SlideShare ist ein Scribd-Unternehmen logo
1 von 66
Downloaden Sie, um offline zu lesen
AI and Machine Learning Demystified
Carol Smith @carologic
Midwest UX 2017, Cincinnati, Ohio
October 13, 2017
AI is when Machines
– Exhibit intelligence
– Perceive their environment
– Take actions/make decision to
maximize chance of success at a goal
NAO’s New Job as “Connie” the concierge at Hilton Hotels
https://developer.softbankrobotics.com/us-en/showcase/nao-ibm-create-new-hilton-concierge
AI and ML Demystified / @carologic / MWUX2017
In the extreme…
Google Search for “movies with AI” Copyrights as labeled.
“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
http://www.wired.co.uk/article/elon-musk-
artificial-intelligence-scaremongering
Remember: “We can unplug the machines!”
Grady Booch, Scientist, philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
AI and ML Demystified / @carologic / MWUX2017
Cognitive computers are
• Made with algorithms
• Knowledgeable ONLY about what taught
• Control ONLY what we give them control of
• Aware of nuances and can continue to learn more
AI and ML Demystified / @carologic / MWUX2017
Cognitive computers (algorithms) can…
• Do very boring work for you
• Often make better, more consistent decisions than humans
• Be efficient, won’t get tired
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
AI and ML Demystified / @carologic / MWUX2017
Exhibit intelligence
- transfer human concepts and relationships
Photo by sunlightfoundation
https://www.flickr.com/photos/sunlightfoundation/2385174105
AI and ML Demystified / @carologic / MWUX2017
Dependent on Experts
• Subject Matter Experts (SME’s) Availability
– Lawyers
– Machinists
– Insurance adjusters
– Physicians
• Usually not experienced in machine learning
– Need close collaboration with those making algorithms
AI and ML Demystified / @carologic / MWUX2017
Number Five “Needs Input”
Short Circuit (1986 film) - Ally Sheedy and Number Five
https://en.wikipedia.org/wiki/Short_Circuit_(1986_film)
AI and ML Demystified / @carologic / MWUX2017
Content is annotated by experts
Image created by Angela Swindell,
Visual Designer, Watson Knowledge Studio
AI and ML Demystified / @carologic / MWUX2017
AI is taxonomies and ontologies coming to life
(NOT like humans learn)
Photo: https://commons.wikimedia.org/wiki/File:Baby_Boy_Oliver.jpg
Enormous
amount of
work.
Only as good as data
and time spent improving it
Biased based on what it taught
AI and ML Demystified / @carologic / MWUX2017
Creating an AI requires
• Algorithms
• Documents
• Ground truth (annotation)
• Teaching
• Iteration
• Repeat
AI and ML Demystified / @carologic / MWUX2017
Supervised (by a human) Machine Learning
Watson Knowledge Studio
https://www.ibm.com/us-en/marketplace/supervised-machine-learning
AI and ML Demystified / @carologic / MWUX2017
Knowledge and Accuracy
• 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
AI and ML Demystified / @carologic / MWUX2017
Across industries – priority of accuracy varies
Higher Priority
90-99%+
Lower Priority
60-89% accuracy is acceptable
AI and ML Demystified / @carologic / MWUX2017
Goal is saving time
Machine learning creates
more highly trained specialists
Not an “all knowing” being
AI and ML Demystified / @carologic / MWUX2017
Cancer Burden in Sub-Saharan Africa
Risk of getting cancer
and
Risk of Dying
~same
The Cancer Atlas http://canceratlas.cancer.org/the-burden/
AI and ML Demystified / @carologic / MWUX2017
What if we could reduce the burden?
• Bring taxonomies and ontologies to life
• Broaden access to evidence based medicine
• More informed treatment decisions
AI and ML Demystified / @carologic / MWUX2017
AI actions for success
• Example: Healthcare
– AI analyzes data (treatment options, similar patients)
– Goal: Provide quick, evidence based options
– Physician selects treatment for patients based on situation
• AI success is helping physician (not replacing)
AI and ML Demystified / @carologic / MWUX2017
Examples
of AI and Cognitive
Computing
AI and ML Demystified / @carologic / MWUX2017
Consider for each example
• What intelligence does the system need?
• What is the AI perceiving in their environment?
• What actions are taken to maximize chance
of success at goal?
AI and ML Demystified / @carologic / MWUX2017
Strategic Games
• 1997 Chess, IBM
• 2016 Go, Google
• Intelligence?
• Perception?
• Action/Decision?
Floor goban, 2007, By Goban1
https://commons.wikimedia.org/wiki/File:FloorGoban.JPG
AI and ML Demystified / @carologic / MWUX2017
Understanding human speech
• Watson developed for quiz show Jeopardy!
• Won against champions in 2011 for $1 million
Video: “IBM's Watson Supercomputer Destroys Humans in Jeopardy!
Engadget” https://www.youtube.com/watch?v=WFR3lOm_xhE
Watson definition: https://en.wikipedia.org/wiki/Watson_(computer)
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
Image Recognition – Google Photos
Carol’s search for “cats” on her Google Photos account.
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
Analyzing Text: Personality of @carologic (not quite)
Personality Insights applied to @Carologic on Twitter
IBM Watson Developer Cloud: https://personality-insights-livedemo.mybluemix.net/
AI and ML Demystified / @carologic / MWUX2017
Automating Repetitive Work
• Automated
Radiologist
highlights
possible
issues
• Radiologist
confirms
IBM’s Automated Radiologist Can Read Images and Medical Records,
MIT Technology Review
https://www.technologyreview.com/s/600706/ibms-automated-radiologist-can-read-images-and-medical-records/
AI and ML Demystified / @carologic / MWUX2017
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
Seeing is preventing.
https://twitter.com/IBMWatson/status/844545761740292096
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
Chatbots – not really AI, yet
• Mapping Q & A
–Expected language
–Appropriate automated
responses
–When to escalate
to a human
Images: 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
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
Ethics in Design for AI
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
AI and ML Demystified / @carologic / MWUX2017
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?
Inspired by Grady Booch, Scientist, philosopher, IBM’er
https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
Trust machines
just as much
as a well-trained human?
AI and ML Demystified / @carologic / MWUX2017
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/
AI and ML Demystified / @carologic / MWUX2017
Transparency
• How was AI taught?
• 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/
AI and ML Demystified / @carologic / MWUX2017
Skills
• Built with people in the industry
• Human workers trained
how to use 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/
AI and ML Demystified / @carologic / MWUX2017
Regulations
• Almost everyone agrees they are necessary
• Who will create regulations?
• Enforce?
“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
AI and ML Demystified / @carologic / MWUX2017
The EU General Data Protection Regulation (GDPR)
• Framework for transparency rights
and safeguards against automated decision-making
• Right to contest a completely automated decision
if it has legal or other significant effects on them
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
AI and ML Demystified / @carologic / MWUX2017
Regulations take forever
• Humans and algorithms aren’t without bias
• ML has potential to make less biased decisions
• Algorithms trained with biased data
pick up and replicate biases, and develop new ones
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
AI and ML Demystified / @carologic / MWUX2017
How do we evolve the practice of UX
to deal with the new issues
these technologies bring
and the new information that is created?
AI and ML Demystified / @carologic / MWUX2017
Take Responsibility
• Create a code of conduct
– What do you value?
– What lines won’t your AI cross?
• Make your AI transparent
– How was it made and what does it do?
– How do you reduce bias?
• Keep humans in control
AI and ML Demystified / @carologic / MWUX2017
Don’t fear AI - Explore AI
Try the tools
Pair with others
IBM Watson Developer Tools (free trials):
https://console.ng.bluemix.net/catalog/?category=watson
AI and ML Demystified / @carologic / MWUX2017
Go forth and create ethical AI’s
• Purpose: Intelligence and actions to maximize success
• Transparency: Code of Conduct
• Skills: How will humans learn to use it?
AI and ML Demystified / @carologic / MWUX2017
Contact Carol
LinkedIn: https://www.linkedin.com/in/caroljsmith
Twitter - @Carologic: https://twitter.com/carologic
Slides on Slideshare: https://www.slideshare.net/carologic
AI and ML Demystified / @carologic / MWUX2017
Additional Information
and Resources
AI and ML Demystified / @carologic / MWUX2017
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/
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
Tone Analyzer - Watson
IBM Watson Developer Cloud, Tone Analyzer
https://tone-analyzer-demo.mybluemix.net/
AI and ML Demystified / @carologic / MWUX2017
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/
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
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/
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
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
AI and ML Demystified / @carologic / MWUX2017
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
AI and Machine Learning Demystified by Carol Smith at Midwest UX 2017

Más contenido relacionado

Was ist angesagt?

