Meta-human Systems = Humans + Machines That Learn
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Lyytinen:2021:JIT,
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author = "Kalle Lyytinen and Jeffrey V Nickerson and
John L King",
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title = "Meta-human Systems = Humans + Machines That Learn",
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journal = "Journal of Information Technology",
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year = "2021",
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volume = "36",
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number = "4",
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pages = "427--445",
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month = "1 " # dec,
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keywords = "genetic algorithms, genetic programming, AI, machine
learning, learning theory, technology, work groups, job
design, organizational forms, monitoring, embodiment,
autonomy",
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ISSN = "0268-3962",
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URL = "https://journals.sagepub.com/doi/pdf/10.1177/0268396220915917",
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DOI = "doi:10.1177/0268396220915917",
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size = "19 pages",
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abstract = "Metahuman systems are new, emergent, sociotechnical
systems where machines that learn join human learning
and create original systemic capabilities. Metahuman
systems will change many facets of the way we think
about organizations and work. They will push
information systems research in new directions that may
involve a revision of the field research goals, methods
and theorizing. Information systems researchers can
look beyond the capabilities and constraints of human
learning toward hybrid human/machine learning systems
that exhibit major differences in scale, scope and
speed. We review how these changes influence
organization design and goals. We identify four
organizational level generic functions critical to
organize meta-human systems properly: delegating,
monitoring, cultivating, and reflecting. We show how
each function raises new research questions for the
field. We conclude by noting that improved
understanding of metahuman systems will primarily come
from learning-by-doing as information systems scholars
try out new forms of hybrid learning in multiple
settings to generate novel, generalisable, impactful
designs. Such trials will result in improved
understanding of metahuman systems. This need for
large-scale experimentation will push many scholars out
from their comfort zone, because it calls for the
revitalization of action research programs that
informed the first wave of socio-technical research at
the dawn of automating work systems.",
- }
Genetic Programming entries for
Kalle Lyytinen
Jeffrey V Nickerson
John Leslie King
Citations