AI for IA’s: Machine Learning Demystified

I had the pleasure of presenting “AI for IA’s: Machine Learning Demystified” at the 2017 Information Architecture Summit last week in Vancouver, BC, Canada.

I provided the basics of artificial intelligence (AI) and how machine learning works as well as how it is relevant to information architecture (IA).

The presentation is on Slideshare.


When machines exhibit intelligence, perceive their environment and take actions to maximize their chance of success at a goal they have artificial intelligence (AI). AI is achieved through the process of training the machine on a specific subject. Training involves spending time transferring human concepts and relationships through documents that are representative of the knowledge we want the machine to know.

The presentation includes discussions on:

  • How training is conducted: the general work cycle and a comparison of training methods.

Examples of AI and Cognitive Computing

Strategic Games

  • 1997 Chess, IBM

Self Driving (autonomous) vehicles

Watson wins Jeopardy!

Automating labeling of birdsongs

Image Recognition — Google Photos

Automating Repetitive Work — Watson examples:

  • Radiology imaging

H&R Block

Staples Easy App


Watson Personality Insights

Watson Tone Analyzer

Ethics in AI

How might we(1)…

• build systems that have ethical and moral foundation?’

• that are transparent to users?

• teach mercy and justice of law?

• extend and advance healthcare?

• increase safety in dangerous work?

So that we trust machines just as much as a well-trained human?

AI will “extend human experience in profound ways” — Grady Booch, Scientist, philosopher, IBM’er

Explore the technology

Pair with folks to try AI out for yourself — IBM Watson Developer Tools (free trials on most tools)

1) Heavily referenced in this presentation is Grady Booch’s inspiring Ted Talk.

UX Leader, speaker and community organizer. My thoughts on user research, design, AI and more. Provoking human values in AI.

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