28 Pitching Essentials
28 Pitching Essentials28 Pitching Essentials
28 Pitching EssentialsMichael Parker
 
SXSW 2016: The Need To Knows
SXSW 2016: The Need To KnowsSXSW 2016: The Need To Knows
SXSW 2016: The Need To KnowsOgilvy Consulting
 
The Future of Everything
The Future of EverythingThe Future of Everything
The Future of EverythingCharbel Zeaiter
 
4 Biggest Challenges for Creative Teams
4 Biggest Challenges for Creative Teams4 Biggest Challenges for Creative Teams
4 Biggest Challenges for Creative TeamsWrike
 
Mobile-First SEO - The Marketers Edition #3XEDigital
Mobile-First SEO - The Marketers Edition #3XEDigitalMobile-First SEO - The Marketers Edition #3XEDigital
Mobile-First SEO - The Marketers Edition #3XEDigitalAleyda Solís
 
Analytics Trends 2016: The next evolution
Analytics Trends 2016: The next evolutionAnalytics Trends 2016: The next evolution
Analytics Trends 2016: The next evolutionDeloitte United States
 
100 growth hacks 100 days | 1 to 10
100 growth hacks 100 days | 1 to 10100 growth hacks 100 days | 1 to 10
100 growth hacks 100 days | 1 to 10Robin Yjord
 
Five Killer Ways to Design The Same Slide
Five Killer Ways to Design The Same SlideFive Killer Ways to Design The Same Slide
Five Killer Ways to Design The Same SlideCrispy Presentations
 
Fight for Yourself: How to Sell Your Ideas and Crush Presentations
Fight for Yourself: How to Sell Your Ideas and Crush PresentationsFight for Yourself: How to Sell Your Ideas and Crush Presentations
Fight for Yourself: How to Sell Your Ideas and Crush PresentationsDigital Surgeons
 
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...RachelPearson36
 
How People Are Leveraging ChatGPT
How People Are Leveraging ChatGPTHow People Are Leveraging ChatGPT
How People Are Leveraging ChatGPTRoy Ahuja
 
Forgotten women in tech history.
Forgotten women in tech history.Forgotten women in tech history.
Forgotten women in tech history.Domo
 
Generative AI at the edge.pdf
Generative AI at the edge.pdfGenerative AI at the edge.pdf
Generative AI at the edge.pdfQualcomm Research
 
GENERATIVE AI, THE FUTURE OF PRODUCTIVITY
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYGENERATIVE AI, THE FUTURE OF PRODUCTIVITY
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYAndre Muscat
 
IQ Work Hacks : Verbal communication
IQ Work Hacks : Verbal communication IQ Work Hacks : Verbal communication
IQ Work Hacks : Verbal communication InterQuest Group
 
Productivity Facts Every Employee Should Know
Productivity Facts Every Employee Should KnowProductivity Facts Every Employee Should Know
Productivity Facts Every Employee Should KnowRobert Half
 

Was ist angesagt? (20)

28 Pitching Essentials
28 Pitching Essentials28 Pitching Essentials
28 Pitching Essentials
 
SXSW 2016: The Need To Knows
SXSW 2016: The Need To KnowsSXSW 2016: The Need To Knows
SXSW 2016: The Need To Knows
 
The Future of Everything
The Future of EverythingThe Future of Everything
The Future of Everything
 
4 Biggest Challenges for Creative Teams
4 Biggest Challenges for Creative Teams4 Biggest Challenges for Creative Teams
4 Biggest Challenges for Creative Teams
 
Mobile-First SEO - The Marketers Edition #3XEDigital
Mobile-First SEO - The Marketers Edition #3XEDigitalMobile-First SEO - The Marketers Edition #3XEDigital
Mobile-First SEO - The Marketers Edition #3XEDigital
 
Analytics Trends 2016: The next evolution
Analytics Trends 2016: The next evolutionAnalytics Trends 2016: The next evolution
Analytics Trends 2016: The next evolution
 
100 growth hacks 100 days | 1 to 10
100 growth hacks 100 days | 1 to 10100 growth hacks 100 days | 1 to 10
100 growth hacks 100 days | 1 to 10
 
Unlocking the Power of ChatGPT
Unlocking the Power of ChatGPTUnlocking the Power of ChatGPT
Unlocking the Power of ChatGPT
 
Five Killer Ways to Design The Same Slide
Five Killer Ways to Design The Same SlideFive Killer Ways to Design The Same Slide
Five Killer Ways to Design The Same Slide
 
Fight for Yourself: How to Sell Your Ideas and Crush Presentations
Fight for Yourself: How to Sell Your Ideas and Crush PresentationsFight for Yourself: How to Sell Your Ideas and Crush Presentations
Fight for Yourself: How to Sell Your Ideas and Crush Presentations
 
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
 
How People Are Leveraging ChatGPT
How People Are Leveraging ChatGPTHow People Are Leveraging ChatGPT
How People Are Leveraging ChatGPT
 
Forgotten women in tech history.
Forgotten women in tech history.Forgotten women in tech history.
Forgotten women in tech history.
 
Generative AI at the edge.pdf
Generative AI at the edge.pdfGenerative AI at the edge.pdf
Generative AI at the edge.pdf
 
GENERATIVE AI, THE FUTURE OF PRODUCTIVITY
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYGENERATIVE AI, THE FUTURE OF PRODUCTIVITY
GENERATIVE AI, THE FUTURE OF PRODUCTIVITY
 
IQ Work Hacks : Verbal communication
IQ Work Hacks : Verbal communication IQ Work Hacks : Verbal communication
IQ Work Hacks : Verbal communication
 
The Rise Of China
The Rise Of ChinaThe Rise Of China
The Rise Of China
 
Productivity Facts Every Employee Should Know
Productivity Facts Every Employee Should KnowProductivity Facts Every Employee Should Know
Productivity Facts Every Employee Should Know
 
How Google Works
How Google WorksHow Google Works
How Google Works
 
Build Features, Not Apps
Build Features, Not AppsBuild Features, Not Apps
Build Features, Not Apps
 

Andere mochten auch

Making Great User Experiences, Pittsburgh Scrum MeetUp, Oct 17, 2017
Making Great User Experiences, Pittsburgh Scrum MeetUp, Oct 17, 2017Making Great User Experiences, Pittsburgh Scrum MeetUp, Oct 17, 2017
Making Great User Experiences, Pittsburgh Scrum MeetUp, Oct 17, 2017Carol Smith
 
サーバサイド Kotlin
サーバサイド Kotlinサーバサイド Kotlin
サーバサイド KotlinHiroki Ohtani
 
What is Artificial Intelligence | Artificial Intelligence Tutorial For Beginn...
What is Artificial Intelligence | Artificial Intelligence Tutorial For Beginn...What is Artificial Intelligence | Artificial Intelligence Tutorial For Beginn...
What is Artificial Intelligence | Artificial Intelligence Tutorial For Beginn...Edureka!
 
