervised-machine-learning
13. Enormous amount of work.
Only as good as data
and time spent improving it
Biased based on what it taught
14. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Knowledge and Accuracy
• How important is accuracy?
• Consider a reverse card
sorting exercise
Gaffney, Gerry. (2000) What is Card Sorting? Usability Techniques Series,
Information & Design. http://www.infodesign.com.au/usabilityresources/design/cardsorting.asp
15. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Across industries – priority of accuracy varies
Higher Priority
90-99%+
Lower Priority
60-89% accuracy is acceptable
16. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Goal is saving time
Machine learning creates
more highly trained
specialists
Not an “all knowing” being
17. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Cancer Burden in Sub-Saharan Africa
Risk of getting cancer
and
Risk of Dying
~same
The Cancer Atlas http://canceratlas.cancer.org/the-burden/
18. IBM Watson / UX in the Age of AI / @carologic / Fluxible
What if we could reduce the burden?
• Bring those taxonomies and ontologies to life
• Broaden access to evidence based medicine
• More informed treatment decisions
• Helping physicians (not replacing)
IBM Watson for Oncology
19. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Why does training take so long?
• Create algorithms
• Gather documents
• Create ground truth (annotation)
• Run training
• Improve and test again
• Repeat (new information, etc.)
20. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Dependent on Experts
• Subject Matter Experts (SME’s) Availability
• Experience in Training varies
– Close collaboration
21. IBM Watson / UX in the Age of AI / @carologic / Fluxible
“The goal is not just the fastest
but the most productive
machine-learning platform for researchers.”
- Pradeep Dubey,
Intel Fellow at the Intel Labs division
http://www.intel.com/content/www/us/en/analytics/machine
-learning/the-race-for-faster-machine-learning.html
22. Humans teach what we feel is important… teach them to share our values.
Super knowing - not super doing
Grady Booch, Scientist, philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
23. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Examples
of AI and Cognitive Computing
24. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Strategic Games
• 1997 Chess, IBM
• 2016 Go, Google
Floor goban, 2007, By Goban1 https://commons.wikimedia.org/wiki/File:FloorGoban.JPG
Graphic, Science Magazine: http://www.sciencemag.org/news/2016/03/update-why-week-s-man-
versus-machine-go-match-doesn-t-matter-and-what-does
25. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Understanding human speech
• Watson developed for quiz show Jeopardy!
• Won against champions in 2011 for $1 million
https://en.wikipedia.org/wiki/Watson_(computer)
Video: “IBM's Watson Supercomputer Destroys Humans in Jeopardy | Engadget”
https://www.youtube.com/watch?v=WFR3lOm_xhE
26. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Decision Making: Self Driving (autonomous) vehicles
Junior, a robotic Volkswagen Passat, in a parking lot at Stanford University, 24
October 2009, By: Steve Jurvetson
https://en.wikipedia.org/wiki/File:Hands-free_Driving.jpg
27. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Image Recognition – Google Photos
Carol’s search for “cats” on her Photos account.
She likes Lacey and Magic quite a bit and being sisters, they like each other.
28. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Sound recognition: Labeling of birdsongs
“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
Photo by Gallo71 (Own work) [Public domain], via Wikimedia Commons
https://commons.wikimedia.org/wiki/File%3ARbruni.JPG
29. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Analyzing Text: Personality of @carologic (not quite)
IBM Watson Developer Cloud, Personality Insights
https://personality-insights-livedemo.mybluemix.net/
30. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Automating Repetitive Work
• Highlight possible
issues
• Radiologist confirms
https://www.technologyreview.com/s/600706/ibms-automated-
radiologist-can-read-images-and-medical-records/
31. IBM Watson / UX in the Age of AI / @carologic / Fluxible
88,000 retina images
• Watson knows what a
healthy eye looks like
• Glaucoma is the second
leading cause of blindness
worldwide
–50% of cases go
undetected
https://twitter.com/IBMWatson/status/844545761740292096
32. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Chatbots for Easy ordering
• Order via text, email,
Facebook Messenger or with
a Slackbot
• Cognitive pieces:
–Speech-to-text
–Chat
–API’s in backend
Story: http://www.businesswire.com/news/home/20161025006273/en/Staples%E2%80%99-
%E2%80%9CEasy-Button%E2%80%9D-Life-IBM-Watson
Photo: Easy Button from Staples: http://www.staples.com/Staples-Easy-Button/product_606396
33. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Chatbots – not really AI, yet
• Mapping Q & A
–Expected language
–Appropriate automated
responses
–When to escalate
to a human
https://www.pexels.com/photo/close-up-of-mobile-phone-248512/
https://www.amazon.com/Amazon-Echo-Bluetooth-Speaker-with-WiFi-Alexa/dp/B00X4WHP5E
https://www.ibm.com/watson/developercloud/doc/conversation/index.html
34. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Optical character recognition (OCR)
• Used to be AI
• Now considered routine computing
Portable scanner and OCR (video)
https://en.wikipedia.org/wiki/File:Portable_scanner_and_OCR_(video).webm
35. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Ethics in Design for AI
36. IBM Watson / UX in the Age of AI / @carologic / Fluxible
How might we…
• build systems that have ethical and moral foundation?’
