Exploring Biological Intelligence Through Artificial Intelligence And Radical Reimplementation

An important goal in artificial intelligence and biology is to uncover general principles that underlie intelligence. While artificial intelligence algorithms need not relate to biology, they might provide a synthetic means to investigate biological intelligence in particular. Importantly, a more complete understanding of such biological intelligence would profoundly impact society. Thus, to explore biological hypotheses some AI researchers take direct inspiration from biology. However, nature\u27s implementations of intelligence may present only one facet of its deeper principles, complicating the search for general hypotheses. This complication motivates the approach in this paper, called radical reimplementation, whereby biological insight can result from purposefully unnatural experiments. The main idea is that biological hypotheses about intelligence can be investigated by reimplementing their main principles intentionally to explicitly and maximally diverge from existing natural examples. If such a reimplementation successfully exhibits properties similar to those seen in biology it may better isolate the underlying hypothesis than an example implemented more directly in nature\u27s spirit. Two examples of applying radical reimplementation are reviewed, yielding potential insights into biological intelligence despite including purposefully unnatural underlying mechanisms. In this way, radical reimplementation provides a principled methodology for intentionally artificial investigations to nonetheless achieve biological relevance. Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved