Real-Time Management: When AI Goes Fast and Flow

Pernille Rydén () and Omar El Sawy ()
Additional contact information
Pernille Rydén: IT University of Copenhagen
Omar El Sawy: Marshall School of Business, University of Southern California

A chapter in Platforms and Artificial Intelligence, 2022, pp 225-243 from Springer

Abstract: Abstract Real-time management of Artificial Intelligence (AI) becomes a central enabling function for coping with the rapid market changes and increasing demands of stakeholders. But diverse sensing of real time makes it tricky for enterprises to adjust business processes towards a real-time-based era and build the temporal conditions needed for deploying AI in a humanistic manner. This chapter, therefore, introduces the concept of Fast and Flow in an AI engagement context. Fast and Flow encompasses two ideas: one considers time as a monetary asset that helps to increase value; the second does not seek to control time and does not define it on the clock scale, rather, it describes the sense of presence. By introducing the components of Fast and Flow interaction, we provide a cognitive psychology dimension to the management of AI and explore the balancing of Fast and Flow in three possible AI scenarios. The first scenario is “business as usual,” but faster and more complex; the second scenario is more focused on consumers and is based on an ideal combination of AI and Fast and Flow management; in the third scenario, there is an overflow of technology—AI is too fast, and people are unable to control it. Finally, we are asking what Fast and Flow management can do for a humanistic deployment of AI in enterprises and societies.

Keywords: Real-time management; Fast and Flow approach; Humanistic implementation of AI (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-030-90192-9_11

Ordering information: This item can be ordered from
http://www.springer.com/9783030901929

DOI: 10.1007/978-3-030-90192-9_11

Access Statistics for this chapter

More chapters in Progress in IS from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().