Abstracts

The stories we are fed about AI seem to fall into two categories:
1) It’s our saviour! It’s going to be wonderful!
2) It’s going to take all our jobs and destroy humanity! 
The media feed us so many simplified stories designed to stimulate our imaginations with science fiction fantasies, both utopian and dystopian. The law and governance around AI is also so far behind the curve that it can confuse the issues, often propagating the misconceptions and making life harder for those wanting to use AI sensibly. The truth is far more nuanced and requires us to understand much more than just the hype. Whether we like it or not, AI is here to stay and as Testers it is our job to understand those nuances, to understand what the actual risks are and how to mitigate them. 

So ...How do you test an AI system? And how do you Quality Assure an AI project?

This talk addresses some of the risks, opportunities and ethics involved. It provides a framework for testing & assuring AI-based systems. It also explores the techniques, skills sets and thinking patterns that we as Testers and QA’s need to adopt to remain relevant, as the fourth Industrial Revolution kicks in for real.

The talk will cover:
- The challenges specific to testing AI systems
- The AI specific Test Phases & Levels and how they fit through the development lifecycle 
- Test Techniques specific to AI systems
- How this testing framework fits into the bigger picture of QE & QA
- How to use this knowledge to create a Quality Assurance wrapper for AI systems to be applied even before the system is created.

It draws on actual live projects for clients, providing a practical, proven framework that can start to be applied immediately. Whether you are a Tester not knowing where to start, a Test Manager struggling to create strategies & approaches for an AI-based system or you just need a general understanding of how to test AI and ML systems, this is for you.

AI is evolving. We need to as well!