AI Alignment: A New Management Paradigm
Name
2020_1101_AI-Alignment_WixomSomehGregory.pdf
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438.8 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Wixom, Barbara H.
Someh, Ida A.
Date Issued
November 19, 2020
Publisher
Cambridge, Mass.: Center for Information Systems Research, Sloan School of Management, Massachusetts Institute of Technology
Citation
Wixom, Barbara H. and Ida A. Someh. “AI Alignment: A New Management Paradigm.” MIT CISR Research Briefing Volume XX, no. 11 (November 2020). https://dspace.mit.edu/handle/1721.1/174794.
Series/Report no.
MIT CISR Research Briefing, Vol. XX, No. 11
Abstract
Since 2019, MIT CISR has investigated fifty-two AI solutions applied analytics models that have some level of autonomy. This research has identified that safely deploying AI solutions at scale requires an adaptive management approach we call AI Alignment. AI Alignment involves achieving amidst dynamic, changing forces three interdependent states of consistency: scientific consistency, between reality and model; application consistency, between model and solution; and stakeholder consistency, between solution and stakeholder needs. In this briefing, we illustrate AI alignment and share supportive practices from AI projects at General Electric, the Australian Taxation Office, and Satellogic.†
Subjects
Data monetization
Information Technologies
Data, AI, and Analytics
Terms of Use
CC BY-NC 4.0 (Attribution-NonCommercial 4.0 International)
Persistent DSpace Link