2017 holiday survey: An annual analysis of the peak shopping season
2017 holiday survey: An annual analysis of the peak shopping season2017 holiday survey: An annual analysis of the peak shopping season
2017 holiday survey: An annual analysis of the peak shopping seasonDeloitte United States
 
나의 이직 이야기
나의 이직 이야기나의 이직 이야기
나의 이직 이야기종립 이
 
Inside Google's Numbers in 2017
Inside Google's Numbers in 2017Inside Google's Numbers in 2017
Inside Google's Numbers in 2017Rand Fishkin
 
Harry Surden - Artificial Intelligence and Law Overview
Harry Surden - Artificial Intelligence and Law OverviewHarry Surden - Artificial Intelligence and Law Overview
Harry Surden - Artificial Intelligence and Law OverviewHarry Surden
 
Dockerで始める Java EE アプリケーション開発 for JJUG CCC 2017
Dockerで始める Java EE アプリケーション開発 for JJUG CCC 2017Dockerで始める Java EE アプリケーション開発 for JJUG CCC 2017
Dockerで始める Java EE アプリケーション開発 for JJUG CCC 2017Kohei Saito
 
さくらのVPS で IPv4 over IPv6ルータの構築
さくらのVPS で IPv4 over IPv6ルータの構築さくらのVPS で IPv4 over IPv6ルータの構築
さくらのVPS で IPv4 over IPv6ルータの構築Tomocha Potter
 
DDD x CQRS 更新系と参照系で異なるORMを併用して上手くいった話
DDD x CQRS   更新系と参照系で異なるORMを併用して上手くいった話DDD x CQRS   更新系と参照系で異なるORMを併用して上手くいった話
DDD x CQRS 更新系と参照系で異なるORMを併用して上手くいった話Koichiro Matsuoka
 
Paginas de matematicas
Paginas de matematicasPaginas de matematicas
Paginas de matematicasespanol
 
Taming the ever-evolving Compliance Beast : Lessons learnt at LinkedIn [Strat...
Taming the ever-evolving Compliance Beast : Lessons learnt at LinkedIn [Strat...Taming the ever-evolving Compliance Beast : Lessons learnt at LinkedIn [Strat...
Taming the ever-evolving Compliance Beast : Lessons learnt at LinkedIn [Strat...Shirshanka Das
 
Spring Bootの本当の理解ポイント #jjug
Spring Bootの本当の理解ポイント #jjugSpring Bootの本当の理解ポイント #jjug
Spring Bootの本当の理解ポイント #jjugMasatoshi Tada
 
Business Process Modeling in Goldman Sachs @ JJUG CCC Fall 2017
Business Process Modeling in Goldman Sachs @ JJUG CCC Fall 2017Business Process Modeling in Goldman Sachs @ JJUG CCC Fall 2017
Business Process Modeling in Goldman Sachs @ JJUG CCC Fall 2017tty fky
 
UX in the Age of AI: Where Does Design Fit In? Fluxible 2017
UX in the Age of AI: Where Does Design Fit In? Fluxible 2017UX in the Age of AI: Where Does Design Fit In? Fluxible 2017
UX in the Age of AI: Where Does Design Fit In? Fluxible 2017Carol Smith
 
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...Edureka!
 
高速なソートアルゴリズムを書こう!!
高速なソートアルゴリズムを書こう!!高速なソートアルゴリズムを書こう!!
高速なソートアルゴリズムを書こう!!masakazu matsubara
 

Andere mochten auch (20)

The AI Rush
The AI RushThe AI Rush
The AI Rush
 
SlideShare 101
SlideShare 101SlideShare 101
SlideShare 101
 
10 facts about jobs in the future
10 facts about jobs in the future10 facts about jobs in the future
10 facts about jobs in the future
 
Making Great User Experiences, Pittsburgh Scrum MeetUp, Oct 17, 2017
Making Great User Experiences, Pittsburgh Scrum MeetUp, Oct 17, 2017Making Great User Experiences, Pittsburgh Scrum MeetUp, Oct 17, 2017
Making Great User Experiences, Pittsburgh Scrum MeetUp, Oct 17, 2017
 
サーバサイド Kotlin
サーバサイド Kotlinサーバサイド Kotlin
サーバサイド Kotlin
 
What is Artificial Intelligence | Artificial Intelligence Tutorial For Beginn...
What is Artificial Intelligence | Artificial Intelligence Tutorial For Beginn...What is Artificial Intelligence | Artificial Intelligence Tutorial For Beginn...
What is Artificial Intelligence | Artificial Intelligence Tutorial For Beginn...
 
2017 holiday survey: An annual analysis of the peak shopping season
2017 holiday survey: An annual analysis of the peak shopping season2017 holiday survey: An annual analysis of the peak shopping season
2017 holiday survey: An annual analysis of the peak shopping season
 
나의 이직 이야기
나의 이직 이야기나의 이직 이야기
나의 이직 이야기
 
Inside Google's Numbers in 2017
Inside Google's Numbers in 2017Inside Google's Numbers in 2017
Inside Google's Numbers in 2017
 
Harry Surden - Artificial Intelligence and Law Overview
Harry Surden - Artificial Intelligence and Law OverviewHarry Surden - Artificial Intelligence and Law Overview
Harry Surden - Artificial Intelligence and Law Overview
 
Dockerで始める Java EE アプリケーション開発 for JJUG CCC 2017
Dockerで始める Java EE アプリケーション開発 for JJUG CCC 2017Dockerで始める Java EE アプリケーション開発 for JJUG CCC 2017
Dockerで始める Java EE アプリケーション開発 for JJUG CCC 2017
 
さくらのVPS で IPv4 over IPv6ルータの構築
さくらのVPS で IPv4 over IPv6ルータの構築さくらのVPS で IPv4 over IPv6ルータの構築
さくらのVPS で IPv4 over IPv6ルータの構築
 
DDD x CQRS 更新系と参照系で異なるORMを併用して上手くいった話
DDD x CQRS   更新系と参照系で異なるORMを併用して上手くいった話DDD x CQRS   更新系と参照系で異なるORMを併用して上手くいった話
DDD x CQRS 更新系と参照系で異なるORMを併用して上手くいった話
 
Paginas de matematicas
Paginas de matematicasPaginas de matematicas
Paginas de matematicas
 
Taming the ever-evolving Compliance Beast : Lessons learnt at LinkedIn [Strat...
Taming the ever-evolving Compliance Beast : Lessons learnt at LinkedIn [Strat...Taming the ever-evolving Compliance Beast : Lessons learnt at LinkedIn [Strat...
Taming the ever-evolving Compliance Beast : Lessons learnt at LinkedIn [Strat...
 
Spring Bootの本当の理解ポイント #jjug
Spring Bootの本当の理解ポイント #jjugSpring Bootの本当の理解ポイント #jjug
Spring Bootの本当の理解ポイント #jjug
 
Business Process Modeling in Goldman Sachs @ JJUG CCC Fall 2017
Business Process Modeling in Goldman Sachs @ JJUG CCC Fall 2017Business Process Modeling in Goldman Sachs @ JJUG CCC Fall 2017
Business Process Modeling in Goldman Sachs @ JJUG CCC Fall 2017
 
UX in the Age of AI: Where Does Design Fit In? Fluxible 2017
UX in the Age of AI: Where Does Design Fit In? Fluxible 2017UX in the Age of AI: Where Does Design Fit In? Fluxible 2017
UX in the Age of AI: Where Does Design Fit In? Fluxible 2017
 
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
 
高速なソートアルゴリズムを書こう!!
高速なソートアルゴリズムを書こう!!高速なソートアルゴリズムを書こう!!
高速なソートアルゴリズムを書こう!!
 

