News article by Marcello Ienca.
Published in The Neuroethics Blog, Emory Center for Ethics.
The history of Artificial Intelligence (AI) is inextricably intertwined with the history of neuroscience. Since the early days of AI, scientists turned to the human brain as a source of guidance for the development of intelligent machines (Ullman 2019). Unsurprisingly, many pioneers of AI such as Warren McCulloch were trained in the sciences of the brain. Modern AI borrowed most of its vocabulary from neurology and psychology. For instance, computational models consisting of networks of interconnected units —one of the most common approaches to AI— are called Artificial Neural Networks (ANN). Each unit is called an “artificial neuron.” Several areas of research in AI are labelled through neuropsychological categories such as computer vision, machine learning, natural language processing etc. It’s not just a matter of terminology. ANNs, for example, are actually inspired by and based on the functioning of biological neural networks that constitute animal nervous systems.
In spite of this intimate link between AI and neuroscience, ethical reflections on these two disciplines have developed quite independently of each other and with little interaction between the two research communities. On the one hand, the AI ethics community has focused primarily on issues such robot rights, algorithmic transparency, biases in AI systems, and autonomous weapons. On the other hand, the neuroethics community has primarily focused on issues such as pharmacological enhancement, brain interventions, neuroimaging, and free will. [ . . . ]