The buzz around Artificial Intelligence (AI) can’t seem to stop these days. But increased interest comes with increased uncertainty. How will AI affect our lives and societies? How can it be used to stay ahead, in business and other domains? What can it do?
To cut through the marketing hype and answer these questions, one must start by understanding what AI is. The field of AI is not new. It emerged in the 1950s as a multi-disciplinary endeavor to try to represent and replicate human intelligence using computers. It involved not only computer science (the ‘Artificial’ in AI), but also cognitive science, linguistics, psychology, and neuroscience (the ‘Intelligence’ in AI). In the decades that followed, AI went through cycles of booms and busts (‘AI winters’), due to (too) high expectations about AI’s potential that inevitably led to disappointments when the potential did not materialize.
Today, AI is used as an umbrella term to refer to all sorts of computational methods that allow machines to perform specific tasks automatically. However, 99% of research and efforts fueling the current AI boom are concentrated in a sub-field known as Machine Learning (ML). ML started to blossom in the late 1990s thanks to the increased availability of digital data, better micro-processors, and new algorithms that allowed computers to process vast amounts of data quickly to identify patterns.