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18 September, 2019
BUILDING TRUST AND ACCOUNTABILITY:
THE ROLE USER EXPERIENCE DESIGN CAN
PLAY IN ARTIFICIAL INTELLIGENCE
Speakers:
• Simon Fortenbacher, Director of User Experience and Design, GSK
• Gergely Szabo, Senior UX/UI Designer, Elsevier
• Kirk Brote, Kirk Brote Consulting
Moderator: Paula de Matos, Project Manager and UX Consultant, UXLS
This webinar is being recorded
Announcements
©PistoiaAlliance
UXLS 2020 Conference
4
Location: Boston, USA
Dates: Spring 2020 (TBC)
Wish to be on the mailing list
email:
paula.dematos@pistoiaalliance.org
https://www.pistoiaalliance.org/news/inspirational-2019-ux-conference-for-the-life-sciences/
©PistoiaAlliance
Coming up: 22.10.2019 Boston Pistoia Alliance FAIR
Implementation and AI/ML Workshop
5
• Morning workshops:
o FAIR Implementation
o AI Best Practices Project Team
o Assay FAIR Data Annotation Project Team
• Plenary talk by Dr. John Overington, CIO, Medicines Discovery Catapult,
UK
• Panel discussion with Dr. Overington; Lihua Yu, PhD, President, H3
Biomedicine Inc; and Al Wang, Head, IT Business Partner, Translational,
Bristol-Myers Squibb
• Evening reception, posters, launch of datathon #2
Register today! : https://www.eventbrite.co.uk/e/pistoia-alliance-fair-implementation-and-
aiml-workshop-tickets-62986729002
©PistoiaAlliance
Learn how
leading industry
experts are
today achieving
practical
benefits from
data integration
and predictive
analytics.
• Learn how techniques and data are
being used to deliver results and
return on investment
• Gain a broad understanding of
how machine learning and
semantic data integration fit
together in the context of drug
discovery
• Put the buzzwords into context
and understand their true meaning
and relevance to your work
https://contechlive.com/product/contech-pharma-delegate-tickets/
• Special offer for Pistoia Alliance members – enter code PISTOIA for
an exclusive discount on delegate tickets.
Speakers
©PistoiaAlliance
Introduction to the speakers
818 September, 2019
Simon Fortenbacher
Director of User Experience
and Design, GSK
• Leads a team of UX
Designers
• One of the project
founders of UXLS
Gergely Szabo
Senior UX Designer, Entellect
• Responsible for the​ ​UX
Research, User Experience
and UI of a series of
Life Science-related ML-
projects at Entellect.
• Formerly of Springer Nature
Kirk Brote
Director of Kirk Brote
Consulting
• UX consulting and design in
genomics, AI, healthcare,
life science, banking &
payments, and retail.
• Formerly of WuxiNextCode
©PistoiaAlliance
Poll Question 1
918 September, 2019
Do you apply UX in the application of AI?
1. Yes
2. Partly
3. No
©PistoiaAlliance
18 September, 2019
UXLS Introduction
AI/UX Webinar
Simon Fortenbacher
Director of UX & Design, R&D Tech, GSK
Image credit: Robert Slowley Photography
©PistoiaAlliance
What is UX Design?
The Customer The User
©PistoiaAlliance
What is UX Design?
1218 September, 2019
• User Experience (UX) is about focusing on the core needs,
goals and expectations of the end users of any product
• UX Design is the process of ensuring a product is specified,
designed, built and tested with end users in mind
• UX Design is not the same as UI Design
– UX Design covers the whole product specification and creation
process, including ensuring the right problems are being solved, and
the users’ needs are being accurately researched, captured and
evaluated
– A UI design might be a potential output from a UX Design activity
• Usability is a measure of the efficiency, effectiveness and
satisfaction of any product
©PistoiaAlliance
What is UX Design?
1318 September, 2019
• The UX Design process covers user research, specification
and design, and testing
• It best starts early with recognising a problem to be solved
Adopted from Stanford d.school model
Empathise Ideate
Define Prototype
Test
©PistoiaAlliance
What is UX Design?
