Enjoyed the talk in Melbourne today. Great audience and some fine questions despite there not being many that had worked in BI testing before. I did enjoy the talk by David Colwell very much, highlighting the real and present opportunity (and dangers?) of using AI to augment our workloads. Well presented. To my benefit, it perfectly aligned to my talk on Intelligent Automation. It helped me get my points across very well. Some key takeaways.
Our Quality Assurance practices are still busy getting basic test automation going. Yet we need to not only adopt automation today, but need to look beyond development and seek out an active role in assuring operational quality where data is highly unstructured and unpredictable. Here, we won’t be able to automate with the more “traditional” automation tools. Scripting, record-n-play, model-driven will only help us to a point when it come to a volume of data that needs to be monitored for quality continuously.
Beginning to experiment and developing internal capability in using AI, Machine Learning and Cognitive toolsets will help us start to work with this problem. This means we need to hire Cognitive developers into our teams, or interns even with a strong aptitude for statistical thinking. We need to coach them up to work with AI models, work with training and validation data, and score models to train bots that can take on the tasks of continuous testing.
I’m excited to see so many technology vendors appearing on this scene this year. I look forward to seeing some interesting use cases coming out in future talks.
Full house at the Test Automation Summit 2017 in Melbourne this fine Thursday with beautiful spring weather too. I snuck out around the Treasury Gardens before my talk and was greeted to a very civilised lunchtime fare of people enjoying the sunshine. Reminded me of my summer lunch breaks in London.
If you have any ideas you wish to discuss, feel free to find me on twitter at @akaKennyJoseph
Kenny Joseph works with CogniCraft as an Innovation Architect, across marketing automation, fast data analytics, full-stack, cloud-native, quality engineering among other things.