1. Rise of the Machines
AI in the agile world

2. Aidan Casey
senior manager - Johnson Controls Cork
@aidanjcasey
https://medium.com/@aidanjcasey

7. Alpha Zero
2017
Alpha Go
2016
Deep Blue
1997
Watson
2011

8. 1997 Deep Blue

9. source: mashable.com/2016/02/10/kasparov-deep-blue/

10. source: eliiza.com.au/what-is-ai/chess-game-tree/

11. 2011 Watson

12. source: blog.ted.com/how-did-supercomputer-watson-beat-jeopardy-champion-ken-jennings-experts-discuss/

13. Natural Language Processing (NLP)
+
Deep QA

14. source: watson4all.blogspot.com/2014/01/the-science-and-technology-behind-ibm
Deep QA

15. natural language processing

17. I walked down the street in a hat with a smile.

18. I walked down the street in a hat with a smile.

19. I walked down the street in a hat with a smile.
Parse Analyse Classify Contextualise

22. 2016 AlphaGo

24. source: Google DeepMind via YouTube

25. machine learning

26. supervised machine learning
Data
Acquisition
Clean and
Prepare Data
Apply & Test
Learning
Algorithms
Train Model Deploy Model
iterate to find
best model

27. source: becominghuman.ai/

28. neural networks

29. 2017 AlphaZero

30. Source : https://deepmind.com/blog/alphago-zero-learning-scratch/

31. supervised learning
machine learning
unsupervised learning
classification regression clustering association

32. Alpha Zero
2017
Alpha Go
2016
Deep Blue
1997
Watson
2011

33. Alpha Zero
2017
Alpha Go
2016
Deep Blue
1997
Watson
2011
custom algorithms
tree Search
natural language
processing
deep QA
supervised
machine learning
unsupervised
machine learning
monte carlo tree
search

34. AI in the Agile World

35. AI assisted SDLC
Natural User
Interface Design
Self Learning Software

36. AI powered expert tooling
NLP will provide
● enriched requirement models
● better code generation
● improved test automation
ML will provide
● more predictable timelines
● test coverage recommendations

37. Accenture’s
Virtual Scrum Master

39. https://www.agilealliance.org/resources/experience-reports/individuals-and-interactions-over-processes-and-tools/

40. Cross Industry Process for Data Mining (CRISP-DM)

41. ChatOps

42. Self Healing Systems
machine learning analysis of
• operation logs => root cause and fixing outages
• network traffic
• the OT => neutralise cyber attack vectors

43. evolution of the user interface
Command
Line
Interface
Graphical
User
Interface
Natural
User
interface

44. Natural user interface design
Intuitive systems that respond to speech and gestures
Immersive interfaces

45. self-learning software

46. Self learning systems
Convergence of machine learning with web analytics will provide a deeper
understanding of our users
● AI assisted personalization
● Automatic persona discovery
● Persona refinement
● Intelligent feature usage reporting
● cohort analysis

47. unbiased product backlog prioritisation

48. software developers from coding fixed business logic to training machine learning
models
AI powered tooling for code generation
software testers Automatic test case generation
AI assisted test scenario planning
UX designers Natural User Interface Design
AI assisted persona mapping
operations ChatOps
Self healing systems
product owners AI assisted backlog prioritisation
Feature / persona usage insights
agile teams AI assisted planning through expert systems

49. What will a product team
look like in the future?

51. Agile Team will (still) need
Autonomy, Mastery & Purpose

53. AI Ethics

57. AI Bias

60. the importance of diversity
in AI

61. we are at an ethical inflection point ….

62. it’s up to us to write right the future

63. proposing the AI manifesto
“We recognise that artificial intelligence will have a significant impact on our
society. We pledge to only build AI systems that will contribute to the greater
good.”
❖ AI systems must treat all people equally, they must not create
or reinforce unfair bias
❖ AI systems must not be weaponized
❖ AI systems must be socially beneficial
❖ AI systems must respect privacy