Ähnlich wie AI and Machine Learning Demystified by Carol Smith at Midwest UX 2017

Designing AI for Humanity at dmi:Design Leadership Conference in Boston
Designing AI for Humanity at dmi:Design Leadership Conference in BostonDesigning AI for Humanity at dmi:Design Leadership Conference in Boston
Designing AI for Humanity at dmi:Design Leadership Conference in BostonCarol Smith
 
Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019
Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019
Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019Carol Smith
 
IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018
IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018
IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018Carol Smith
 
UX in the Age of AI: Leading with Design
UX in the Age of AI: Leading with DesignUX in the Age of AI: Leading with Design
UX in the Age of AI: Leading with DesignUXPA International
 
UX in the Age of AI: Leading with Design UXPA2018
UX in the Age of AI: Leading with Design UXPA2018UX in the Age of AI: Leading with Design UXPA2018
UX in the Age of AI: Leading with Design UXPA2018Carol Smith
 
AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17
AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17
AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17Carol Smith
 
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...Chetan Khatri
 
Designing Trustable AI Experiences at World Usability Day in Cleveland
Designing Trustable AI Experiences at World Usability Day in ClevelandDesigning Trustable AI Experiences at World Usability Day in Cleveland
Designing Trustable AI Experiences at World Usability Day in ClevelandCarol Smith
 
Dynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in Toronto
Dynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in TorontoDynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in Toronto
Dynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in TorontoCarol Smith
 
Artificial Intelligence and Machine Learning
Artificial Intelligence and Machine LearningArtificial Intelligence and Machine Learning
Artificial Intelligence and Machine LearningMykola Dobrochynskyy
 
Practical Machine Ethics @ SXSW2019
Practical Machine Ethics @ SXSW2019Practical Machine Ethics @ SXSW2019
Practical Machine Ethics @ SXSW2019Jesus Ramos
 
Ai recent trends in technology v3
Ai   recent trends in technology v3Ai   recent trends in technology v3
Ai recent trends in technology v3Sibasish Chowdhury
 
Generative Artificial Intelligence and Data Privacy: A Primer
Generative Artificial Intelligence and Data Privacy: A Primer Generative Artificial Intelligence and Data Privacy: A Primer
Generative Artificial Intelligence and Data Privacy: A Primer Internet Law Center
 
Présentation de Bruno Schroder au 20e #mforum (07/12/2016)
Présentation de Bruno Schroder au 20e #mforum (07/12/2016)Présentation de Bruno Schroder au 20e #mforum (07/12/2016)
Présentation de Bruno Schroder au 20e #mforum (07/12/2016)Agence du Numérique (AdN)
 
AI, Robotics, and Smart Contracts
AI, Robotics, and Smart ContractsAI, Robotics, and Smart Contracts
AI, Robotics, and Smart ContractsSteve Omohundro
 
UX for Artificial Intelligence / UXcamp Europe '17 / Berlin / Jan Korsanke
UX for Artificial Intelligence / UXcamp Europe '17 / Berlin / Jan KorsankeUX for Artificial Intelligence / UXcamp Europe '17 / Berlin / Jan Korsanke
UX for Artificial Intelligence / UXcamp Europe '17 / Berlin / Jan KorsankeJan Korsanke
 
EDW 2015 cognitive computing panel session
EDW 2015 cognitive computing panel session EDW 2015 cognitive computing panel session
EDW 2015 cognitive computing panel session Steve Ardire
 
The Rising Tide Raises All Boats: The Advancement of Science of Cybersecurity
The Rising Tide Raises All Boats:  The Advancement of Science of CybersecurityThe Rising Tide Raises All Boats:  The Advancement of Science of Cybersecurity
The Rising Tide Raises All Boats: The Advancement of Science of Cybersecuritylaurieannwilliams
 
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...Kalilur Rahman
 

Ähnlich wie AI and Machine Learning Demystified by Carol Smith at Midwest UX 2017 (20)

Designing AI for Humanity at dmi:Design Leadership Conference in Boston
Designing AI for Humanity at dmi:Design Leadership Conference in BostonDesigning AI for Humanity at dmi:Design Leadership Conference in Boston
Designing AI for Humanity at dmi:Design Leadership Conference in Boston
 
Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019
Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019
Designing Trustable AI Experiences at IxDA Pittsburgh, Jan 2019
 
IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018
IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018
IA in the Age of AI: Embracing Abstraction and Change at IA Summit 2018
 
UX in the Age of AI: Leading with Design
UX in the Age of AI: Leading with DesignUX in the Age of AI: Leading with Design
UX in the Age of AI: Leading with Design
 
UX in the Age of AI: Leading with Design UXPA2018
UX in the Age of AI: Leading with Design UXPA2018UX in the Age of AI: Leading with Design UXPA2018
UX in the Age of AI: Leading with Design UXPA2018
 
AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17
AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17
AI for IA's: Machine Learning Demystified at IA Summit 2017 - IAS17
 
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
 
Designing Trustable AI Experiences at World Usability Day in Cleveland
Designing Trustable AI Experiences at World Usability Day in ClevelandDesigning Trustable AI Experiences at World Usability Day in Cleveland
Designing Trustable AI Experiences at World Usability Day in Cleveland
 
Dynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in Toronto
Dynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in TorontoDynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in Toronto
Dynamic UXR: Ethical Responsibilities and AI. Carol Smith at Strive in Toronto
 
Artificial Intelligence and Machine Learning
Artificial Intelligence and Machine LearningArtificial Intelligence and Machine Learning
Artificial Intelligence and Machine Learning
 
Practical Machine Ethics @ SXSW2019
Practical Machine Ethics @ SXSW2019Practical Machine Ethics @ SXSW2019
Practical Machine Ethics @ SXSW2019
 
Ai recent trends in technology v3
Ai   recent trends in technology v3Ai   recent trends in technology v3
Ai recent trends in technology v3
 
Generative Artificial Intelligence and Data Privacy: A Primer
Generative Artificial Intelligence and Data Privacy: A Primer Generative Artificial Intelligence and Data Privacy: A Primer
Generative Artificial Intelligence and Data Privacy: A Primer
 
Présentation de Bruno Schroder au 20e #mforum (07/12/2016)
Présentation de Bruno Schroder au 20e #mforum (07/12/2016)Présentation de Bruno Schroder au 20e #mforum (07/12/2016)
Présentation de Bruno Schroder au 20e #mforum (07/12/2016)
 
AI, Robotics, and Smart Contracts
AI, Robotics, and Smart ContractsAI, Robotics, and Smart Contracts
AI, Robotics, and Smart Contracts
 
UX for Artificial Intelligence / UXcamp Europe '17 / Berlin / Jan Korsanke
UX for Artificial Intelligence / UXcamp Europe '17 / Berlin / Jan KorsankeUX for Artificial Intelligence / UXcamp Europe '17 / Berlin / Jan Korsanke
UX for Artificial Intelligence / UXcamp Europe '17 / Berlin / Jan Korsanke
 
Ai titech-virach-20191026
Ai titech-virach-20191026Ai titech-virach-20191026
Ai titech-virach-20191026
 
EDW 2015 cognitive computing panel session
EDW 2015 cognitive computing panel session EDW 2015 cognitive computing panel session
EDW 2015 cognitive computing panel session
 
The Rising Tide Raises All Boats: The Advancement of Science of Cybersecurity
The Rising Tide Raises All Boats:  The Advancement of Science of CybersecurityThe Rising Tide Raises All Boats:  The Advancement of Science of Cybersecurity
The Rising Tide Raises All Boats: The Advancement of Science of Cybersecurity
 
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...
 

