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AI as a Disruptive Technology

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Artificial Intelligence as a Disruptive Technology

Abstract

Artificial intelligence (AI) is symptomatic of the Fourth Industrial Revolution and is the most important of several disruptive technologies which includes blockchain. There are three types of AI: artificial narrow intelligence whereby robots or comparable substitutes are able to perform singular tasks well; artificial general intelligence whereby AI seeks to emulate human intelligence and capabilities; and artificial superintelligence which is futuristic whereby AI mechanisms are superior to human intelligence. There are numerous subfields of AI including machine learning and its major subdivisions of deep learning and deep mind, robotics, facial recognition, artificial neural networks, and natural learning progression.

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Notes

  1. 1.

    Jacob Morgan, What is the Fourth Industrial Revolution? FORBES (Feb. 19, 2016) https://www.forbes.com/sites/jacobmorgan/2016/02/19/what-is-the-4th-industrial-revolution/#3a92fc57f392.

    This author wrote about the first major prong of the disruptive technologies that characterize the Fourth Industrial Revolution in his book, REGULATION OF CRYPTOCURRENCIES AND BLOCKCHAIN TECHNOLOGIES (Palgrave Macmillan, 2018).

  2. 2.

    Mike Bainbridge, 3 Phases of Disruption, DISRUPTION HUB (May 4, 2017), https://distruptionhub.com/3-phases-distruption/.

  3. 3.

    Grant McCracken, The Five Stages of Disruption Denial, HBR (April, 2013), https://hbr.org/2013/04/distruption-denail.

  4. 4.

    Examples include: mobile internet, Internet of Things (discussed in Chap. 5), automation of knowledge work, advanced robotics, cloud, autonomous or semi-autonomous vehicles, next generation genomics, next generation storage, 3D printing, advanced materials, advanced oil and gas exploration and recovery, and renewable energy. Maria Fonseca, Guide to 12 Technology Examples, Intelligent HQ (March 2, 2014), https://www.intelligenthq.com/technology/12-disruptive-technologies/.

  5. 5.

    For a lengthy itemized history of AI from which this discussion relied on, see A Brief History of AI, AI TOPICS, https://aitopics.org/misc/brief-history.

  6. 6.

    Martin Childs, John McCarthy: Computer scientist known as the father of AI, INDEPENDENT (Nov. 1, 2011), https://www.independent.co.uk/news/obituaries/john-mccarthy-computer-scientist-known-as-the-father-of-ai-6255307.html.

  7. 7.

    Alan Turing, STANFORD ENCYCLOPEDIA OF PHILOSOPHY, rev. Sept. 30, 2013, https://plato.stanford.edu/entries/turing/.

  8. 8.

    Deep Blue, IBM 100, https://www.ibm.com/ibm/history/ibm100/us/en/icons/deepblue/.

  9. 9.

    Tom Simonite, DeepMind Beats Pros at Starcraft in Another Triumph for Bots, WIRED (Jan. 25, 2019), https://technewstube.com/wired/1074075/deepmind-beats-pros-at-starcraft-in-another-triumph-for-bots/.

  10. 10.

    Artificial Intelligence, ENCYCLOPAEDIA BRITANNICA, https://www.britannica.com/technology/artificial-intelligence.

  11. 11.

    Artificial Intelligence, SCIENCE DAILY, https://www.sciencedaily.com/terms/artificial_intelligence.htm.

  12. 12.

    Artificial Intelligence, OXFORD LIVING DICTIONARY, https://en.oxforddictionaries.com/definition/artificial_intelligence.

  13. 13.

    Artificial Intelligence, WIKIPEDIA, https://en.wikipedia.org/wiki/Artificial_intelligence.

  14. 14.

    NATIONAL SECURITY COMMISSION ON ARTIFICIAL INTELLIGENCE ACT OF 2018, S. 2806, 115th Cong. (2018), https://www.congress.gov/115/bills/s2806/BILLS-115s2806is.pdf.

  15. 15.

    Ben Dickson, What is Narrow, General, and Super Artificial Intelligence?, TECHTALKS (May 12, 2017), https://bdtechtalks.com/2017/05/12/what-is-narrow-general-and-super-artificial-intelligence/.

  16. 16.

    Id.

  17. 17.

    Tetiana Shevchenko, 3 Types of Artificial Intelligence Everyone Knows About, LETZGRO (Aug. 10, 2016), http://letzgro.net/blog/3-types-of-artificial-intelligence/.

  18. 18.

    MAX TEGMARK, LIFE 3.0: BEING HUMAN IN THE AGE OF ARTIFICIAL INTELLIGENCE, at 134 (Vintage Books, 2017).

  19. 19.

    Id. at 162.

  20. 20.

    Aaron Hintze, Understanding the Four Types of Artificial Intelligence, GOVERNMENT INTELLIGENCE (Nov. 14, 2016), http://www.govtech.com/computing/Understanding-the-Four-Types-of-Artificial-Intelligence.html.

  21. 21.

    Kai-Fu Lee, The Four Waves of A.I., FORTUNE (Nov. 1, 2018) at 91–94, fortune.com/2018/10/22/artificial-intelligence-ai-deep-learning-kai-fu-lee/.

  22. 22.

    Id. at 94.

  23. 23.

    Yasir Arfat, QUORA (April 17, 2016), https://www.quora.com/What-are-the-subfields-of-AI.

  24. 24.

    The Difference Between AI, Machine Learning & Robots, DELL TECHNOLOGIES, https://www.delltechnologies.com/en-us/perspectives/the-difference-between-ai-machine-learning-and-robotics/.

  25. 25.

