Ghost in the Machine: Theorizing data knowledge in the Age of Intelligent Technologies
(2023) Forty-Fourth International Conference on Information Systems p.1-9- Abstract
- AI technologies have led to new ways of thinking about data, knowledge, and organizations. Despite the arguments that data speak for themselves, the era of datafication demands revisiting data and knowledge and reflecting on new ways of theorizing. Considering that working with data is important for most employees, there is a need to investigate how the knowing of data can be achieved. In this paper, we move beyond the factual view of data and the hierarchical view of data and knowledge, to introduce data knowledge as a new type of knowledge. We present a first step towards a theory of explanation of what is data knowledge in today ́s organizations. To investigate this, we apply an etymological lens, and review systematically the IS... (More)
- AI technologies have led to new ways of thinking about data, knowledge, and organizations. Despite the arguments that data speak for themselves, the era of datafication demands revisiting data and knowledge and reflecting on new ways of theorizing. Considering that working with data is important for most employees, there is a need to investigate how the knowing of data can be achieved. In this paper, we move beyond the factual view of data and the hierarchical view of data and knowledge, to introduce data knowledge as a new type of knowledge. We present a first step towards a theory of explanation of what is data knowledge in today ́s organizations. To investigate this, we apply an etymological lens, and review systematically the IS literature. Our preliminary findings demonstrate unveiling data, balancing between intuition and data, acknowledging external and internal capabilities, and realizing data, as the four main concepts of data knowledge. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/feb43802-416a-4300-a4a0-e246995c4054
- author
- Koukouvinou, Panagiota ; Ademaj, Gemza LU ; Sarker, Saonee LU and Holmström, Jonny
- organization
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Data, Knowledge, Theorizing, Etymology, systematic review
- host publication
- ICIS 2023 Proceedings. 22 : AI in Business and Society - AI in Business and Society
- pages
- 1 - 9
- publisher
- AIS Electronic Library (AISeL)
- conference name
- Forty-Fourth International Conference on Information Systems
- conference location
- Hyderabad, India
- conference dates
- 2023-12-10 - 2024-03-13
- external identifiers
-
- scopus:85192532950
- ISBN
- 978-1-958200-07-0
- language
- English
- LU publication?
- yes
- id
- feb43802-416a-4300-a4a0-e246995c4054
- alternative location
- https://aisel.aisnet.org/icis2023/aiinbus/aiinbus/22
- date added to LUP
- 2024-03-26 10:46:58
- date last changed
- 2024-05-30 15:02:03
@inproceedings{feb43802-416a-4300-a4a0-e246995c4054, abstract = {{AI technologies have led to new ways of thinking about data, knowledge, and organizations. Despite the arguments that data speak for themselves, the era of datafication demands revisiting data and knowledge and reflecting on new ways of theorizing. Considering that working with data is important for most employees, there is a need to investigate how the knowing of data can be achieved. In this paper, we move beyond the factual view of data and the hierarchical view of data and knowledge, to introduce data knowledge as a new type of knowledge. We present a first step towards a theory of explanation of what is data knowledge in today ́s organizations. To investigate this, we apply an etymological lens, and review systematically the IS literature. Our preliminary findings demonstrate unveiling data, balancing between intuition and data, acknowledging external and internal capabilities, and realizing data, as the four main concepts of data knowledge.}}, author = {{Koukouvinou, Panagiota and Ademaj, Gemza and Sarker, Saonee and Holmström, Jonny}}, booktitle = {{ICIS 2023 Proceedings. 22 : AI in Business and Society}}, isbn = {{978-1-958200-07-0}}, keywords = {{Data; Knowledge; Theorizing; Etymology; systematic review}}, language = {{eng}}, pages = {{1--9}}, publisher = {{AIS Electronic Library (AISeL)}}, title = {{Ghost in the Machine: Theorizing data knowledge in the Age of Intelligent Technologies}}, url = {{https://aisel.aisnet.org/icis2023/aiinbus/aiinbus/22}}, year = {{2023}}, }