1418 September, 2019
• UX Design emphasises the need for iterative usability testing
as way to verify the effectiveness of any product during
development
©PistoiaAlliance
What is UX Design?
1518 September, 2019
• User Research helps understand what users actually need,
not what they say they need…
“Your local
B&Q closes
at five o’clock”
3:49pm
“OK Google. What time does my local B&Q* close today?”
“Your local B&Q closes
in one hour. With current
traffic conditions you
should be able to get
there thirty minutes
before closing time.”
3:49pm
* Or a home improvement store of your choice
©PistoiaAlliance
What is the User Experience
for Life Science Community?
Project members include
Steering committee
A project team of UX folk in the life science R&D sector
©PistoiaAlliance
What do we do?
17
We build stuff ▼
We highlight
UX value ►
We run conferences ▼
We
talk ►
We compare ourselves ▼
©PistoiaAlliance
The UXLS Toolkit
18
uxls.org
info@pistoiaalliance.org @pistoiaalliance www.pistoiaalliance.org
Thank you
©PistoiaAlliance
Poll Question 2
To what extent does a good user experience improve your trust
in the results of an AI?
• A lot
• Somewhat
• Not very much
• Not at all
©PistoiaAlliance
18 September, 2019
UX and AI
AI/UX Webinar
Gergely Szabo
Lead UX, Entellect (Elsevier’s Life Science ML platform)
Image credit: Robert Slowley Photography
©PistoiaAlliance
2218 September, 2019
Who we are? Entellect is a new cloud-based data platform designed to
help life sciences companies overcome the challenges of
modern R&D by enriching and harmonizing proprietary and
external data and delivering it in an AI-ready environment.
©PistoiaAlliance
2318 September, 2019
What we do?
©PistoiaAlliance
How do you help IA/ML workflows as a UX person?
2418 September, 2019
Special scenarios
• Dashboard / analytics experience
• Complicated search / API capabilities
• Text editor as main user interface
• Big Data, Slow UX
• CTA: a PDF, a report or data set
• Onboarding: check your hardware requirements
©PistoiaAlliance
How do you help IA/ML workflows as a UX person?
2518 September, 2019
Special scenarios
• Dashboard / analytics experience
• Complicated search / API capabilities
• Text editor as main user interface
• Big Data, Slow UX
• CTA: a PDF, a report or data set
• Onboarding: check your hardware requirements
©PistoiaAlliance
Some useful UX research methods
2618 September, 2019
Qualitative research comes first
• User interviews (ethnographic studies)
• Card sorting exercises
• Building personas / identifying user roles
• User testing
• Experience maps (a-ha’s and pain points)
• Reporting
©PistoiaAlliance
Some useful UX research methods
2718 September, 2019
Qualitative research comes first
• User interviews (ethnographic studies)
• Card sorting exercises
• Building personas / identifying user roles
• User testing
• Experience maps (a-ha’s and pain points)
• Reporting
©PistoiaAlliance
Understanding our users
2818 September, 2019
• 1on 1 card-sorting with a
dozen people
• Every level of experience
and knowledge
• Talking through our roles
too
• Rating persona skills
• Introducing a… UX ontology
:)
©PistoiaAlliance
Share and collaborate
2918 September, 2019
• Document and share
• Update main maps
• Use it as a reference
• Link user roles to user
stories
©PistoiaAlliance
Typical deliverables
3018 September, 2019
• Research and user test reports
• User role / persona maps
• Review of user journeys / workflows
• Onboarding documents and
playbooks
• And some dashboard UI…
info@pistoiaalliance.org @pistoiaalliance www.pistoiaalliance.org
Thank you
©PistoiaAlliance
Poll Question 3
3218 September, 2019
What do you believe are the biggest factors in engendering trust
in an AI application in R&D?
1. Verified sources of data ‘feeding’ an AI process
2. Better education on how AI works overall
3. Access to the AI model build and validation processes
4. Being able to review the steps & sources the AI process has
taken to reach a result
5. How the AI application presents its results
Building trust and accountability: the role User
Experience design can play in Artificial Intelligence
Kirk Brote, Kirk Brote Consulting
©PistoiaAlliance
The Role of Trust and Accountability
The bottom line is that user’s won’t adopt what they don’t trust.