• that are transparent to users?
• teach mercy and justice of law?
• extend and advance healthcare?
• increase safety in dangerous work?
Grady Booch, Scientist, philosopher, IBM’er
https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
37. IBM Watson / UX in the Age of AI / @carologic / Fluxible
So that we trust machines just as much
as a well-trained human?
38. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Guiding Principles – Ethical AI
• Purpose
• Aid humans, not replace them
• Symbiotic relationship
“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/
39. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Transparency
• How AI was trained
• What data was used
• Humans remain in control of the system
“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/
40. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Skills
• Build with people in the industry
• Human workers trained on how to use these tools
to their advantage
“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/
41. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Regulations
• Almost everyone agrees they are necessary
• Who will create regulations?
• Enforce?
42. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Create a code of conduct
• Regulations take forever
• Take responsibility
– What do you value?
– What lines won’t your AI cross?
– How do you reduce bias?
43. IBM Watson / UX in the Age of AI / @carologic / Fluxible
AI will
“extend human experience in profound ways”
- Grady Booch, Scientist, philosopher, IBM’er
Grady Booch, Scientist, philosopher, IBM’er
https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
44. IBM Watson / UX in the Age of AI / @carologic / Fluxible
How do we evolve the practice of UX
to deal with the new issues
these technologies bring
and the new information that is created?
45. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Don’t fear AI - explore AI
Try the tools
Pair with others
IBM Watson Developer Tools (free trials):
https://console.ng.bluemix.net/catalog/?categ
ory=watson
46. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Go forth and create ethical AI’s
• Purpose
• Transparency
• Skills
• Code of Conduct
“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/
47. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Contact Carol
LinkedIn: https://www.linkedin.com/in/caroljsmith
Twitter - @Carologic: https://twitter.com/carologic
Slides on Slideshare: https://www.slideshare.net/carologic
48. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Additional Information
and Resources
49. IBM Watson / UX in the Age of AI / @carologic / Fluxible
“The biggest challenge here is “understanding
people, not just what they vocalize,”....
Our motivations are often not expressed upfront,
yet it is key to understanding what people want to
get done.”
- Rob High, IBM fellow and Watson CTO
https://techcrunch.com/2017/02/27/for-ibms-cto-for-watson-not-a-
lot-of-value-in-replicating-the-human-mind-in-a-computer/
50. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Should work to Reduce Waste
• Sharing of models, annotators, algorithms not desirable
(currently):
– Huge amount of work
– Proprietary information
• Benefits are not clear to business (yet):
– “A rising tide lifts all boats"
– Build on others work
– Solve more interesting problems
51. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Watson is a cognitive technology that can think like a human.
• Understand
• Analyze and interpret all kinds of data
• Unstructured text, images, audio and video
• Reason
• Understand the personality, tone, and emotion of content
• Learn
• Grow the subject matter expertise in your apps and systems
• Interact
• Create chat bots that can engage in dialog
https://www.ibm.com/watson/
52. IBM Watson / UX in the Age of AI / @carologic / Fluxible
More on Strategic Games
Graphic, Science Magazine: http://www.sciencemag.org/news/2016/03/update-why-week-s-man-
versus-machine-go-match-doesn-t-matter-and-what-does
53. IBM Watson / UX in the Age of AI / @carologic / Fluxible
The Job Question
• Make new economies
and opportunities –
potentially:
–Create jobs
–Entire new fields
• Some jobs will be lost
–What can we do to
mitigate this?
Jobs that no longer exist: The Lector http://www.ranker.com/list/jobs-that-no-
longer-exist/coy-jandreau
54. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Tone Analyzer - Watson
IBM Watson Developer Cloud, Tone Analyzer
https://tone-analyzer-demo.mybluemix.net/
55. IBM Watson / UX in the Age of AI / @carologic / Fluxible
Optimist’s guide to the robot apocalypse - @sarahfkessler
“The optimist’s guide to the robot apocalypse” by Sarah Kessler. March 09, 2017. QZ.
