#ATAGTR2023 Speaker
Welcome to the 8th Edition of the Global Testing Retreat 2023!
About Speaker
Brijesh Deb is a seasoned tech pro with more than 2 decades of experience. He works as a Principal Consultant at Infosys in the Netherlands and is also the Chief Enablement Officer of The Test Chat community. He’s all about making software testing and Agile work smoothly. He’s a hands-on guy who doesn’t just test apps and digital solutions but also helps organizations get better at dealing with digital transformations, making sure they always deliver top-notch stuff to their customers. When he’s not deep into tech, he likes to share his thoughts on LinkedIn and dig into understanding people through his love of anthropology, keeping things interesting and always learning something new.
In AI We Trust, or Not: Navigating between reliance and distrust in the Testing
As the allure of AI-driven testing enchants the tech world with promises of streamlined operations and optimized efficiencies, a nuanced exploration beyond its glimmering façade reveals significant, often overlooked, pitfalls. This riveting keynote dives deep into the intricacies and paradoxes of AI in testing – unmasking its struggles with bias, ethical dilution, and contextual misapprehensions that cast shadows over its purported capabilities. We embark on a journey through the realms of testing automation, navigating through the perplexing mazes of ethical considerations, and the elusive understanding of context, to conjure a balanced, innovative, and morally aligned testing future.
Â
This keynote aims to weave through the enticing yet deceptive landscapes of AI in testing, instigating thought-provoking discussions and offering tangible navigational tools to steer through its concealed impediments towards a robust, ethically aligned, and contextually aware testing future.
Â
Key Takeaways:
- AI’s Double-Edged Sword: An exploration of the paradoxes and conflicts arising from AI’s capabilities vs. its real-world outcomes in testing, punctuated with practical examples of where and how AI falls short despite its theoretical promises.Â
- Context, Bias, and Ethics: An Interwoven Complexity:A critical examination of how bias and ethical misalignments infiltrate AI testing, coupled with its struggle to accurately capture and implement contextual nuances, thereby exploring the intertwined complexities that shape and often misshape testing outcomes.Â
- Crafting the Compass: Guiding Principles for the Future: Unveiling a forward-looking framework that not only acknowledges AI’s shortcomings but also paves the way towards rectifying them – involving a symbiotic relationship between technology and human oversight, ethical alignment, and research-driven approaches to augment AI’s contextual understanding in testing environments.