This is the single greatest challenge designing AI in any vertical
but especially in life sciences.
Consumers have not had great experiences with commercially
available AI experiences that colors their expectations on the
maturity of the tools.
• Siri, Alexa, and Google Assistant all have major, widely known
failure points.
• No digital assistant today does a good job anticipating
concerns like a real assistant would.
©PistoiaAlliance
Impact of Bias on AI Experiences
As designers and developers of AI systems, we are the lens
between data and experience, addressing fairness,
accountability, and long-term effects on society when designing
with data.
• All systems made by humans are intrinsically tied to human
bias
– Google photos racially bias tagging system
– Microsoft Tay’s offensive behavior on Twitter
– Tesla autopilot fatal accidents
©PistoiaAlliance
Unintended Consequences in AI
• Designers need to spend an inordinate amount of time
focusing on the potential for unintended consequences
• That is needed not only to avoid another PR nightmare for
large corporations; it is about designing AI that reflects and
evolves with our vision for a more ethical society
©PistoiaAlliance
Training Pitfalls in AI
• AI, ML, and many other related technologies need to be
trained in order to be effective and training requires data
• Most commonly the most widely available data is used for
training because of the volume required.
• Medical Data for training is best characterized how?
– Overwhelmingly ‘WHITE’ , with other races under represented
– Still overwhelmingly ‘MALE’
©PistoiaAlliance
Ethics and Consequences
In genomics AI and ML is informing us about actual as well as
potential health problems. Do the same decision frameworks still
hold in this model?
So what do we show users?
• Is there anything that can be done about the result?
• What certainty is there about the potential harm being
realized?
• What benefit is there to the patient in knowing the risk or
prediction?
©PistoiaAlliance
Ethics and Consequences
Individual decisions can have profound impact at scale. Using AI
to power decision making opportunities impacts the decision
making process itself. As scientists become more and more
comfortable trusting AI, we have to remain vigilant in
understanding how AI based decisions are being made to ensure
their validity.
Question and Answer Session
info@pistoiaalliance.org @pistoiaalliance www.pistoiaalliance.org
Thank you for attending

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Building trust and accountability - the role User Experience design can play in Artificial Intelligence

  • 1. 18 September, 2019 BUILDING TRUST AND ACCOUNTABILITY: THE ROLE USER EXPERIENCE DESIGN CAN PLAY IN ARTIFICIAL INTELLIGENCE Speakers: • Simon Fortenbacher, Director of User Experience and Design, GSK • Gergely Szabo, Senior UX/UI Designer, Elsevier • Kirk Brote, Kirk Brote Consulting Moderator: Paula de Matos, Project Manager and UX Consultant, UXLS
  • 2. This webinar is being recorded
  • 4. ©PistoiaAlliance UXLS 2020 Conference 4 Location: Boston, USA Dates: Spring 2020 (TBC) Wish to be on the mailing list email: paula.dematos@pistoiaalliance.org https://www.pistoiaalliance.org/news/inspirational-2019-ux-conference-for-the-life-sciences/
  • 5. ©PistoiaAlliance Coming up: 22.10.2019 Boston Pistoia Alliance FAIR Implementation and AI/ML Workshop 5 • Morning workshops: o FAIR Implementation o AI Best Practices Project Team o Assay FAIR Data Annotation Project Team • Plenary talk by Dr. John Overington, CIO, Medicines Discovery Catapult, UK • Panel discussion with Dr. Overington; Lihua Yu, PhD, President, H3 Biomedicine Inc; and Al Wang, Head, IT Business Partner, Translational, Bristol-Myers Squibb • Evening reception, posters, launch of datathon #2 Register today! : https://www.eventbrite.co.uk/e/pistoia-alliance-fair-implementation-and- aiml-workshop-tickets-62986729002
  • 6. ©PistoiaAlliance Learn how leading industry experts are today achieving practical benefits from data integration and predictive analytics. • Learn how techniques and data are being used to deliver results and return on investment • Gain a broad understanding of how machine learning and semantic data integration fit together in the context of drug discovery • Put the buzzwords into context and understand their true meaning and relevance to your work https://contechlive.com/product/contech-pharma-delegate-tickets/ • Special offer for Pistoia Alliance members – enter code PISTOIA for an exclusive discount on delegate tickets.
