Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-19T11:46:19.490Z Has data issue: false hasContentIssue false

Intelligent machines and human minds

Published online by Cambridge University Press:  10 November 2017

Elizabeth S. Spelke
Affiliation:
Department of Psychology, Harvard University, Cambridge, MA 02138. spelke@wjh.harvard.eduhttps://software.rc.fas.harvard.edu/lds/research/spelke/elizabeth-spelke/
Joseph A. Blass
Affiliation:
Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208. joeblass@u.northwestern.eduhttp://qrg.northwestern.edu/people/Blass

Abstract

The search for a deep, multileveled understanding of human intelligence is perhaps the grand challenge for 21st-century science, with broad implications for technology. The project of building machines that think like humans is central to meeting this challenge and critical to efforts to craft new technologies for human benefit.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Chiandetti, C., Spelke, E. S. & Vallortigara, G. (2014) Inexperienced newborn chicks use geometry to spontaneously reorient to an artificial social partner. Developmental Science 18(6):972–78. doi:10.1111/desc.12277.CrossRefGoogle Scholar
Doeller, C. F., Barry, C. & Burgess, N. (2010) Evidence for grid cells in a human memory network. Nature 463(7281):657–61. doi:10.1038/nature08704.CrossRefGoogle Scholar
Doeller, C. F. & Burgess, N. (2008) Distinct error-correcting and incidental learning of location relative to landmarks and boundaries. Proceedings of the National Academy of Sciences of the United States of America 105(15):5909–14.CrossRefGoogle ScholarPubMed
Doeller, C. F., King, J. A. & Burgess, N. (2008) Parallel striatal and hippocampal systems for landmarks and boundaries in spatial memory. Proceedings of the National Academy of Sciences of the United States of America 105(15):5915–20. doi:10.1073/pnas.0801489105.CrossRefGoogle ScholarPubMed
Hubel, D. H. & Wiesel, T. N. (1959) Receptive fields of single neurons in the cat's striate cortex. Journal of Physiology 124:574–91.CrossRefGoogle Scholar
Marr, D. (1982/2010). Vision. MIT Press.Google Scholar
Mascalzoni, E., Regolin, L. & Vallortigara, G. (2010). Innate sensitivity for self-propelled causal agency in newly hatched chicks. Proceedings of the National Academy of Sciences of the United States of America 107(9):4483–85.CrossRefGoogle ScholarPubMed
Moser, E., Kropff, E. & Moser, M. B. (2008). Place cells, grid cells, and the brain's spatial representation system. Annual Review of Neuroscience 31:6989.CrossRefGoogle ScholarPubMed
O'Keefel, (2014). Nobel lecture: Spatial cells in the hippocampal formation. Available at: http://www.nobelprize.org/nobel_prizes/medicine/laureates/2014/okeefe-lecture.html.Google Scholar
O'Keefe, J. & Nadel, L. (1978). The hippocampus as a cognitive map. Oxford University Press.Google Scholar
Regolin, L., Vallortigara, G. & Zanforlin, M. (1995). Object and spatial representations in detour problems by chicks. Animal Behaviour 49:195–99.CrossRefGoogle Scholar
Spelke, E. S. & Lee, S. A. (2012). Core systems of geometry in animal minds. Philosophical Transactions of the Royal Society, B: Biological Sciences 367(1603):2784–93.CrossRefGoogle ScholarPubMed
Squire, L. (1992). Memory and the hippocampus: A synthesis from findings with rats, monkeys and humans. Psychological Review 99(2):195231.CrossRefGoogle ScholarPubMed
Wills, T. J., Cacucci, F., Burgess, N. & O'Keefe, J. (2010). Development of the hippocampal cognitive map in preweanling rats. Science 328(5985):1573–76.CrossRefGoogle ScholarPubMed