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.
- 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
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