001469505 000__ 05466cam\\22006257i\4500
001469505 001__ 1469505
001469505 003__ OCoLC
001469505 005__ 20230803003333.0
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001469505 008__ 230608s2023\\\\sz\a\\\\ob\\\\000\0\eng\d
001469505 019__ $$a1381106623
001469505 020__ $$a3031310047$$qelectronic book
001469505 020__ $$a9783031310041$$q(electronic bk.)
001469505 020__ $$z9783031310034
001469505 020__ $$z3031310039
001469505 0247_ $$a10.1007/978-3-031-31004-1$$2doi
001469505 035__ $$aSP(OCoLC)1381479818
001469505 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dYDX$$dUKAHL$$dYDX$$dN$T$$dOCLCF
001469505 049__ $$aISEA
001469505 050_4 $$aQ325.5$$b.G35 2023
001469505 08204 $$a006.3/101$$223/eng/20230608
001469505 1001_ $$aGanem, Joseph,$$eauthor.
001469505 24510 $$aUnderstanding the impact of machine learning on labor and education :$$ba time-dependent Turing test /$$cJoseph Ganem.
001469505 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2023]
001469505 300__ $$a1 online resource (xvii, 74 pages) :$$billustrations (some color).
001469505 336__ $$atext$$btxt$$2rdacontent
001469505 337__ $$acomputer$$bc$$2rdamedia
001469505 338__ $$aonline resource$$bcr$$2rdacarrier
001469505 4901_ $$aSpringerBriefs in philosophy,$$x2211-4556
001469505 504__ $$aIncludes bibliographical references.
001469505 5050_ $$aIntroduction: The difference between knowing and learning -- Labor Markets: Comparative learning advantages -- Learning to Work: The two dimensions of job performance -- The Judgment Game: The Turing Test as a general research framework -- The Learning Game: A time-dependent Turing Test -- Implications: Recommendations for future education and labor policies.
001469505 506__ $$aAccess limited to authorized users.
001469505 520__ $$aThis book provides a novel framework for understanding and revising labor markets and education policies in an era of machine learning. It posits that while learning and knowing both require thinking, learning is fundamentally different than knowing because it results in cognitive processes that change over time. Learning, in contrast to knowing, requires time and agency. Therefore, "learning algorithms" -- that enable machines to modify their actions based on real-world experiences -- are a fundamentally new form of artificial intelligence that have potential to be even more disruptive to labor markets than prior introductions of digital technology. To explore the difference between knowing and learning, Turing's "Imitation Game," -- that he proposed as a test for machine thinking -- is expanded to include time dependence. The arguments presented in the book introduce three novel concepts: (1) Comparative learning advantage: This is a concept analogous to comparative labor advantage but arises from the disparate times required to learn new knowledge bases/skillsets. It is argued that in the future, comparative learning advantages between humans and machines will determine their division of labor. (2) Two dimensions of job performance -- expertise and interpersonal: Job tasks can be sorted into two broad categories. Tasks that require expertise have stable endpoints, which makes these tasks inherently repetitive and subject to automation. Tasks that are interpersonal are highly context-dependent and lack stable endpoints, which makes these tasks inherently non-routine. Humans compared to machines have a comparative learning advantage along the interpersonal dimension, which is increasing in value economically. (3) The Learning Game is a time-dependent version of Turing's "Imitation Game." It is more than a thought experiment. The "Learning Game" provides a mathematical framework with quantitative criteria for training and assessing comparative learning advantages. The book is highly interdisciplinary -- presenting philosophical arguments in economics, artificial intelligence, and education. It also provides data, mathematical analysis, and testable criteria that researchers in these fields will find of practical use. The book calls for a rethinking of how labor markets operate and how the education system should prepare students for future jobs. It concludes with a list of counterintuitive recommendations for future education and labor policies that all stakeholders -- employers, employees, educators, students, and political leaders -- should heed.
001469505 588__ $$aDescription based on online resource; title from digital title page (viewed on July 12, 2023).
001469505 650_0 $$aMachine learning$$xPhilosophy.
001469505 650_0 $$aArtificial intelligence$$xEducational applications.
001469505 650_0 $$aArtificial intelligence$$xIndustrial applications.
001469505 655_0 $$aElectronic books.
001469505 77608 $$iPrint version:$$z3031310039$$z9783031310034$$w(OCoLC)1373337240
001469505 830_0 $$aSpringerBriefs in philosophy,$$x2211-4556
001469505 852__ $$bebk
001469505 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-31004-1$$zOnline Access$$91397441.1
001469505 909CO $$ooai:library.usi.edu:1469505$$pGLOBAL_SET
001469505 980__ $$aBIB
001469505 980__ $$aEBOOK
001469505 982__ $$aEbook
001469505 983__ $$aOnline
001469505 994__ $$a92$$bISE