  • 8. ©PistoiaAlliance Introduction to the speakers 818 September, 2019 Simon Fortenbacher Director of User Experience and Design, GSK • Leads a team of UX Designers • One of the project founders of UXLS Gergely Szabo Senior UX Designer, Entellect • Responsible for the​ ​UX Research, User Experience and UI of a series of Life Science-related ML- projects at Entellect. • Formerly of Springer Nature Kirk Brote Director of Kirk Brote Consulting • UX consulting and design in genomics, AI, healthcare, life science, banking & payments, and retail. • Formerly of WuxiNextCode
  • 9. ©PistoiaAlliance Poll Question 1 918 September, 2019 Do you apply UX in the application of AI? 1. Yes 2. Partly 3. No
  • 10. ©PistoiaAlliance 18 September, 2019 UXLS Introduction AI/UX Webinar Simon Fortenbacher Director of UX & Design, R&D Tech, GSK Image credit: Robert Slowley Photography
  • 11. ©PistoiaAlliance What is UX Design? The Customer The User
  • 12. ©PistoiaAlliance What is UX Design? 1218 September, 2019 • User Experience (UX) is about focusing on the core needs, goals and expectations of the end users of any product • UX Design is the process of ensuring a product is specified, designed, built and tested with end users in mind • UX Design is not the same as UI Design – UX Design covers the whole product specification and creation process, including ensuring the right problems are being solved, and the users’ needs are being accurately researched, captured and evaluated – A UI design might be a potential output from a UX Design activity • Usability is a measure of the efficiency, effectiveness and satisfaction of any product
  • 13. ©PistoiaAlliance What is UX Design? 1318 September, 2019 • The UX Design process covers user research, specification and design, and testing • It best starts early with recognising a problem to be solved Adopted from Stanford d.school model Empathise Ideate Define Prototype Test
  • 14. ©PistoiaAlliance What is UX Design? 1418 September, 2019 • UX Design emphasises the need for iterative usability testing as way to verify the effectiveness of any product during development
  • 15. ©PistoiaAlliance What is UX Design? 1518 September, 2019 • User Research helps understand what users actually need, not what they say they need… “Your local B&Q closes at five o’clock” 3:49pm “OK Google. What time does my local B&Q* close today?” “Your local B&Q closes in one hour. With current traffic conditions you should be able to get there thirty minutes before closing time.” 3:49pm * Or a home improvement store of your choice
  • 16. ©PistoiaAlliance What is the User Experience for Life Science Community? Project members include Steering committee A project team of UX folk in the life science R&D sector
  • 17. ©PistoiaAlliance What do we do? 17 We build stuff ▼ We highlight UX value ► We run conferences ▼ We talk ► We compare ourselves ▼
  • 20. ©PistoiaAlliance Poll Question 2 To what extent does a good user experience improve your trust in the results of an AI? • A lot • Somewhat • Not very much • Not at all
  • 21. ©PistoiaAlliance 18 September, 2019 UX and AI AI/UX Webinar Gergely Szabo Lead UX, Entellect (Elsevier’s Life Science ML platform) Image credit: Robert Slowley Photography
  • 22. ©PistoiaAlliance 2218 September, 2019 Who we are? Entellect is a new cloud-based data platform designed to help life sciences companies overcome the challenges of modern R&D by enriching and harmonizing proprietary and external data and delivering it in an AI-ready environment.
