Theory‐Driven Perspectives on Generative Artificial Intelligence in Business and Management

Теоретически обоснованные подходы к генеративному искусственному интеллекту в бизнесе и управлении
Robert M. Davison, Renate E. Meyer, Gazi Islam, James Faulconbridge, Shuang Ren, David A. Ellis, Riikka M. Sarala, M. N. Ravishankar, Michelle Greenwood, Stephanie Decker, Olivia Brown, Julie Gore, Christina Lubinski, Niall MacKenzie, Daniel Muzio, Paolo Quattrone, Tammar B. Zilber, Paul Hibbert
2024-01-01

ChatGPTbusiness and managementdata privacy and securitygenerative artificial intelligencereal-time web access
The etymology of words is often a source of insights to not only make sense of their meaning, but also speculate and imagine meanings that are not so obvious and thereby see the phenomena signalled by these words in new and surprising ways.The etymology of 'artificial' and 'intelligence' does not disappoint.'Artificial' comes from 'art' and -fex 'maker', from facere 'to do, make'.'Intelligence' comes from inter 'between' and legere 'choose, pick out, read' but also 'collect, gather'.There is enough in these etymologies to offer a few speculations and imagine the contours of generative artificial intelligence (GAI) and its possible futures.The first of these is inspired by the craft of making and relates to the very function and use of AI.Most of the current fascinations with AI emphasize the predictive capacity of the various tools increasingly available and at easy disposal.Indeed, marketers know well in advance when we will need the next toothbrush, fuel our cars, buy new clothes, and so forth.The list is long.This feature of AI enchants us when, for instance, one thinks of a product and, invariably, an advertisement related to that product appears on our social media page.This quasi-magical predictive ability captures collective imaginations and draws upon very well-ingrained forms of knowledge production which presuppose that data techniques are there to represent the world, paradoxically, even when it is not there, as is the case with predictions.The issue is that the future is not out there; we do not know what future generations want from us and still, we are increasingly called to respond to their demands.Despite the availability of huge amounts of data points and intelligence, the future, even if proximal and mundane -as our examples above, always holds surprises.This means that AI may be useful not to predict the future, but to actually imagine and make it, as the -fex in 'artificial' reveals.This is the art in the 'artificial' and points to the possibility of conceiving AI as a compositional art, which helps us to create images of the future, sparks imagination and creativity and, hopefully, offers a space for speculation and reflection.The word intelligence is our second cue, which stresses how 'inter' means to be and explore what is 'in between'.As entrepreneurs are in between different ventures and explore what is not yet there (Hjorth and Holt, 2022), AI may be useful to probe grey areas between statuses
1
ChatGPT’s real-time web access may improve market analysis, trend tracking, customer service, and dynamic data-driven problem-solving through more current contextual information.
2
Extending GAI interactions across the Internet introduces additional data privacy and security challenges for organizations.
3
Generative artificial intelligence is generating both enthusiasm and anxiety because it may transform or disrupt business and management practices.
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Real-time web access creates concerns about information accuracy and reliability because online content can be dynamic and unverified.
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Responsible evaluation and use of advanced GAI capabilities is necessary in business and management contexts.

Generative artificial intelligence in business and management contexts

Its transformative and disruptive implications, opportunities, risks, and responsible-use requirements for business and management

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Publication Date
2024-01-01
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Authors
Robert M. Davison
Renate E. Meyer
Gazi Islam
James Faulconbridge
Shuang Ren
David A. Ellis
Riikka M. Sarala
M. N. Ravishankar
Michelle Greenwood
Stephanie Decker
Olivia Brown
Julie Gore
Christina Lubinski
Niall MacKenzie
Daniel Muzio
Paolo Quattrone
Tammar B. Zilber
Paul Hibbert
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