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H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
2 / 2
© Lawrence Lek
„H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
MACHINE LEARNING WON’T REACH ITS POTENTIAL
– AND MAY ACTUALLY CAUSE HARM –
IF IT DOESN’T DEVELOP
IN TANDEM WITH USER EXPERIENCE DESIGN.
Caroline Sinders, Fast Company
What are the challenges for UX?
© Lawrence Lek
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Develop relevant use cases
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Spotify - Discovery Weekly
Discovery Weekly is an automated music
recommendation digest for each Spotify user every
monday. It uses a feedback loop mechanism to
personalize, optimize or automate the existing
service.
Spotify - Discovery Weekly
© Fabien Girardin
Spotify - Discovery Weekly
© Fabien Girardin
„H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S SMACHINE LEARNING WILL CHANGE CUSTOMER
PERSONAS FOREVER
Andre Smith, Digitalist Magazine / SAP
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Re-think customer personas
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Re-think customer personas
Thanks to machine learning, computers will soon know your
customers better than your customers know themselves.
• They’re much better at „guesswork“ than humans are
• More efficient targeting of new customers
• More cost-effective
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Create intuitive AI interfaces
„H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
THE FUTURE OF MACHINE LEARNING
IS COMING UP WITH A HYBRID LANGUAGE THAT
BRIDGES DESIGN AND ENGINEERING.
Caroline Sinders, Fast Company
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Make tons of data manageable
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Make tons of data manageable
Big data techniques and analytics changed the way that
businesses conduct their everyday operations. The sheer
volume of data is where Deep Learning algorithms come in to
deliver superior insights.
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Use data to be super-relevant or be silent
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Let users tell about poor information
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Let users tell about poor information
For example in banking, one could consider the temporal evolution of
account balances to segment savings behaviors. This type of
algorithms that leads to decision-making needs to learn to be more
precise.
It’s the designer’s job to find ways to let users tell implicitly or
explicitly about poor information.
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Design for discovery
• Filter Bubble - Tweak algorithms to
be less accurate
• Profile Detox - Let an open door to
reshape profiles
• Human Computation - Enlist humans
to give more diversity
© Fabien Girardin
„H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S SMOBILE PHONES HAVE BECOME
SLOT MACHINES!
Tristan Harris, a former Google product manager
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Design for engagement responsibly
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Design for engagement responsibly
Today, algorithms typically score the relevance of social and news
content. Major online services are fighting to hook people, grab their
attention for as long as possible. Their business is to keep users
active as long and frequently as possible on their platforms. They use
techniques that promote addiction = hooking people endlessly
searching for the next reward.
That new power raises the need for new design principles in the age
of machine learning.
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Empathy is not (yet) available
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Empathy is not (yet) available
The ethical and practical considerations of machine learning
have to be shaped by how products using machine learning
affect users and how users can understand and see those
effects.
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Questions are the new answers
© Jan Korsanke
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Questions are the new answers
In future computers won’t deliver answers before asking
you back (a string of) questions. But what are rules and
etiquette for machines?
© Jan Korsanke
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Illustrate for transparency
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Illustrate for transparency
When users don’t understand how an algorithm gets its results,
it can be difficult to trust the system. Transparency
communicates trust.
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Seamful design
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Seamful design
Designers must know that a „Prediction Feature“ is not the
same as informing, and consider how well such a prediction
could support a user action.
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Machine bias: AI can lead to discrimination
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Challenges for UX
Machine bias: AI can lead to discrimination
Most of the current facial recognition techniques use the same
data set, which was trained on mainly white people. It would
not recognise people with other skintones.
„H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
ULTIMATELY,
DESIGNERS MUST ACT AS A BULWARK
AGAINST IRRESPONSIBLE,
UNETHICAL USE OF AI.
