Top-down vs Bottom-up Approaches to Strong AI

By LUKE MCGOVERN
Published: August 15, 2008

What are the major differences between top-down and bottom-up approaches to AI? The top-down approach is hinged on the belief that logic can be inferred from an existing intelligent system. The bottom-up approach, on the other hand, is concerned with creating basic elements and allowing a system to evolve to best suit it's environment.

Both approaches already have applications in the real world. The top-down approach has shown amazing results in the form of semantic understanding. One common application is replicating the logic behind language to create speech and language interpretation systems. The bottom-up approach has produced genetic algorithms which have been created to help find optimal solutions to complex problems.

When looking at the future of Strong AI, top-down approaches are showing the most results by far. There are however, a few bottom-up approaches such as the creation of child machines with a willingness to learn that are worth noting.

A bottom-up approch would be the most ideal way to create human-like intelligence as we ourselves are part of a bottom-up design process (which occured in the form of evolution). Unfortunately the world is not going to wait for something to grow out the electronic ooze and instead, the top-down approach will slowly show signs of true intelligence as all things of understanding will be put into boxes of logic for digital machines to understand. In all likely-hood, Strong AI will be a combination of the two approaches with an amalgamation of different systems to produce a Frankenstein-like effect. Humankind itself is likely to go down this road in years to come with the prospect of becoming super-intelligent cyborgs able to conjure up anything you wanted to know. The direct brain interface is not quite there yet, but with the way people are clinging to their iPhones, one could be easly mistaken in thinking that this has already happened.