Mehr von Carol Smith

Navigating the Complexity of Trust at UXPA Boston 2021
Navigating the Complexity of Trust at UXPA Boston 2021Navigating the Complexity of Trust at UXPA Boston 2021
Navigating the Complexity of Trust at UXPA Boston 2021Carol Smith
 
Implementing Ethics: Developing Trustworthy AI PyCon 2020
Implementing Ethics: Developing Trustworthy AI PyCon 2020Implementing Ethics: Developing Trustworthy AI PyCon 2020
Implementing Ethics: Developing Trustworthy AI PyCon 2020Carol Smith
 
Designing Trustworthy AI: A User Experience Framework at RSA 2020
Designing Trustworthy AI: A User Experience Framework at RSA 2020Designing Trustworthy AI: A User Experience Framework at RSA 2020
Designing Trustworthy AI: A User Experience Framework at RSA 2020Carol Smith
 
IA is Elemental: People are Fundamental at World IA Day 2020 Pittsburgh
IA is Elemental: People are Fundamental at World IA Day 2020 PittsburghIA is Elemental: People are Fundamental at World IA Day 2020 Pittsburgh
IA is Elemental: People are Fundamental at World IA Day 2020 PittsburghCarol Smith
 
Gearing up for Ethnography, Michigan State, World Usability Day 2019
Gearing up for Ethnography, Michigan State, World Usability Day 2019Gearing up for Ethnography, Michigan State, World Usability Day 2019
Gearing up for Ethnography, Michigan State, World Usability Day 2019Carol Smith
 
Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Developm...
Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Developm...Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Developm...
Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Developm...Carol Smith
 
On the Road: Best Practices for Autonomous Experiences at WUC19
On the Road: Best Practices for Autonomous Experiences at WUC19On the Road: Best Practices for Autonomous Experiences at WUC19
On the Road: Best Practices for Autonomous Experiences at WUC19Carol Smith
 
Designing More Ethical and Unbiased Experiences - Abstractions
Designing More Ethical and Unbiased Experiences - AbstractionsDesigning More Ethical and Unbiased Experiences - Abstractions
Designing More Ethical and Unbiased Experiences - AbstractionsCarol Smith
 
Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019
Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019
Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019Carol Smith
 
Navigating challenges in IA people management at IAC19
Navigating challenges in IA people management at IAC19Navigating challenges in IA people management at IAC19
Navigating challenges in IA people management at IAC19Carol Smith
 
What can DesignOps do for you? by Carol Smith at TLMUX in Montreal
What can DesignOps do for you? by Carol Smith at TLMUX in MontrealWhat can DesignOps do for you? by Carol Smith at TLMUX in Montreal
What can DesignOps do for you? by Carol Smith at TLMUX in MontrealCarol Smith
 
Gearing up for Ethnography at Midwest UX 2018
Gearing up for Ethnography at Midwest UX 2018Gearing up for Ethnography at Midwest UX 2018
Gearing up for Ethnography at Midwest UX 2018Carol Smith
 
Product Design in Agile Environments: Making it Work at ProductCamp Pittsburgh
Product Design in Agile Environments: Making it Work at ProductCamp PittsburghProduct Design in Agile Environments: Making it Work at ProductCamp Pittsburgh
Product Design in Agile Environments: Making it Work at ProductCamp PittsburghCarol Smith
 
Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...
Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...
Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...Carol Smith
 
Making Great User Experiences at Cleveland C# .Net Meetup July 27 2017
Making Great User Experiences at Cleveland C# .Net Meetup July 27 2017Making Great User Experiences at Cleveland C# .Net Meetup July 27 2017
Making Great User Experiences at Cleveland C# .Net Meetup July 27 2017Carol Smith
 
Faster Usability Testing in an Agile World - Agile UX Virtual Summit 2017 by ...
Faster Usability Testing in an Agile World - Agile UX Virtual Summit 2017 by ...Faster Usability Testing in an Agile World - Agile UX Virtual Summit 2017 by ...
Faster Usability Testing in an Agile World - Agile UX Virtual Summit 2017 by ...Carol Smith
 
Making Faster UX in an Agile World - HOAPitt 2017
Making Faster UX in an Agile World - HOAPitt 2017Making Faster UX in an Agile World - HOAPitt 2017
Making Faster UX in an Agile World - HOAPitt 2017Carol Smith
 
Design vs.Cancer: Patients Win UXDC 2017
Design vs.Cancer: Patients Win UXDC 2017Design vs.Cancer: Patients Win UXDC 2017
Design vs.Cancer: Patients Win UXDC 2017Carol Smith
 
DIY Usability Testing for Business Analysts (BA)
DIY Usability Testing for Business Analysts (BA)DIY Usability Testing for Business Analysts (BA)
DIY Usability Testing for Business Analysts (BA)Carol Smith
 
Mature Products: The Cycle of UX Reinvention UXPA 2016
Mature Products: The Cycle of UX Reinvention UXPA 2016Mature Products: The Cycle of UX Reinvention UXPA 2016
Mature Products: The Cycle of UX Reinvention UXPA 2016Carol Smith
 

Mehr von Carol Smith (20)

Navigating the Complexity of Trust at UXPA Boston 2021
Navigating the Complexity of Trust at UXPA Boston 2021Navigating the Complexity of Trust at UXPA Boston 2021
Navigating the Complexity of Trust at UXPA Boston 2021
 
Implementing Ethics: Developing Trustworthy AI PyCon 2020
Implementing Ethics: Developing Trustworthy AI PyCon 2020Implementing Ethics: Developing Trustworthy AI PyCon 2020
Implementing Ethics: Developing Trustworthy AI PyCon 2020
 
Designing Trustworthy AI: A User Experience Framework at RSA 2020
Designing Trustworthy AI: A User Experience Framework at RSA 2020Designing Trustworthy AI: A User Experience Framework at RSA 2020
Designing Trustworthy AI: A User Experience Framework at RSA 2020
 
IA is Elemental: People are Fundamental at World IA Day 2020 Pittsburgh
IA is Elemental: People are Fundamental at World IA Day 2020 PittsburghIA is Elemental: People are Fundamental at World IA Day 2020 Pittsburgh
IA is Elemental: People are Fundamental at World IA Day 2020 Pittsburgh
 
Gearing up for Ethnography, Michigan State, World Usability Day 2019
Gearing up for Ethnography, Michigan State, World Usability Day 2019Gearing up for Ethnography, Michigan State, World Usability Day 2019
Gearing up for Ethnography, Michigan State, World Usability Day 2019
 
Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Developm...
Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Developm...Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Developm...
Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Developm...
 
On the Road: Best Practices for Autonomous Experiences at WUC19
On the Road: Best Practices for Autonomous Experiences at WUC19On the Road: Best Practices for Autonomous Experiences at WUC19
On the Road: Best Practices for Autonomous Experiences at WUC19
 
Designing More Ethical and Unbiased Experiences - Abstractions
Designing More Ethical and Unbiased Experiences - AbstractionsDesigning More Ethical and Unbiased Experiences - Abstractions
Designing More Ethical and Unbiased Experiences - Abstractions
 
Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019
Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019
Prototyping for Beginners - Pittsburgh Inclusive Innovation Summit 2019
 
Navigating challenges in IA people management at IAC19
Navigating challenges in IA people management at IAC19Navigating challenges in IA people management at IAC19
Navigating challenges in IA people management at IAC19
 
What can DesignOps do for you? by Carol Smith at TLMUX in Montreal
What can DesignOps do for you? by Carol Smith at TLMUX in MontrealWhat can DesignOps do for you? by Carol Smith at TLMUX in Montreal
What can DesignOps do for you? by Carol Smith at TLMUX in Montreal
 
Gearing up for Ethnography at Midwest UX 2018
Gearing up for Ethnography at Midwest UX 2018Gearing up for Ethnography at Midwest UX 2018
Gearing up for Ethnography at Midwest UX 2018
 
Product Design in Agile Environments: Making it Work at ProductCamp Pittsburgh
Product Design in Agile Environments: Making it Work at ProductCamp PittsburghProduct Design in Agile Environments: Making it Work at ProductCamp Pittsburgh
Product Design in Agile Environments: Making it Work at ProductCamp Pittsburgh
 
Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...
Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...
Demystifying Artificial Intelligence: Solving Difficult Problems at ProductCa...
 