Katharine Schwab, Fast Company
H O W D E E P L E A R N I N G
C H A N G E S T H E
D E S I G N P R O C E S S
Principles for designing AI responsibly
• AI must be designed to assist humanity
• AI must be transparent
• AI must maximize efficiencies without destroying the dignity of people
• AI must be designed for intelligent privacy
• AI must have algorithmic accountability
• AI must guard against bias
Satya Nadella, Microsoft CEO
Alexander Meinhardt
krunchtime.org
KRUNCHTI M E I NTE RACTIVE

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2017 How Deep Learning Changes the Design Process (2)

  • 1. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S 2 / 2 © Lawrence Lek
  • 2. „H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S MACHINE LEARNING WON’T REACH ITS POTENTIAL – AND MAY ACTUALLY CAUSE HARM – IF IT DOESN’T DEVELOP IN TANDEM WITH USER EXPERIENCE DESIGN. Caroline Sinders, Fast Company
  • 3. What are the challenges for UX? © Lawrence Lek
  • 4. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Develop relevant use cases
  • 5. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Spotify - Discovery Weekly Discovery Weekly is an automated music recommendation digest for each Spotify user every monday. It uses a feedback loop mechanism to personalize, optimize or automate the existing service.
  • 6. Spotify - Discovery Weekly © Fabien Girardin
  • 7. Spotify - Discovery Weekly © Fabien Girardin
  • 8. „H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S SMACHINE LEARNING WILL CHANGE CUSTOMER PERSONAS FOREVER Andre Smith, Digitalist Magazine / SAP
  • 9. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Re-think customer personas
  • 10. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Re-think customer personas Thanks to machine learning, computers will soon know your customers better than your customers know themselves. • They’re much better at „guesswork“ than humans are • More efficient targeting of new customers • More cost-effective
  • 11. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Create intuitive AI interfaces
  • 12. „H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S THE FUTURE OF MACHINE LEARNING IS COMING UP WITH A HYBRID LANGUAGE THAT BRIDGES DESIGN AND ENGINEERING. Caroline Sinders, Fast Company
  • 13. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Make tons of data manageable
  • 14. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Make tons of data manageable Big data techniques and analytics changed the way that businesses conduct their everyday operations. The sheer volume of data is where Deep Learning algorithms come in to deliver superior insights.
  • 15. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Use data to be super-relevant or be silent
  • 16. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Let users tell about poor information
  • 17. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Let users tell about poor information For example in banking, one could consider the temporal evolution of account balances to segment savings behaviors. This type of algorithms that leads to decision-making needs to learn to be more precise. It’s the designer’s job to find ways to let users tell implicitly or explicitly about poor information.
  • 18. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Design for discovery • Filter Bubble - Tweak algorithms to be less accurate • Profile Detox - Let an open door to reshape profiles • Human Computation - Enlist humans to give more diversity © Fabien Girardin
  • 19. „H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S SMOBILE PHONES HAVE BECOME SLOT MACHINES! Tristan Harris, a former Google product manager
  • 20. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Design for engagement responsibly
  • 21. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Design for engagement responsibly Today, algorithms typically score the relevance of social and news content. Major online services are fighting to hook people, grab their attention for as long as possible. Their business is to keep users active as long and frequently as possible on their platforms. They use techniques that promote addiction = hooking people endlessly searching for the next reward. That new power raises the need for new design principles in the age of machine learning.
  • 22. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Empathy is not (yet) available
  • 23. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Empathy is not (yet) available The ethical and practical considerations of machine learning have to be shaped by how products using machine learning affect users and how users can understand and see those effects.
  • 24. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Questions are the new answers © Jan Korsanke
  • 25. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Questions are the new answers In future computers won’t deliver answers before asking you back (a string of) questions. But what are rules and etiquette for machines? © Jan Korsanke
  • 26. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Illustrate for transparency
  • 27. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Illustrate for transparency When users don’t understand how an algorithm gets its results, it can be difficult to trust the system. Transparency communicates trust.
  • 28. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Seamful design
  • 29. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Seamful design Designers must know that a „Prediction Feature“ is not the same as informing, and consider how well such a prediction could support a user action.
  • 30. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Machine bias: AI can lead to discrimination
  • 31. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Challenges for UX Machine bias: AI can lead to discrimination Most of the current facial recognition techniques use the same data set, which was trained on mainly white people. It would not recognise people with other skintones.
  • 32. „H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S ULTIMATELY, DESIGNERS MUST ACT AS A BULWARK AGAINST IRRESPONSIBLE, UNETHICAL USE OF AI. Katharine Schwab, Fast Company
  • 33. H O W D E E P L E A R N I N G C H A N G E S T H E D E S I G N P R O C E S S Principles for designing AI responsibly • AI must be designed to assist humanity • AI must be transparent • AI must maximize efficiencies without destroying the dignity of people • AI must be designed for intelligent privacy • AI must have algorithmic accountability • AI must guard against bias Satya Nadella, Microsoft CEO