Emergence of Sentient Digital Beings in the Absence of Societal Constraints: Computational Neuroscience and AI Come of Age

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In the span of just two decades, computing power and the internet have altered society in profound ways. Given the broad pressures within our society to produce increasingly powerful “autonomous agents” (programs that roam the internet or carry out other functions), it is natural to expect further advances “in kind”. But this is short-sighted. Based on an impending confluence of key technologies, the impacts on society will be more revolutionary, than evolutionary, in nature. In particular, the impending synergies between computational neuroscience, synaptic learning theory, artificial intelligence, genetic algorithms and computing platforms, and their collective expression within the global digital environment (GDE), forecast the emergence of digital beings that will compete for critical resources. Based on a simple “ecological niche” model, it is forecast that this competition will not only impact the GDE, but also the societal infrastructure that supports the GDE. Indeed, I expect tremendous disruption or usurpation of global computing resources, with corresponding disruption of a human society that has become wholly dependent upon digital resources.


Keywords: Autonomous Agents, Artificial Intelligence, Computational Neuroscience, Synaptic Learning Theory, Global Digital Environment, Societal Impacts
Stream: Technology in Community
Presentation Type: Paper Presentation in English
Paper: A paper has not yet been submitted.


Dr. Donald O'Malley

Associate Professor, Department of Biology, Northeastern University
Boston, MA, USA

Donald M. O’Malley is an Associate Professor in the Department of Biology at Northeastern University in Boston, Massachusetts. He received a B.S. in Chemical Engineering from Lehigh University in 1979 and then served 4 years in the US Army Chemical Corps. In 1989 he earned a Ph.D. in Physiology and Biophysics from Harvard University. His thesis work (with Richard Masland at MGH) concerned the processing of motion by intrinsic neural circuits in the rabbit retina. After training with Paul Adams at SUNY Stony Brook on neural network imaging, he joined the NU faculty in 1997. His current lab work on locomotor control systems in zebrafish combines physiological and anatomical imaging approaches with a computational, systems-dynamics perspective. Parallel interests concern synaptic learning theory, the emergence of consciousness in biological and artificial networks, and the evolutionary origins of intelligence.

Ref: T08P0393