7 Steps to Design, Build, and Scale an AI Product by Allie Miller at #AgileIndia2019
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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
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7 Steps to Design, Build, and Scale an AI Product by Allie Miller at #AgileIndia2019
- 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