Paper Number
2605
Paper Type
Short
Abstract
Since its inception, artificial intelligence has been described and studied in relation to the intelligence we know best – our own human intelligence. The hardening of such a human centric conceptual framing reduces the ability of scholars to look beyond taken-for granted anthropomorphic assumptions. In this short paper, we question in what manner technologies built by humans can exhibit intelligence – ostensibly Artificial Intelligence. We reconstruct the phenomenon as artificial ‘Intelligence’ through a list of five frames of ‘intelligence as we do not know it’: i) a human-like comprehension, ii) a model, iii) a palimpsest, iv) a probabilistic outcome, and v) a mutable accomplishment. We describe these conceptual framings and discuss their implications for information systems (IS) research. These novel conceptualizations provide the initial stages to overturn the dominance of human-centric assumptions about artificial Intelligence and further construct a phenomenon to explore artificial Intelligences as we do not know them.
Recommended Citation
Sullivan, Rick; Struijk, Mylène; and Hovorka, Dirk, "Seeking intelligence as we do not know it: A site of phenomenon (re)construction" (2024). ICIS 2024 Proceedings. 14.
https://aisel.aisnet.org/icis2024/general_is/general_is/14
Seeking intelligence as we do not know it: A site of phenomenon (re)construction
Since its inception, artificial intelligence has been described and studied in relation to the intelligence we know best – our own human intelligence. The hardening of such a human centric conceptual framing reduces the ability of scholars to look beyond taken-for granted anthropomorphic assumptions. In this short paper, we question in what manner technologies built by humans can exhibit intelligence – ostensibly Artificial Intelligence. We reconstruct the phenomenon as artificial ‘Intelligence’ through a list of five frames of ‘intelligence as we do not know it’: i) a human-like comprehension, ii) a model, iii) a palimpsest, iv) a probabilistic outcome, and v) a mutable accomplishment. We describe these conceptual framings and discuss their implications for information systems (IS) research. These novel conceptualizations provide the initial stages to overturn the dominance of human-centric assumptions about artificial Intelligence and further construct a phenomenon to explore artificial Intelligences as we do not know them.
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