Simple Heuristics That Make Algorithms Smart
Although simple heuristics often yield “biased” decisions, they can deliver a better answers. What might this mean for today’s complex algorithms?
Jason Collins is data science lead with Australia's corporate, markets, and financial services regulator. He specializes in economics, evolution, and behavioral science, and he blogs at Evolving Economics. He has co-led PwC Australia's behavioral economics practice and has also worked as a lawyer and an economic policy adviser with the Australian Treasury. He has a Ph.D. from the University of Western Australia.
Although simple heuristics often yield “biased” decisions, they can deliver a better answers. What might this mean for today’s complex algorithms?
Behavioral teams have been a positive and resulted in some excellent outcomes. But my experience working in and alongside nudge units has me asking: Has the pendulum swung too far?
Is our reluctance to have our decisions and actions replaced by automated systems warranted?
When we examine objectives from an evolutionary biology perspective, we see that what appears irrational might simply be a misunderstanding on our part of what someone’s objectives are.
Can humans and computers work together, or should we simply bow down to the algorithms?