Making Great User Experiences at Cleveland C# .Net Meetup July 27 2017
Making Great User Experiences at Cleveland C# .Net Meetup July 27 2017Making Great User Experiences at Cleveland C# .Net Meetup July 27 2017
Making Great User Experiences at Cleveland C# .Net Meetup July 27 2017
 
Faster Usability Testing in an Agile World - Agile UX Virtual Summit 2017 by ...
Faster Usability Testing in an Agile World - Agile UX Virtual Summit 2017 by ...Faster Usability Testing in an Agile World - Agile UX Virtual Summit 2017 by ...
Faster Usability Testing in an Agile World - Agile UX Virtual Summit 2017 by ...
 
Making Faster UX in an Agile World - HOAPitt 2017
Making Faster UX in an Agile World - HOAPitt 2017Making Faster UX in an Agile World - HOAPitt 2017
Making Faster UX in an Agile World - HOAPitt 2017
 
Design vs.Cancer: Patients Win UXDC 2017
Design vs.Cancer: Patients Win UXDC 2017Design vs.Cancer: Patients Win UXDC 2017
Design vs.Cancer: Patients Win UXDC 2017
 
DIY Usability Testing for Business Analysts (BA)
DIY Usability Testing for Business Analysts (BA)DIY Usability Testing for Business Analysts (BA)
DIY Usability Testing for Business Analysts (BA)
 
Mature Products: The Cycle of UX Reinvention UXPA 2016
Mature Products: The Cycle of UX Reinvention UXPA 2016Mature Products: The Cycle of UX Reinvention UXPA 2016
Mature Products: The Cycle of UX Reinvention UXPA 2016
 

Último

We are inviting you on board, to move forward together in the Right Direction
We are inviting you on board, to move forward together in the Right DirectionWe are inviting you on board, to move forward together in the Right Direction
We are inviting you on board, to move forward together in the Right DirectionRight Direction Aero
 
PHX Corporate Presentation March 2024 Final
PHX Corporate Presentation March 2024 FinalPHX Corporate Presentation March 2024 Final
PHX Corporate Presentation March 2024 FinalPanhandleOilandGas
 
HOW TO START EARNING WITH AFFILIATE MARKETING
HOW TO START EARNING WITH AFFILIATE MARKETINGHOW TO START EARNING WITH AFFILIATE MARKETING
HOW TO START EARNING WITH AFFILIATE MARKETINGNATHAN SPEAKS
 
Business Models and Business Model Innovation
Business Models and Business Model InnovationBusiness Models and Business Model Innovation
Business Models and Business Model InnovationMichal Hron
 
ICv2 Hobby Games White Paper 2024 - State of the Industry
ICv2 Hobby Games White Paper 2024 - State of the IndustryICv2 Hobby Games White Paper 2024 - State of the Industry
ICv2 Hobby Games White Paper 2024 - State of the IndustryDennisViau
 
Project Work on Consumer Behavior in Fast Food Restaurants. Their behavior to...
Project Work on Consumer Behavior in Fast Food Restaurants. Their behavior to...Project Work on Consumer Behavior in Fast Food Restaurants. Their behavior to...
Project Work on Consumer Behavior in Fast Food Restaurants. Their behavior to...BilalAhmed717
 
Reframing Requirements: A Strategic Approach to Requirement Definition, with ...
Reframing Requirements: A Strategic Approach to Requirement Definition, with ...Reframing Requirements: A Strategic Approach to Requirement Definition, with ...
Reframing Requirements: A Strategic Approach to Requirement Definition, with ...Jake Truemper
 
Shravan Kumaran and sanjay kumaran.pdf..
Shravan Kumaran and sanjay kumaran.pdf..Shravan Kumaran and sanjay kumaran.pdf..
Shravan Kumaran and sanjay kumaran.pdf..ranjithapriya2
 
Benihana of Tokyo case study11111111.pdf
Benihana of Tokyo case study11111111.pdfBenihana of Tokyo case study11111111.pdf
Benihana of Tokyo case study11111111.pdfjavenxxx01
 
10 Tips for Great Teams CSUN Conference 2024
10 Tips for Great Teams CSUN Conference 202410 Tips for Great Teams CSUN Conference 2024
10 Tips for Great Teams CSUN Conference 2024Nate Evans
 
Pitch Deck Teardown: SuperScale's $5.4M Series A deck
Pitch Deck Teardown: SuperScale's $5.4M Series A deckPitch Deck Teardown: SuperScale's $5.4M Series A deck
Pitch Deck Teardown: SuperScale's $5.4M Series A deckHajeJanKamps
 
L-1 VISA Business (Plan Sample) - Plan Writers
L-1 VISA Business (Plan Sample) - Plan WritersL-1 VISA Business (Plan Sample) - Plan Writers
L-1 VISA Business (Plan Sample) - Plan WritersPlan Writers
 
Bus Eth ch3 ppt.ppt business ethics and corporate social responsibilities ppt
Bus Eth ch3 ppt.ppt business ethics and corporate social responsibilities pptBus Eth ch3 ppt.ppt business ethics and corporate social responsibilities ppt
Bus Eth ch3 ppt.ppt business ethics and corporate social responsibilities pptendeworku
 
AirOxi - Pioneering Aquaculture Advancements Through NFDB Empanelment.pptx
AirOxi -  Pioneering Aquaculture Advancements Through NFDB Empanelment.pptxAirOxi -  Pioneering Aquaculture Advancements Through NFDB Empanelment.pptx
AirOxi - Pioneering Aquaculture Advancements Through NFDB Empanelment.pptxAirOxi Tube
 
The Smart Bridge Interview now Veranda Learning
The Smart Bridge Interview now Veranda LearningThe Smart Bridge Interview now Veranda Learning
The Smart Bridge Interview now Veranda LearningNaval Singh
 
CORPORATE SOCIAL RESPONSIBILITY - FINAL REQUIREMENT.pdf
CORPORATE SOCIAL RESPONSIBILITY - FINAL REQUIREMENT.pdfCORPORATE SOCIAL RESPONSIBILITY - FINAL REQUIREMENT.pdf
CORPORATE SOCIAL RESPONSIBILITY - FINAL REQUIREMENT.pdfLouis Malaybalay
 
A Comprehensive Case Study on the IL&FS Crisis (final).pptx
A Comprehensive Case Study on the IL&FS Crisis (final).pptxA Comprehensive Case Study on the IL&FS Crisis (final).pptx
A Comprehensive Case Study on the IL&FS Crisis (final).pptxShainaMaheshwari1
 
unfinished legacy it is a clothing brand
unfinished legacy it is a clothing brandunfinished legacy it is a clothing brand
unfinished legacy it is a clothing brandakashm530190
 
Presented by Sabri international .......
Presented by Sabri international .......Presented by Sabri international .......
Presented by Sabri international .......SABRI INTERNATIONAL
 

Último (20)

We are inviting you on board, to move forward together in the Right Direction
We are inviting you on board, to move forward together in the Right DirectionWe are inviting you on board, to move forward together in the Right Direction
We are inviting you on board, to move forward together in the Right Direction
 
PHX Corporate Presentation March 2024 Final
PHX Corporate Presentation March 2024 FinalPHX Corporate Presentation March 2024 Final
PHX Corporate Presentation March 2024 Final
 
HOW TO START EARNING WITH AFFILIATE MARKETING
HOW TO START EARNING WITH AFFILIATE MARKETINGHOW TO START EARNING WITH AFFILIATE MARKETING
HOW TO START EARNING WITH AFFILIATE MARKETING
 
Business Models and Business Model Innovation
Business Models and Business Model InnovationBusiness Models and Business Model Innovation
Business Models and Business Model Innovation
 
ICv2 Hobby Games White Paper 2024 - State of the Industry
ICv2 Hobby Games White Paper 2024 - State of the IndustryICv2 Hobby Games White Paper 2024 - State of the Industry
ICv2 Hobby Games White Paper 2024 - State of the Industry
 
Project Work on Consumer Behavior in Fast Food Restaurants. Their behavior to...
Project Work on Consumer Behavior in Fast Food Restaurants. Their behavior to...Project Work on Consumer Behavior in Fast Food Restaurants. Their behavior to...
Project Work on Consumer Behavior in Fast Food Restaurants. Their behavior to...
 
