How Testers Can Revolutionize AI and Machine Learning
You may have heard that software ate the world and AI is eating software. However, if you’ve been paying attention, then you’ve probably realized that the world is filled with bad software. Many organizations struggle with meeting their quality goals and keeping testing-related costs contained. Software is indeed revolutionizing the world, but the world is also paying a revolutionary price for bad software. So where do AI and machine learning (ML) fit in? Are AI/ML breakthroughs just new ways of filling the world with bad software? Or do they offer a path towards better software?
Tariq King believes that although ML is bringing valuable improvements and capabilities to software, it is unlikely for such advances to be successful without integrating testing and quality engineering into AI/ML workstreams. Join Tariq as he highlights the parallels and differences between ML engineering and software testing, and explains why he is convinced that testing professionals hold the keys for the transition to AI/ML system development. However, before testers can revolutionize AI/ML, they must first become agents of change through innovation. For the first time, Tariq will share his own journey and transformation, and discuss how he is helping other individuals, teams, and organizations on the road to AI.
Tariq King is the Vice President of Product-Service Systems at EPAM, where he manages a portfolio that lies at the intersection of software products and services, and supports the business through technology consulting. Tariq has over fifteen years' experience in software engineering and testing and has formerly held positions as Chief Scientist, Head of Quality, Director of Quality Engineering, Manager of Software Engineering and Test Architect. Tariq holds Ph.D. and M.S. degrees in Computer Science from Florida International University, and a B.S. in Computer Science from Florida Tech. His areas of research are software testing, artificial intelligence, autonomic and cloud computing, model-driven engineering, and computer science education. He has published over 40 research articles in peer-reviewed IEEE and ACM journals, conferences, and workshops, and has been an international keynote speaker at leading software conferences in industry and academia.