This document discusses the rise of machine learning and how it has evolved from early attempts at programming computers to think intelligently to the current approach of using large datasets and neural networks. It notes that while artificial intelligence may replace some human jobs, design will still require emotional intelligence. The document also raises challenges for experience designers to design for openness across physical and digital experiences, learn the new possibilities of machine learning, and consider heuristics and ethics.

1. #Machine learning
Peter J. Bogaards
Trending topic for experience design(ers)
iTED #3 - 23 januari 2015

2. Now watch this… https://www.youtube.com/watch?v=OXA4-5x31V0

4. “No artificial intelligence will ever replace a human designer,
because design is largely about emotional intelligence.”

5. The old way
Artificial intelligence
Thinking machines
Intelligent systems
Understanding knowledge
Expert systems
Marvin Minsky

6. Heuristically programmed ALgorithmic computer
2001: A Space Odyssey
Stanley Kubrick (1968)

7. The new way
Machine intelligence
Natural language processing
Image recognition
Deep learning (neural networks)
Feedback, learning and growing
Geoffrey Hinton

8. Her
Spike Jonze (2013)

9. “(…) deep learning is when machine intelligence hits big data.”

12. A different paradigm
“Instead of trying to program computers to act intelligently - an approach
that hadn’t worked because we don’t really know what intelligence is -
Artificial Intelligence now embraced a statistical, brute force approach
based on analyzing vast amounts of information with powerful
computers and sophisticated algorithms.”
(Irving Wladawsky-Berger, Wall Street Journal)

23. “Who needs websites when you have Siri?”

24. Challenges for experience design
Design for openness (physical and digital)
Give up control
Learn the new possibilities
Create personal, meaningful experiences across multiple ‘everything’
Think heuristics and ethics

26. Naveen Rao (CEO Nervana Systems)
“Deep Learning: Intelligence from Big Data” Stanford Graduate School of Business (Sep 2014)
https://www.youtube.com/watch?v=czLI3oLDe8M#t=1h15m36s

27. Thank you
peter.bogaards@informaat.com
@BogieZero