Reframing Requirements: A Strategic Approach to Requirement Definition, with ...
Reframing Requirements: A Strategic Approach to Requirement Definition, with ...Reframing Requirements: A Strategic Approach to Requirement Definition, with ...
Reframing Requirements: A Strategic Approach to Requirement Definition, with ...
 
Shravan Kumaran and sanjay kumaran.pdf..
Shravan Kumaran and sanjay kumaran.pdf..Shravan Kumaran and sanjay kumaran.pdf..
Shravan Kumaran and sanjay kumaran.pdf..
 
Benihana of Tokyo case study11111111.pdf
Benihana of Tokyo case study11111111.pdfBenihana of Tokyo case study11111111.pdf
Benihana of Tokyo case study11111111.pdf
 
10 Tips for Great Teams CSUN Conference 2024
10 Tips for Great Teams CSUN Conference 202410 Tips for Great Teams CSUN Conference 2024
10 Tips for Great Teams CSUN Conference 2024
 
Pitch Deck Teardown: SuperScale's $5.4M Series A deck
Pitch Deck Teardown: SuperScale's $5.4M Series A deckPitch Deck Teardown: SuperScale's $5.4M Series A deck
Pitch Deck Teardown: SuperScale's $5.4M Series A deck
 
L-1 VISA Business (Plan Sample) - Plan Writers
L-1 VISA Business (Plan Sample) - Plan WritersL-1 VISA Business (Plan Sample) - Plan Writers
L-1 VISA Business (Plan Sample) - Plan Writers
 
Bus Eth ch3 ppt.ppt business ethics and corporate social responsibilities ppt
Bus Eth ch3 ppt.ppt business ethics and corporate social responsibilities pptBus Eth ch3 ppt.ppt business ethics and corporate social responsibilities ppt
Bus Eth ch3 ppt.ppt business ethics and corporate social responsibilities ppt
 
AirOxi - Pioneering Aquaculture Advancements Through NFDB Empanelment.pptx
AirOxi -  Pioneering Aquaculture Advancements Through NFDB Empanelment.pptxAirOxi -  Pioneering Aquaculture Advancements Through NFDB Empanelment.pptx
AirOxi - Pioneering Aquaculture Advancements Through NFDB Empanelment.pptx
 
The Smart Bridge Interview now Veranda Learning
The Smart Bridge Interview now Veranda LearningThe Smart Bridge Interview now Veranda Learning
The Smart Bridge Interview now Veranda Learning
 
CORPORATE SOCIAL RESPONSIBILITY - FINAL REQUIREMENT.pdf
CORPORATE SOCIAL RESPONSIBILITY - FINAL REQUIREMENT.pdfCORPORATE SOCIAL RESPONSIBILITY - FINAL REQUIREMENT.pdf
CORPORATE SOCIAL RESPONSIBILITY - FINAL REQUIREMENT.pdf
 
WAM Corporate Presentation Mar 12 2024_Video.pdf
WAM Corporate Presentation Mar 12 2024_Video.pdfWAM Corporate Presentation Mar 12 2024_Video.pdf
WAM Corporate Presentation Mar 12 2024_Video.pdf
 
A Comprehensive Case Study on the IL&FS Crisis (final).pptx
A Comprehensive Case Study on the IL&FS Crisis (final).pptxA Comprehensive Case Study on the IL&FS Crisis (final).pptx
A Comprehensive Case Study on the IL&FS Crisis (final).pptx
 
unfinished legacy it is a clothing brand
unfinished legacy it is a clothing brandunfinished legacy it is a clothing brand
unfinished legacy it is a clothing brand
 
Presented by Sabri international .......
Presented by Sabri international .......Presented by Sabri international .......
Presented by Sabri international .......
 