@sarahfkessler https://qz.com/904285/the-optimists-guide-to-the-robot-apocalypse/
56. IBM Watson / UX in the Age of AI / @carologic / Fluxible
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
57. IBM Watson / UX in the Age of AI / @carologic / Fluxible
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
58. IBM Watson / UX in the Age of AI / @carologic / Fluxible
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/
59. IBM Watson / UX in the Age of AI / @carologic / Fluxible
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
60. IBM Watson / UX in the Age of AI / @carologic / Fluxible
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
61. IBM Watson / UX in the Age of AI / @carologic / Fluxible
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
62. IBM Watson / UX in the Age of AI / @carologic / Fluxible
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
63. IBM Watson / UX in the Age of AI / @carologic / Fluxible
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
Editor's Notes
More recently,
The Terminator, Short Circuit, 2001 Space Odyssey, The Matrix, Metropolis
Westworld
Metropolis (1927), 2001 Space Odyssey (1968), War Games (1983), Blade Runner (1982), The Terminator (1984), Short Circuit (1986), The Matrix (1999), Ex Machina (2015),
Take set of knowledge we give them and apply to new data
Help humans discover patterns and find unknown
Provide body of knowledge for ground-truth
curated
representative
used to compare further knowledge
Training
Don’t learn like a typical human
Only what they need to know
Consider a reverse card sorting exercise
30 participants
How important is it that they all get it right every time?
Consider your industry
Government safety compliance
Accidents related to this tire?
Financial compliance
Accounts with connections to this organization?
Ecommerce chat bot
Women’s pants with pockets?
When carefully (or not so carefully) piled books succumb to gravity
Grew up with bookalanches occurring regularly
Stepfather is an oncologist – would bring home piles of articles, papers, books and more.
He reads everything he can get his hands on. He never stops trying to understand and fight cancer.
Late stage of disease at diagnosis and lack of treatment
Analyzes a patient’s medical information against a vast array of data and expertise to provide evidence-based treatment options.
Saving some trees and reducing bookalanches
IBM’s Deep Blue beat world chess champion Garry Kasparov in a 6 game match
Google's AlphaGo beat human world Go champion Lee Sedol, 4:1
Developed initially to answer Jeopardy! questions
IBM's Watson named after IBM's first CEO, industrialist Thomas J. Watson.
“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
“Analysis of birdsong (for neuroscience or the many other fields that study this behavior) typically focuses on "syllables" or "notes", recurring elements in the song… Each individual has a unique song that bears some similarity to the song of the bird that tutored it, but is not a direct copy. To analyze song, experimenters label syllables by hand. Typically the experimenter records one bird at a time while carrying out a behavioral experiment. However, each songbird produces thousands of songs a day, more than can be labeled. In order to deal with this mountain of data, some labs have developed automated analyses.”
David Nicholson trained a classifier on syllables of one bird’s song to automate labeling of those syllables (same bird).
This was not to train a classifier to distinguish the song of one bird from another.
Specialists spend more time on more complex patients
IBM’s Avicenna software highlighted possible embolisms on this CT scan in green, finding mostly the same problems as a human radiologist who marked up the image in red.
IBM Research Australia is working to help stop this ‘silent thief of sight’ by teaching Watson to detect it. After learning from 88,000 retina images, Watson can understand what a healthy eye looks like, and identify abnormalities that indicate of the onset of eye diseases like glaucoma. In the future, this early detection technology could help keep glaucoma out of sight for millions.
Reorder
Track shipments
Chat with CSR
http://www.businesswire.com/news/home/20161025006273/en/Staples%E2%80%99-%E2%80%9CEasy-Button%E2%80%9D-Life-IBM-Watson
“Simplifies the customers’ shopping experience, allowing them to quickly reorder supplies, track shipments or chat about customer service needs.”
Staples “Easy Button” office supply reordering system which integrates IBM’s Watson technology to simplify office supply management for Staples Business Advantage Customers
teach to discern between right and wrong?
letter vs. spirit of law?
The Job: To read to large rooms of factory workers slaving away at remedial tasks for hours on end. Lectors were sometimes even hired with pooled money from the factory workers themselves for their entertainment.
Who Did It: Well spoken gentlemen.
Why It Went Away: A whole smorgasbord of reasons from the radio, to the Walk-Man, iPhones, iPods, podcasts...
By Coy Jandreau - user uploaded image