Artificial wisdom

From Wikipedia, the free encyclopedia

Artificial wisdom is a software system that can demonstrate one or more qualities of being wise.

Artificial wisdom can be described as artificial intelligence reaching the top-level of decision-making when confronted with the most complexe challenging situations.[1] The term artificial wisdom is used when the "intelligence" is based on more than by chance collecting and interpreting data, but by design[2] enriched with smart and conscience strategies that wise people would use.[3]

The worries about the future with artificial intelligence is bend to a more positive perspective when considering computer-aided wisdom; the collaboration between artificial intelligence and contemplative neuroscience.[4]

References[]

  1. ^ Phillips-Wren, Gloria; Ichalkaranje, Nikhil & Jain, Lakhmi (2008). "Intelligent Decision Making: An AI-Based Approach". Cite journal requires |journal= (help)CS1 maint: multiple names: authors list (link)
  2. ^ Suarez, Juan Francisco (2014). "Wise by Design: A Wisdom-Based Framework for Innovation and Organizational Design and its Potential Application in the Future of Higher Education". Dissertations & Theses Antioch University: 131.
  3. ^ Wang, Feng-Hsu (2011). "Personalized recommendation for web-based learning based on ant colony optimization with segmented-goal and meta-control strategies". IEEE International Conference on Fuzzy Systems: 2054–2059. doi:10.1109/FUZZY.2011.6007628. ISBN 978-1-4244-7315-1. S2CID 33702266.
  4. ^ Karamjit, Gill (2013). "Citizens and netizens: a contemplation on ubiquitous technology". AI & Society. 28 (2): 131–132. doi:10.1007/s00146-013-0451-5.

Further reading[]

  • Casacuberta Sevilla, David (2013). "The quest for artificial wisdom". AI & Society. 28 (2): 199–207. doi:10.1007/s00146-012-0390-6. S2CID 17183036.
  • Davis, Joshua P. (2019). "Artificial wisdom? A potential limit on AI in law (and elsewhere)". Oklahoma Law Review. 72 (1). doi:10.2139/ssrn.3350600.
  • Tsai, Cheng-hung (2020). "Artificial wisdom: a philosophical framework". AI & Society. doi:10.1007/s00146-020-00949-5. S2CID 211234659.
  • Siddike M.A.K., Iwano K., Hidaka K., Kohda Y., Spohrer J. (2018). "Wisdom Service Systems: Harmonious Interactions Between People and Machine". Advances in Intelligent Systems and Computing. 601: 115–127. doi:10.1007/978-3-319-60486-2_11. ISBN 978-3-319-60485-5.CS1 maint: multiple names: authors list (link)
  • Gopnik, Alison, "Making AI More Human: Artificial intelligence has staged a revival by starting to incorporate what we know about how children learn", Scientific American, vol. 316, no. 6 (June 2017), pp. 60–65.
  • Marcus, Gary, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific American, vol. 316, no. 3 (March 2017), pp. 58–63. A stumbling block to AI has been an incapacity for reliable disambiguation. An example is the "pronoun disambiguation problem": a machine has no way of determining to whom or what a pronoun in a sentence refers. (p. 61.)
  • San Segundo, Rosa (2002). "A new concept of knowledge". Online Information Review. 26 (4): 239–245. doi:10.1108/14684520210438688. hdl:10016/4490.
  • George Musser, "Artificial Imagination: How machines could learn creativity and common sense, among other human qualities", Scientific American, vol. 320, no. 5 (May 2019), pp. 58–63.
  • Serenko, Alexander; Michael Dohan (2011). "Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence" (PDF). Journal of Informetrics. 5 (4): 629–649. doi:10.1016/j.joi.2011.06.002.
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