We are going to learn about How to use Artificial Intelligence for designing better digital product.

1. Human Centred AI
- Nilotpal Nayan

2. Who Am I ?
I am - UX Designer
I work - at WhatFix UX Designer + Founder MyCampusCart
Reachout to me for - Design Discussion/Talks/Mentorship/UX Courses
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3. Human Centred Ai
- What is AI
- Different Kinds of AI
- How to incorporate Ai for designing Human Centred Products
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4. What is Ai?
A machine entity that can Learn,
Adapt, and Self-correct.
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5. What is Ai?
A machine entity that can Learn,
Adapt, and Self-correct.
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6. What is Ai?
1. Learn
- Set of instructions
- A definite success criteria
- Training Set
2. Adapt
3. Self-correct
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7. What is Ai?
1. Learn
2. Adapt
- Use the existing data and
outcome to predict outcome of
future.
3. Self-correct
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8. What is Ai?
1. Learn
2. Adapt
3. Self-correct
- Use improvised instructions
and do more training.
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9. Kinds of AI
From a Bird’s-eye -view Ai can do two kind of Task -
1. Automation
2. Augmentation
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10. Kinds of AI - Examples
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Voice assistants
- Siri, Alexa, Google Home
Image recognition
- Google lens.
Ai Powered Robots
- Sophie.

11. Incorporating Ai for designing Human Centred Products
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1. Defining User Needs and Success Criteria
2. Data Collection
3. Mental Model
4. Explainability and Trust

12. Defining User Needs and Success Criteria

13. Defining User Needs and Success Criteria
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“Even the best AI will fail if it doesn’t provide unique value to users.

14. Defining User Needs and Success Criteria
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“Even the best AI will fail if it doesn’t provide unique value to users.
- A Enough Smart Guy

15. Defining User Needs and Success Criteria
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Identify if Ai can add unique value?

16. Defining User Needs and Success Criteria
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When AI is probably better-
1. Personalisation
2. Prediction of future events
3. Detection of low occurrence events that change
over time

17. Defining User Needs and Success Criteria
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When AI is probably not better at-
1. Handling Exceptional cases
2. Maintaining predictability
3. Complete transparency
4. High-value task which requires emotional decision
making

18. Defining User Needs and Success Criteria
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Can we use AI to ?
What Problems are suitable to
solve using AI

19. Defining user needs
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- Is there an user need and associated behaviour pattern ?
Ex. - Checking fastest route to office when you are late
- Setting alarm to catch morning flight
- Turning on silent mode before important meeting

20. Defining AI success and Reward function
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What is acceptable and true prediction for AI?
True Positive/True negative
- Increase Trust + Better User experience
False Positive/False Negative
- May/may not decrease trust + affect User Experience
Confusion Matrix

21. Defining AI success and Reward function
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What is acceptable and true prediction for AI?
Ex. - Google map prediction of Traffic jam.

22. What kind of AI ?
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- If AI is needed, which type is Best ?
Automated or Augmented

23. What kind of AI ?
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Automated if -
- People lack the knowledge or ability to do the task
- Tasks are boring, repetitive, awkward, or dangerous

24. What kind of AI ?
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Augment if -
- People enjoy the task
- Personal responsibility for the outcome is required or important
- Specific preferences are hard to communicate

25. Data Collection

26. Data Collection
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- Match user needs with data needs
- Manage privacy & security
- Protect personally identifiable information
- Balance underfitting & overfitting
- Consider bias in the data collection and evaluation process

27. Mental Model

28. Mental Model
- Set expectations for adaptation
- Design for experimentation
- Connect feedback with personalization
- Fail gracefully
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29. Mental Model
Set expectations for adaptation
- Expectation of improved experience based on User’s
interaction and feedback.
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30. Mental Model
Design for experimentation
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31. Mental Model
Connect feedback with personalization
- Implicit Feedback
- Explicit Feedback
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32. Mental Model
Fail gracefully
- Implicit Feedback
- Explicit Feedback
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33. Explainability and Trust

34. Explainability and Trust
Help users calibrate their trust (if required)
- Show AI’s level of confidence
- Explain the source of data used
- Account for situational stakes
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35. UX Courses
Meet the Ghost
- User Research Methods
- Next batch: Starts from 2nd October
- Only 7 students each batch
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Insight to Interfaces
- Ideation and Wireframing
- Next batch: Starts from 10th October
- Only 7 students each batch

36. Thanks a lot
Ask me anything