Conference paper | Konferenzbeitrag

Technological Opacity of Machine Learning in Healthcare

Recently, a host of propositions for guidelines for the ethical development and use of artificial intelligence (AI) has been published. This body of work contains timely contributions for sensitizing developers to the ethical and societal implications of their work. However, a sustained embedding of ethics in largely algorithm-based technology development, research and studies requires a precise framing of the origins of the new vulnerabilities created. Recently, scholars have been referring to ethics associated with technology that is in some way “opaque” to at least part of its associated stakeholders. This “opacity” can take several forms which will be discussed in this paper. There are various ways in which such an opacity can create vulnerabilities and, hence, relevant ethical, societal, epistemic and regulatory challenges. This paper provides a non-exhaustive list of examples in healthcare that call for educational resources and consideration in development processes that try to reveal and counter these opacities.

Technological Opacity of Machine Learning in Healthcare

Urheber*in: Herzog, Christian

Namensnennung 4.0 International

0
/
0

Umfang
Seite(n): 9
Sprache
Englisch
Anmerkungen
Status: Erstveröffentlichung; begutachtet (peer reviewed)
2. Weizenbaum Conference. Berlin, 2019

Erschienen in
Proceedings of the Weizenbaum Conference 2019 "Challenges of Digital Inequality - Digital Education, Digital Work, Digital Life"

Thema
Technik, Technologie
Technikfolgenabschätzung
Automatisierung
künstliche Intelligenz
Gesundheitswesen
Ethik
Technikfolgen

Ereignis
Geistige Schöpfung
(wer)
Herzog, Christian
Ereignis
Veröffentlichung
(wo)
Deutschland, Berlin
(wann)
2019

DOI
Rechteinformation
GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln
Letzte Aktualisierung
21.06.2024, 16:27 MESZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Konferenzbeitrag

Beteiligte

  • Herzog, Christian

Entstanden

  • 2019

Ähnliche Objekte (12)