New AI Computing Paradigm Needs New Quality Thinking - Which-50

A lot has been written about problems with artificial intelligence recently; speech recognition failing to correctly deal with Irish accents, image recognition that cannot detect faces of colour, all kinds of biases in AI decision making, or autonomous vehicles causing accidents. In response, some have called for more rigorous testing, quality assurance, and trust certification of AI products and services and their providers. For example, in his recent keynote at a Committee for Economic Development of Australia (CEDA) event in Sydney, Dr Alan Finkel, Australia's chief scientists, proposed a solution to "overcoming our mistrust of robots in our homes and workplaces". In his talk Dr Finkel proposed a trust certification for AI, whereby providers would submit to a voluntary auditing process to establish the quality of their AI-based products, as well as the ethical standards that their organisation embodies. Dr Finkel claims that "true quality is achieved by design, not by test and reject," so we should ensure that AI products are reliable before we release them into the wild.