2024
Hummel, Patrik; Braun, Matthias; Bishoff, Serena; Samhammer, David; Sietz, Katharina; Fasching, Peter A.; Dabrock, Peter
Perspectives of patients and clinicians on big data and AI in health: a comparative empirical investigation Journal Article
In: AI & SOCIETY, 2024, ISSN: 1435-5655.
Abstract | Links | BibTeX | Tags: AI, Big data, Digital health
@article{nokey,
title = {Perspectives of patients and clinicians on big data and AI in health: a comparative empirical investigation},
author = {Patrik Hummel and Matthias Braun and Serena Bishoff and David Samhammer and Katharina Sietz and Peter A. Fasching and Peter Dabrock},
url = {https://www.esdit.nl/perspectives-of-patients-and-clinicians-on-big-data-and-ai-in-health/},
doi = {10.1007/s00146-023-01825-8},
issn = {1435-5655},
year = {2024},
date = {2024-01-07},
urldate = {2024-01-07},
journal = {AI & SOCIETY},
abstract = {Big data and AI applications now play a major role in many health contexts. Much research has already been conducted on ethical and social challenges associated with these technologies. Likewise, there are already some studies that investigate empirically which values and attitudes play a role in connection with their design and implementation. What is still in its infancy, however, is the comparative investigation of the perspectives of different stakeholders.},
keywords = {AI, Big data, Digital health},
pubstate = {published},
tppubtype = {article}
}
Big data and AI applications now play a major role in many health contexts. Much research has already been conducted on ethical and social challenges associated with these technologies. Likewise, there are already some studies that investigate empirically which values and attitudes play a role in connection with their design and implementation. What is still in its infancy, however, is the comparative investigation of the perspectives of different stakeholders.
2023
Aizenberg, Evgeni; Dennis, Matthew; van den Hoven, Jeroen
Examining the assumptions of AI hiring assessments and their impact on job seekers' autonomy over self-representation Journal Article
In: AI & Society, 2023.
Abstract | Links | BibTeX | Tags: AI, Algorithm, Authonomy, Dignity, Hiring, Self-representation
@article{nokey,
title = {Examining the assumptions of AI hiring assessments and their impact on job seekers' autonomy over self-representation},
author = {Evgeni Aizenberg and Matthew Dennis and Jeroen van den Hoven},
url = {https://www.esdit.nl/examining-the-assumptions-of-ai/},
doi = {https://doi.org/10.1007/s00146-023-01783-1},
year = {2023},
date = {2023-10-21},
urldate = {2023-10-21},
journal = {AI & Society},
abstract = {In this paper, we examine the epistemological and ontological assumptions algorithmic hiring assessments make about job seekers’ attributes (e.g., competencies, skills, abilities) and the ethical implications of these assumptions. Given that both traditional psychometric hiring assessments and algorithmic assessments share a common set of underlying assumptions from the psychometric paradigm, we turn to literature that has examined the merits and limitations of these assumptions, gathering insights across multiple disciplines and several decades. Our exploration leads us to conclude that algorithmic hiring assessments are incompatible with attributes whose meanings are context-dependent and socially constructed. Such attributes call instead for assessment paradigms that offer space for negotiation of meanings between the job seeker and the employer. We argue that in addition to questioning the validity of algorithmic hiring assessments, this raises an often overlooked ethical impact on job seekers’ autonomy over self-representation: their ability to directly represent their identity, lived experiences, and aspirations. Infringement on this autonomy constitutes an infringement on job seekers’ dignity. We suggest beginning to address these issues through epistemological and ethical reflection regarding the choice of assessment paradigm, the means to implement it, and the ethical impacts of these choices. This entails a transdisciplinary effort that would involve job seekers, hiring managers, recruiters, and other professionals and researchers. Combined with a socio-technical design perspective, this may help generate new ideas regarding appropriate roles for human-to-human and human–technology interactions in the hiring process.},
keywords = {AI, Algorithm, Authonomy, Dignity, Hiring, Self-representation},
pubstate = {published},
tppubtype = {article}
}
In this paper, we examine the epistemological and ontological assumptions algorithmic hiring assessments make about job seekers’ attributes (e.g., competencies, skills, abilities) and the ethical implications of these assumptions. Given that both traditional psychometric hiring assessments and algorithmic assessments share a common set of underlying assumptions from the psychometric paradigm, we turn to literature that has examined the merits and limitations of these assumptions, gathering insights across multiple disciplines and several decades. Our exploration leads us to conclude that algorithmic hiring assessments are incompatible with attributes whose meanings are context-dependent and socially constructed. Such attributes call instead for assessment paradigms that offer space for negotiation of meanings between the job seeker and the employer. We argue that in addition to questioning the validity of algorithmic hiring assessments, this raises an often overlooked ethical impact on job seekers’ autonomy over self-representation: their ability to directly represent their identity, lived experiences, and aspirations. Infringement on this autonomy constitutes an infringement on job seekers’ dignity. We suggest beginning to address these issues through epistemological and ethical reflection regarding the choice of assessment paradigm, the means to implement it, and the ethical impacts of these choices. This entails a transdisciplinary effort that would involve job seekers, hiring managers, recruiters, and other professionals and researchers. Combined with a socio-technical design perspective, this may help generate new ideas regarding appropriate roles for human-to-human and human–technology interactions in the hiring process.