Biological Faithfulness is Unnecessary for Machine Learning

Meagan Wiederman

doi:10.5206/uwomj.v87i2.1134

Abstract

Artificial intelligence (AI) is the ability of any device to take an input, like that of its environment, and work to achieve a desired output. Some advancements in AI have focused n replicating the human brain in machinery. This is being made possible by the human connectome project: an initiative to map all the connections between neurons within the brain. A full replication of the thinking brain would inherently create something that could be argued to be a thinking machine. However, it is more interesting to question whether a non-biologically faithful AI could be considered as a thinking machine. Under Turing’s definition of ‘thinking’, a machine which can be mistaken as human when responding in writing from a “black box,” where they can not be viewed, can be said to pass for thinking. Backpropagation is an error minimizing algorithm to program AI for feature detection with no biological counterpart which is prevalent in AI. The recent success of backpropagation demonstrates that biological faithfulness is not required for deep learning or ‘thought’ in a machine. Backpropagation has been used in medical imaging compression algorithms and in pharmacological modelling.

Highlights

The brain, or natural intelligence (NI), is considered the gold standard model of intelligence
Progress inspired by NI advances the field of artificial intelligence (AI) design under the assumption that making a machine like the thinking brain would translate into a thinking machine
Biologically faithful neural ai McClelland et al argue that models should be informed and constrained by our knowledge of the neural processes that underpin cognition, since learning is inherently anthropomorphic, and that machines will require humanistic qualities to be capable of such feats.[4]

Summary

Introduction

The brain, or natural intelligence (NI), is considered the gold standard model of intelligence. Since the machine and human cannot be seen and it’s only their output to the judge’s questions that indicates their intelligence, the Turing test can allow for nonbiologically faithful models to be considered “thinking”.

Results

Conclusion