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A Framework for Understanding AI-Induced Field Change: How AI Technologies are Legitimized and Institutionalized

πŸ“… 2021
technical research breakthrough
πŸ”΅ Rare

πŸ“– Description

A Framework for Understanding AI -Induced Field Change: How AI Technologies are Legitimized and Institutionalized Benjamin Cedric Larsen Department of Economics Government & Business Copenhagen Business School Copenhagen, Denmark [email address redacted] ABSTRACT Artificial intelligence (AI) systems operate in increasingly diverse areas, from healthcare to facial recognition, the stock market, autonomous vehicles, and so on. While the underlying digital infrastructure of AI systems is developing rapidly, each area of implemen tation is subject to different degrees and processes of legitimization. By combining elements from institutional theory and information systems -theory, this paper presents a conceptual framework to analyze and unde rstand AI -induced field -change. The introd uction of novel AI -agents into new or existing fields creates a dynamic in which algorithms (re)shape organizations and institutions while existing inst...

πŸ“Š Game Impacts

Not verified in game

Which variables this event was proposed to move, and in which direction. The magnitudes are held in the corpus but are not shown here, because they have not been verified against the shipped game. They come from pdoom-data. They describe what an event was proposed to do, not what the shipped game does with it. Most events in the corpus are flavour: they are shown for colour and do not move any game variable. Only a small minority reach the systems below, and several of the variables listed here are not read by the game at all yet. Treat this table as a design proposal under review, not as a measurement of play. Corrections and arguments are welcome — the suggestion links at the foot of this page go straight to the data repo.

Variable Direction Condition
Research proposed: up Always
Papers proposed: up Always
Vibey Doom proposed: up Always

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