OVIC: Closer to the Machine

On this episode of AI Australia, we're changing things up a little. With James overseas, Nigel and his friend Sarah Turner from REA Group hosted multiple panel conversations with some of Australia's best and brightest in the field of AI, computer science, mathematics, and regulation to discuss the launch of OVIC's new book: Closer to the Machine. OVIC is the Office of Victorian Information Commissioner and is the primary regulator and source of independent advice to the community and Victorian government about how the public sector collects, uses and shares information.   In this episode, we're lucky to be joined by: Sarah Turner (co-host) - General Counsel, REA Group Adam Spencer - comedian, media personality and former radio presenter Rachel Dixon - Privacy and Data Protection Deputy Commissioner, OVIC Professor Toby Walsh (University of New South Wales and CSIRO's Data61)  Professor Richard Nock (Australian National University and CSIRO's Data61)  Associate Professor Ben Rubinstein (University of Melbourne)  Katie Miller (Independent Broad-based Anti-corruption Commission)  Professor Margaret Jackson (RMIT)    In this episode we discuss: The degree to which we all take for granted how big a part AI plays in our lives The rate of improvement in algorithms in their narrow fields of "expertise". We discuss how quickly a chess-playing AI went from basic to beating the chess grandmaster Gary Kasparov OVIC's motivation for publishing the book on data privacy and protection Grappling with the implications of how AI systems can be misused, or easily breached from a security standpoint. Do we continue to push the boundaries in the face of privacy risks and concerns? Do we pull back? The challenge of discrimination. Eventually, machines will need to make decisions that "discriminate" against people in one way or another - but there is such a thing as good discrimination and bad discrimination. Who gets to make those definitions? What role should government play in the regulation (or non-regulation) of AI? Accountability. What happens when AI "goes rogue"? Where does the buck stop? How the conversation has evolved over the years, and become more "realistic" in a sense.   Links mentioned: OVIC: Closer to the Machine book