Prescott, T.J. (2013) The AI singularity and runaway human intelligence. In: Biomimetic and Biohybrid Systems. Second International Conference, Living Machines 2013, July 29 – August 2, London, UK. Lecture Notes in Computer Science, 8064 L . Springer Berlin Heidelberg , pp. 438-440. ISBN 9783642398018
Abstract
There is increasing discussion of the possibility of AI being developed to a point where it reaches a "singularity" beyond which it will continue to improve in a runaway fashion without human help. Worst-case scenarios suppose that, in the future, homo sapiens might even be replaced by intelligent machines as the dominant "species" on our planet. This paper argues that the standard argument for the AI singularity is based on an inappropriate comparison of advanced AI to average human intelligence, arguing instead that progress in AI should be measured against the collective intelligence of the global community of human minds brought together and enhanced be smart technologies that include AI. By this argument, AI as a separate entity, is unlikely to surpass "runaway" human (or, perhaps, posthuman) intelligence whose continued advance, fueled by scientific and cultural feedback, shows no sign of abating. An alternative scenario is proposed that human collective intelligence will take an increasingly biohybrid form as we move towards a greater, deeper and more seamless integration with our technology. © 2013 Springer-Verlag Berlin Heidelberg.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2013 Springer-Verlag Berlin Heidelberg. This is an author produced version of a paper subsequently published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Societal impact of technology; AI singularity; collective intelligence; human-machine symbiosis; biohybrid |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 16 Nov 2016 15:45 |
Last Modified: | 21 Mar 2018 17:08 |
Published Version: | http://link.springer.com/chapter/10.1007/978-3-642... |
Status: | Published |
Publisher: | Springer Berlin Heidelberg |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-642-39802-5-59 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:107509 |