How do we train a stone to think? A review of machine intelligence and its implications
Paul Mario Koola, Satheesh Ramachandran, Kalyan Vadakkeveedu · Theoretical Issues in Ergonomics Science · 2015
Machines have been getting intelligent and they are outpacing humans at certain complex tasks. This paper gives an overview of some of the key technologies used in machine intelligence. We hypothesize that given the future projections in machine capabilities, man–machine symbiosis is a given. Hence, we propose that human learning must be driven to increase the capacity to understand the concepts and apply that knowledge, rather than just memorise the facts or processes. Repetitive human tasks will get automated, freeing us to push the boundaries of creativity and innovation. This will force us to change how we learn and adapt.