  • 24. ©PistoiaAlliance How do you help IA/ML workflows as a UX person? 2418 September, 2019 Special scenarios • Dashboard / analytics experience • Complicated search / API capabilities • Text editor as main user interface • Big Data, Slow UX • CTA: a PDF, a report or data set • Onboarding: check your hardware requirements
  • 25. ©PistoiaAlliance How do you help IA/ML workflows as a UX person? 2518 September, 2019 Special scenarios • Dashboard / analytics experience • Complicated search / API capabilities • Text editor as main user interface • Big Data, Slow UX • CTA: a PDF, a report or data set • Onboarding: check your hardware requirements
  • 26. ©PistoiaAlliance Some useful UX research methods 2618 September, 2019 Qualitative research comes first • User interviews (ethnographic studies) • Card sorting exercises • Building personas / identifying user roles • User testing • Experience maps (a-ha’s and pain points) • Reporting
  • 27. ©PistoiaAlliance Some useful UX research methods 2718 September, 2019 Qualitative research comes first • User interviews (ethnographic studies) • Card sorting exercises • Building personas / identifying user roles • User testing • Experience maps (a-ha’s and pain points) • Reporting
  • 28. ©PistoiaAlliance Understanding our users 2818 September, 2019 • 1on 1 card-sorting with a dozen people • Every level of experience and knowledge • Talking through our roles too • Rating persona skills • Introducing a… UX ontology :)
  • 29. ©PistoiaAlliance Share and collaborate 2918 September, 2019 • Document and share • Update main maps • Use it as a reference • Link user roles to user stories
  • 30. ©PistoiaAlliance Typical deliverables 3018 September, 2019 • Research and user test reports • User role / persona maps • Review of user journeys / workflows • Onboarding documents and playbooks • And some dashboard UI…
  • 32. ©PistoiaAlliance Poll Question 3 3218 September, 2019 What do you believe are the biggest factors in engendering trust in an AI application in R&D? 1. Verified sources of data ‘feeding’ an AI process 2. Better education on how AI works overall 3. Access to the AI model build and validation processes 4. Being able to review the steps & sources the AI process has taken to reach a result 5. How the AI application presents its results
  • 33. Building trust and accountability: the role User Experience design can play in Artificial Intelligence Kirk Brote, Kirk Brote Consulting
  • 34. ©PistoiaAlliance The Role of Trust and Accountability The bottom line is that user’s won’t adopt what they don’t trust. This is the single greatest challenge designing AI in any vertical but especially in life sciences. Consumers have not had great experiences with commercially available AI experiences that colors their expectations on the maturity of the tools. • Siri, Alexa, and Google Assistant all have major, widely known failure points. • No digital assistant today does a good job anticipating concerns like a real assistant would.
  • 35. ©PistoiaAlliance Impact of Bias on AI Experiences As designers and developers of AI systems, we are the lens between data and experience, addressing fairness, accountability, and long-term effects on society when designing with data. • All systems made by humans are intrinsically tied to human bias – Google photos racially bias tagging system – Microsoft Tay’s offensive behavior on Twitter – Tesla autopilot fatal accidents
  • 36. ©PistoiaAlliance Unintended Consequences in AI • Designers need to spend an inordinate amount of time focusing on the potential for unintended consequences • That is needed not only to avoid another PR nightmare for large corporations; it is about designing AI that reflects and evolves with our vision for a more ethical society
  • 37. ©PistoiaAlliance Training Pitfalls in AI • AI, ML, and many other related technologies need to be trained in order to be effective and training requires data • Most commonly the most widely available data is used for training because of the volume required. • Medical Data for training is best characterized how? – Overwhelmingly ‘WHITE’ , with other races under represented – Still overwhelmingly ‘MALE’
  • 38. ©PistoiaAlliance Ethics and Consequences In genomics AI and ML is informing us about actual as well as potential health problems. Do the same decision frameworks still hold in this model? So what do we show users? • Is there anything that can be done about the result? • What certainty is there about the potential harm being realized? • What benefit is there to the patient in knowing the risk or prediction?
  • 39. ©PistoiaAlliance Ethics and Consequences Individual decisions can have profound impact at scale. Using AI to power decision making opportunities impacts the decision making process itself. As scientists become more and more comfortable trusting AI, we have to remain vigilant in understanding how AI based decisions are being made to ensure their validity.