Despite widespread belief that AI will transform the way we do business, 82% of businesses are still in the investigation or non-adoptive stage of AI. This talk will explore the fundamental use cases in AI and how designers and engineers can be at the forefront of prioritizing AI/ML best practices. From user research to MVP iterations, we will explore the core differences between building an AI and non-AI product so that you can feel confident proposing or launching an AI project of your own. More details: https://confengine.com/agile-india-2019/proposal/8517/7-steps-to-design-build-and-scale-an-ai-product Conference link: https://2019.agileindia.org

1. 7 Steps to Design,
Build, and Scale
an AI Product
AGILE INDIA
March 21, 2019

2. Allie Miller
Amazon
IBM Watson
Wharton MBA
Dartmouth BA
@alliekmiller

3. Allie K. Miller | Agile India
Artificial Intelligence
Using a computer to perform human-level tasks.
Ex: visual recognition, speech recognition,
natural language understanding, pattern
recognition, and language translation.

4. Machine Learning
Computer sees millions of examples.
Computer makes model to map inputs to outputs.
Computer sees new input.
Computer provides output.
Allie K. Miller | Agile India

5. Now we know
what AI is.
How do you build it?

6. 7steps

7. 7 STEPS TO DESIGN,
BUILD, AND SCALE AI
Agile India | Allie K. Miller
Problem Scope Team Data
Test Optimize Scale

8. PROBLEM FIND PAINPOINT
The bigger the need,
the easier the sell.
OUTCOME
What is the result you
want?
MEET USERS
Speak to users, develop
personas, find goals.
Allie K. Miller | Agile India

9. SCOPE TIMELINE
Is there a date you
must hit? Why?
RESOURCES
What are your constraints?
BUDGET
Minimum MVP budget?
Add a buffer.
Allie K. Miller | Agile India

10. TEAM HIRE OR TEACH ML
1 MLE : 4 SWEs
DIVERSITY & BIAS
Age, gender, ethnicity,
etc. Robust QA.
MULTI-FUNCTION
Eng, design, product,
sales, mktg, legal, finance,
execs, and SMEs early.
Allie K. Miller | Agile India

11. DATA UNIQUE PIPELINE
What source? Is it
owned?
GOOD DATA
Sourcing and cleaning.
Mirror input. Who is
annotating and QA?
Focus on noise reduction.
MORE OF IT
Prepare for edge cases.
Allie K. Miller | Agile India

12. HALFWAY
DONE!
Allie K. Miller | Agile India

13. UX
BONUS!
IS IT AI?
Do users need to know it
is AI (Uber vs doctor)?
INTERFACE
Are users involved?
Common: thumbs up/down.
Less common?
TRANSPARENCY
Is more transparent
always better?
Allie K. Miller | Agile India

14. TEST PROVE SMALL
Research competitors,
align your team.
SUCCESS METRICS
AI and non-AI.
Accuracy and painpoints.
MEASURE & ADAPT
Don't aim for perfection.
Allie K. Miller | Agile India

15. OPTIMIZE FEEDBACK LOOP
Treat mistakes with care.
DATA LIFECYCLE
Data is value.
Constant stream.
Can it be automated?
DON'T SILO IT
Integrate AI within
business workflow.
Allie K. Miller | Agile India

16. SCALE EXPAND SMART
Bigger data set? More
cities? New features?
COMBINE TECH
IoT is popular!
CHECK IN
Every few months.
Still valuable? Can it be
improved? New products?
Allie K. Miller | Agile India

17. Problem: who are you helping and why?
Scope: what are the constraints?
Team: who is the best to get it done?
Data: where is the fuel?
Test: how can we prove this will work?
Optimize: can we make it better?
Scale: can the project grow?
1
2
3
4
5
6
7
Allie K. Miller | Agile India

18. Allie Miller
Thank you!
@alliekmiller