    Louis Columbus, McKinsey’s State of Machine Learning and AI, 2017, FORBES (July 9, 2017), https://www.forbes.com/sites/louiscolumbus/2017/07/09/mckinseys-state-of-machine-learning-and-ai-2017/#291e5bd175b6.

  26. 26.

    Artificial Intelligence (AI) vs. Machine Learning vs. Deep Learning, SKYMIND, https://skymind.ai/wiki/ai-vs-machine-learning-vs-deep-learning.

  27. 27.

    Algorithm is a set of instructions or procedure for performing a calculation or solving a mathematical problem generally by use of a computer.

  28. 28.

    Neurons are electrically excitable cells in the nervous system that function to process and transmit information, SCIENCEDAILY, https://www.sciencedaily.com/terms/neuron.htm.

  29. 29.

    Seema Singh, Cousins of Artificial Intelligence, TOWARDS DATA SCIENCE (May 26, 2018), https://towardsdatascience.com/cousins-of-artificial-intelligence-dda4edc27b55.

  30. 30.

    Raja Mitra, Understanding AI and the Shades of Difference among its Subsets, MEDIUM.COM (May 6, 2017), https://medium.com/@montouche/understanding-ai-and-the-shades-of-difference-among-its-subsets-4c84b106d0c1.

  31. 31.

    AlphaGo, https://deepmind.com/research/alphago/.

  32. 32.

    Solve Intelligence. Use it to make the world a better place, DEEPMIND, https://deepmind.com/about/.

  33. 33.

    Machine learning can boost the value of wind energy, DEEPMIND, https://deepmind.com/blog/machine-learning-can-boost-value-wind-energy/.

  34. 34.

    How we’re helping today, DEEPMIND, https://deepmind.com/applied/deepmind-health/working-partners/how-were-helping-today/.

  35. 35.

    For a discussion how the NTM seeks to mimic the human brain’s short-term memory, see Google’s Secretive DeepMind Startup Unveils a “Neural Turing Machine,” MIT TECHNOLOGY REVIEW (Oct. 29, 2014), https://www.technologyreview.com/s/532156/googles-secretive-deepmind-startup-unveils-a-neural-turing-machine/.

  36. 36.

    Robotics, THE AMERICAN HERITAGE DICTIONARY OF THE ENGLISH LANGUAGE, https://www.ahdictionary.com/word/search.html?q=robotics/.

  37. 37.

    Robotics, WIKIPEDIA, https://en.wikipedia.org/wiki/Robotics.

  38. 38.

    Taniya Arya, What is computer vision in artificial intelligence?, QUORA, https://www.quora.com/What-is-computer-vision-in-artificial-intelligence.

  39. 39.

    Vision and AI, VISION RECOGNITION, MBHA, https://mbhs.edu/~lpiper/computer_vision03/visionai.html.

  40. 40.

    Honda, ASIMO, http://asimo.honda.com/downloads/pdf/asimo-technical-information.pdf.

  41. 41.

    Computer Vision vs. Machine Vision, AIA VISION ONLINE, https://www.visiononline.org/vision-resources-details.cfm/vision-resources/Computer-Vision-vs-Machine-Vision/content_id/4585.

  42. 42.

    Other sub-domains of computer vision are: scene reconstruction, event detection, video tracking, object recognition, 3D pose estimation, learning, indexing, motion estimation, and image restoration. Computer vision, WIKIPEDIA, https://en.wikipedia.org/wiki/Computer_vision.

  43. 43.

    Facial recognition system, WIKIPEDIA, https://en.wikipedia.org/wiki/Facial_recognition_system.

  44. 44.

    Facial Recognition Market Worldwide Expected to Reach $9.6 Billion by 2022, HT HOSPITAL TECHNOLOGY (July 1, 2016), https://hospitalitytech.com/facial-recognition-market-expected-reach-96-billion-worldwide-2022.

  45. 45.

    Artificial neural network, TECHOPEDIA, https://www.techopedia.com/definition/5967/artificial-neural-network-ann.

  46. 46.

    A Basic Introduction to Neural Networks, http://pages.cs.wisc.edu/~bolo/shipyard/neural/local.html.

  47. 47.

    Artificial neural network, WIKIPEDIA, https://en.wikipedia.org/wiki/Artificial_neural_network; https://www.sciencedirect.com/topics/neuroscience/speech-processing.

  48. 48.

    Speech Processing, SCIENCEDIRECT, https://www.sciencedirect.com/topics/neuroscience/speech-processing.

  49. 49.

    G. Harsha Vardham and G. Hari Charan, Artificial Intelligence and its Applications for Speech Recognition, 3 INTERNATIONAL J. OF SCIENCE & RESEARCH, Issue 8 (Aug. 12, 2014), https://www.ijsr.net/archive/v3i8/MDUwODE0MDU=.pdf.

  50. 50.

    Kenneth A. DeJong, Evolutionary Computation: A Unified Approach, AMAZON CO UK, https://www.amazon.com/Evolutionary-Computation-Approach-Kenneth-Jong/dp/0262529602 and Evolutionary Computation, WIKIPEDIA, https://en.wikipedia.org/wiki/Evolutionary_computation.

  51. 51.

    Jason Brownlee, What is Natural Language Processing?, MACHINE LEARNING MASTERY (Sept. 22, 2017), https://machinelearningmastery.com/natural-language-processing/; and Matt Kiser, Introduction Language Processing, ALGORITHMIA (Aug. 11, 2016), https://blog.algorithmia.com/introduction-natural-language-processing-nlp/.

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  1. Goldstein Academic Center 203, Pace University, Pleasantville, NY, USA

    Rosario Girasa

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Girasa, R. (2020). AI as a Disruptive Technology. In: Artificial Intelligence as a Disruptive Technology. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-35975-1_1

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  • DOI: https://doi.org/10.1007/978-3-030-35975-1_1

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