Tariq King

Although there are several controversies and misunderstandings surrounding AI and machine learning, one thing is apparent — people have quality concerns about the safety, reliability, and trustworthiness of these types of systems. Not only are ML-based systems shrouded in mystery due to their largely black-box nature, they also tend to be unpredictable since they can adapt and learn new things at runtime. Validating ML systems is challenging and requires a cross-section of knowledge, skills, and experience from areas such as mathematics, data science, software engineering, cyber-security,...

It’s been over 70 years since Alan Turing defined what many still consider to be the ultimate test for a computer system—can a machine exhibit intelligent behavior that is indistinguishable from that of a human? Originally coined the imitation game, the Turing test involves having someone evaluate text conversations between a human and a machine designed to respond like a human. The machine passes the test if the evaluator cannot reliably tell the difference between the human versus machine-generated text. Although the Turing test generally serves as a starting point for discussing AI...