TY - JOUR
T1 - Metahuman systems = humans + machines that learn
AU - Lyytinen, Kalle
AU - Nickerson, Jeffrey V.
AU - King, John L.
N1 - Publisher Copyright:
© Association for Information Technology Trust 2020.
PY - 2021/12
Y1 - 2021/12
N2 - 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’s 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 metahuman 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, generalizable, 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.
AB - 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’s 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 metahuman 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, generalizable, 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.
KW - Machine learning
KW - autonomy
KW - embodiment
KW - job design
KW - learning theory
KW - monitoring
KW - organizational forms
KW - technology
KW - work groups
UR - http://www.scopus.com/inward/record.url?scp=85085339316&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85085339316&partnerID=8YFLogxK
U2 - 10.1177/0268396220915917
DO - 10.1177/0268396220915917
M3 - Article
AN - SCOPUS:85085339316
SN - 0268-3962
VL - 36
SP - 427
EP - 445
JO - Journal of Information Technology
JF - Journal of Information Technology
IS - 4
ER -