AI and Machine Learning Demystified by Carol Smith at Midwest UX 2017

  • 1. AI and Machine Learning Demystified Carol Smith @carologic Midwest UX 2017, Cincinnati, Ohio October 13, 2017
  • 2. AI is when Machines – Exhibit intelligence – Perceive their environment – Take actions/make decision to maximize chance of success at a goal NAO’s New Job as “Connie” the concierge at Hilton Hotels https://developer.softbankrobotics.com/us-en/showcase/nao-ibm-create-new-hilton-concierge
  • 3. AI and ML Demystified / @carologic / MWUX2017 In the extreme… Google Search for “movies with AI” Copyrights as labeled.
  • 4. “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 http://www.wired.co.uk/article/elon-musk- artificial-intelligence-scaremongering
  • 5. Remember: “We can unplug the machines!” Grady Booch, Scientist, philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
  • 6. AI and ML Demystified / @carologic / MWUX2017 Cognitive computers are • Made with algorithms • Knowledgeable ONLY about what taught • Control ONLY what we give them control of • Aware of nuances and can continue to learn more
  • 7. AI and ML Demystified / @carologic / MWUX2017 Cognitive computers (algorithms) can… • Do very boring work for you • Often make better, more consistent decisions than humans • Be efficient, won’t get tired 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
  • 8. AI and ML Demystified / @carologic / MWUX2017 Exhibit intelligence - transfer human concepts and relationships Photo by sunlightfoundation https://www.flickr.com/photos/sunlightfoundation/2385174105
  • 9. AI and ML Demystified / @carologic / MWUX2017 Dependent on Experts • Subject Matter Experts (SME’s) Availability – Lawyers – Machinists – Insurance adjusters – Physicians • Usually not experienced in machine learning – Need close collaboration with those making algorithms
  • 10. AI and ML Demystified / @carologic / MWUX2017 Number Five “Needs Input” Short Circuit (1986 film) - Ally Sheedy and Number Five https://en.wikipedia.org/wiki/Short_Circuit_(1986_film)
  • 11. AI and ML Demystified / @carologic / MWUX2017 Content is annotated by experts Image created by Angela Swindell, Visual Designer, Watson Knowledge Studio
  • 12. AI and ML Demystified / @carologic / MWUX2017 AI is taxonomies and ontologies coming to life (NOT like humans learn) Photo: https://commons.wikimedia.org/wiki/File:Baby_Boy_Oliver.jpg
  • 14. Only as good as data and time spent improving it Biased based on what it taught
  • 15. AI and ML Demystified / @carologic / MWUX2017 Creating an AI requires • Algorithms • Documents • Ground truth (annotation) • Teaching • Iteration • Repeat
  • 16. AI and ML Demystified / @carologic / MWUX2017 Supervised (by a human) Machine Learning Watson Knowledge Studio https://www.ibm.com/us-en/marketplace/supervised-machine-learning
  • 17. AI and ML Demystified / @carologic / MWUX2017 Knowledge and Accuracy • 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
  • 18. AI and ML Demystified / @carologic / MWUX2017 Across industries – priority of accuracy varies Higher Priority 90-99%+ Lower Priority 60-89% accuracy is acceptable
  • 19. AI and ML Demystified / @carologic / MWUX2017 Goal is saving time Machine learning creates more highly trained specialists Not an “all knowing” being
  • 20. AI and ML Demystified / @carologic / MWUX2017 Cancer Burden in Sub-Saharan Africa Risk of getting cancer and Risk of Dying ~same The Cancer Atlas http://canceratlas.cancer.org/the-burden/
  • 21. AI and ML Demystified / @carologic / MWUX2017 What if we could reduce the burden? • Bring taxonomies and ontologies to life • Broaden access to evidence based medicine • More informed treatment decisions
  • 22. AI and ML Demystified / @carologic / MWUX2017 AI actions for success • Example: Healthcare – AI analyzes data (treatment options, similar patients) – Goal: Provide quick, evidence based options – Physician selects treatment for patients based on situation • AI success is helping physician (not replacing)
  • 23. AI and ML Demystified / @carologic / MWUX2017 Examples of AI and Cognitive Computing
  • 24. AI and ML Demystified / @carologic / MWUX2017 Consider for each example • What intelligence does the system need? • What is the AI perceiving in their environment? • What actions are taken to maximize chance of success at goal?
  • 25. AI and ML Demystified / @carologic / MWUX2017 Strategic Games • 1997 Chess, IBM • 2016 Go, Google • Intelligence? • Perception? • Action/Decision? Floor goban, 2007, By Goban1 https://commons.wikimedia.org/wiki/File:FloorGoban.JPG
  • 26. AI and ML Demystified / @carologic / MWUX2017 Understanding human speech • Watson developed for quiz show Jeopardy! • Won against champions in 2011 for $1 million Video: “IBM's Watson Supercomputer Destroys Humans in Jeopardy! Engadget” https://www.youtube.com/watch?v=WFR3lOm_xhE Watson definition: https://en.wikipedia.org/wiki/Watson_(computer)
  • 27. AI and ML Demystified / @carologic / MWUX2017 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
  • 28. AI and ML Demystified / @carologic / MWUX2017 Image Recognition – Google Photos Carol’s search for “cats” on her Google Photos account.
  • 29. AI and ML Demystified / @carologic / MWUX2017 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
  • 30. AI and ML Demystified / @carologic / MWUX2017 Analyzing Text: Personality of @carologic (not quite) Personality Insights applied to @Carologic on Twitter IBM Watson Developer Cloud: https://personality-insights-livedemo.mybluemix.net/
  • 31. AI and ML Demystified / @carologic / MWUX2017 Automating Repetitive Work • Automated Radiologist highlights possible issues • Radiologist confirms IBM’s Automated Radiologist Can Read Images and Medical Records, MIT Technology Review https://www.technologyreview.com/s/600706/ibms-automated-radiologist-can-read-images-and-medical-records/
  • 32. AI and ML Demystified / @carologic / MWUX2017 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 Seeing is preventing. https://twitter.com/IBMWatson/status/844545761740292096
  • 33. AI and ML Demystified / @carologic / MWUX2017 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
  • 34. AI and ML Demystified / @carologic / MWUX2017 Chatbots – not really AI, yet • Mapping Q & A –Expected language –Appropriate automated responses –When to escalate to a human Images: 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
  • 35. AI and ML Demystified / @carologic / MWUX2017 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
  • 36. AI and ML Demystified / @carologic / MWUX2017 Ethics in Design for AI
  • 37. 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
  • 38. AI and ML Demystified / @carologic / MWUX2017 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? Inspired by Grady Booch, Scientist, philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
  • 39. Trust machines just as much as a well-trained human?
  • 40. AI and ML Demystified / @carologic / MWUX2017 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/
  • 41. AI and ML Demystified / @carologic / MWUX2017 Transparency • How was AI taught? • 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/
  • 42. AI and ML Demystified / @carologic / MWUX2017 Skills • Built with people in the industry • Human workers trained how to use 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/
  • 43. AI and ML Demystified / @carologic / MWUX2017 Regulations • Almost everyone agrees they are necessary • Who will create regulations? • Enforce?
  • 44. “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
  • 45. AI and ML Demystified / @carologic / MWUX2017 The EU General Data Protection Regulation (GDPR) • Framework for transparency rights and safeguards against automated decision-making • Right to contest a completely automated decision if it has legal or other significant effects on them 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
  • 46. AI and ML Demystified / @carologic / MWUX2017 Regulations take forever • Humans and algorithms aren’t without bias • ML has potential to make less biased decisions • Algorithms trained with biased data pick up and replicate biases, and develop new ones 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
  • 47. AI and ML Demystified / @carologic / MWUX2017 How do we evolve the practice of UX to deal with the new issues these technologies bring and the new information that is created?
  • 48. AI and ML Demystified / @carologic / MWUX2017 Take Responsibility • Create a code of conduct – What do you value? – What lines won’t your AI cross? • Make your AI transparent – How was it made and what does it do? – How do you reduce bias? • Keep humans in control
  • 49. AI and ML Demystified / @carologic / MWUX2017 Don’t fear AI - Explore AI Try the tools Pair with others IBM Watson Developer Tools (free trials): https://console.ng.bluemix.net/catalog/?category=watson
  • 50. AI and ML Demystified / @carologic / MWUX2017 Go forth and create ethical AI’s • Purpose: Intelligence and actions to maximize success • Transparency: Code of Conduct • Skills: How will humans learn to use it?
  • 51. AI and ML Demystified / @carologic / MWUX2017 Contact Carol LinkedIn: https://www.linkedin.com/in/caroljsmith Twitter - @Carologic: https://twitter.com/carologic Slides on Slideshare: https://www.slideshare.net/carologic
  • 52. AI and ML Demystified / @carologic / MWUX2017 Additional Information and Resources
  • 53. AI and ML Demystified / @carologic / MWUX2017 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/
  • 54. AI and ML Demystified / @carologic / MWUX2017 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
  • 55. AI and ML Demystified / @carologic / MWUX2017 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
  • 56. AI and ML Demystified / @carologic / MWUX2017 Tone Analyzer - Watson IBM Watson Developer Cloud, Tone Analyzer https://tone-analyzer-demo.mybluemix.net/
  • 57. AI and ML Demystified / @carologic / MWUX2017 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/
  • 58. AI and ML Demystified / @carologic / MWUX2017 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
  • 59. AI and ML Demystified / @carologic / MWUX2017 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
  • 60. AI and ML Demystified / @carologic / MWUX2017 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/
  • 61. AI and ML Demystified / @carologic / MWUX2017 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
  • 62. AI and ML Demystified / @carologic / MWUX2017 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
  • 63. AI and ML Demystified / @carologic / MWUX2017 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
  • 64. AI and ML Demystified / @carologic / MWUX2017 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
  • 65. AI and ML Demystified / @carologic / MWUX2017 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

Hinweis der Redaktion

  1. Exhibit intelligence Perceive their environment Take actions to maximize chance of success at a goal
  2. Metropolis (1927), 2001 Space Odyssey (1968), War Games (1983), Blade Runner (1982), The Terminator (1984), Short Circuit (1986), The Matrix (1999), Ex Machina (2015), More recently, The Terminator, Short Circuit, 2001 Space Odyssey, The Matrix, Metropolis, Westworld
  3. Take set of knowledge we give them and apply to new data Help humans discover patterns and find unknown
  4. Provide body of knowledge for ground-truth curated representative used to compare further knowledge
  5. Teaching Don’t learn like a typical human Only what they need to know
  6. Consider a reverse card sorting exercise 30 participants How important is it that they all get it right every time? Consider your industry
  7. Government safety compliance Accidents related to this tire? Financial compliance Accounts with connections to this organization? Ecommerce chat bot Women’s pants with pockets?
  8. 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.
  9. Late stage of disease at diagnosis and lack of treatment
  10. 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
  11. 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
  12. Developed initially to answer Jeopardy! questions IBM's Watson named after IBM's first CEO, industrialist Thomas J. Watson.
  13. “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.
  14. 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.
  15. 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.
  16. 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
  17. teach to discern between right and wrong? letter vs. spirit of law?
  18. The EU is more inclined to create hard laws that are enforceable. The EU General Data Protection Regulation, or GDPR, which will come into force in May 2018, is an excellent example. This framework creates certain transparency rights and safeguards against automated decision-making.  Article 22, for example, grants individuals the right to contest a completely automated decision if it has legal or other significant effects on them.  Other articles require data collectors such as advertisers to provide people with access to the collectors’ data on them, and to inform people about the general functionality of the automated system when decisions are made using that data.
  19. 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