ITM Web Conf.
Volume 62, 2024International Conference on Exploring Service Science (IESS 2.4)
|Number of page(s)
|Smart Healthcare & Pharmacy
|01 February 2024
Intelligence Augmentation and capability co-elevation in healthcare enabled by reasoned transparency
University of Salerno, Political and Communication Sciences Department, 84084 Fisciano (SA), Italy
* Corresponding author: firstname.lastname@example.org
Artificial intelligence (AI) systems in healthcare can have a significant impact on the performance of the actors involved, encouraging, for example, increasingly early diagnoses, personalized treatments and more accurate data management and processing techniques. However, these results may depend on increasingly profitable human-machine interactions, Intelligence Augmentation, and potential in terms of capability co-elevation. Starting from this assumption, this study aims to understand which can be the Intelligence Augmentation and capability co- elevation driver in healthcare. This conceptual paper has been carried out with the conceptual goal of delineating, so, to address the research question, a deductive reasoning approach was applied and the methodological approach followed has been based on the description of the theoretical background, definition of evidence from an illustrative case, Livongo Health, addressed by analyzing secondary data extrapolated from the website contents, and development conclusions. From the illustration case, insights have been outlined to understand how to achieve the objectives of Intelligence Augmentation and capability co-elevation: it has been observed how the reasoned transparency in AI systems can be understood as an enabling factor.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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