Published on April 26th, 2019 | by Emergent Enterprise0
3 Reasons Why AI will Never Match Human Creativity
There is much handwringing about AI and how it will take over one day. In this article by Katharine Schwab at FastCompany she shares one expert’s view about AI and its limitations especially when it comes to creativity. There is always potential for bad outcomes for technological progress but most of those are due to how we as a society create them. Use your creativity – and your innovation – for good.
[Source Photo: Flickr user Daniel Huizinga]
Sociology professor Anton Oleinik argues that neural networks are structured in a way that limits the possibility that they will ever have true artificial creativity.
Neural networks–a common type of artificial intelligence–are infiltrating every aspect of our lives, powering the internet-connected devices in our homes, the algorithms that dictate what we see online, and even the computational systems in our cars. But according to an article published in the peer-reviewed journal Big Data & Society by Anton Oleinik, a sociology professor at Memorial University of Newfoundland, there’s one crucial area where neural networks do not outperform humans: creativity.
Researchers have projected that automation may claim 800 million jobs around the world by 2030. Others suggest that as many as half of American jobs may be under threat from automation. But amid all the handwringing about robots taking people’s jobs, Oleinik’s analysis is further evidence that AI will likely only replace repetitive tasks that humans aren’t particularly skilled at to begin with. Even as AI creeps into creative fields, it is still only doing the work of recommending ideas to a human designer, who is spared some of his or her job’s mindlessness but still makes the final call about what a website or app will look like.
So why are neural nets so bad at being creative? Neural networks are machine learning algorithms composed of layers of calculations that excel at ingesting vast amounts of data and finding every pattern within them. They fundamentally rely on statistical regression–which means that while they’re good at identifying patterns, they fail miserably to anticipate when a pattern will change, let alone connect one pattern to an unrelated pattern, a crucial ingredient in creativity. “Scholars in science and technology studies consider the capacity to trace linkages between heterogeneous and previously unconnected elements as a distinctive human social activity,” Oleinik writes. Unfortunately, creativity would be impossible without radical predictions, something regression analysis will never be able to do.