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6. AI-produced certainties in health care: current and future challenges

Author

Tretter, Max, Ott, Tabea, and Dabrock, Peter

Abstract

Since uncertainty is a major challenge in medicine and bears the risk of causing incorrect diagnoses and harmful treatment, there are many efforts to tackle it. For some time, AI technologies have been increasingly implemented in medicine and used to reduce medical uncertainties. What initially seems desirable, however, poses challenges. We use a multimethod approach that combines philosophical inquiry, conceptual analysis, and ethical considerations to identify key challenges that arise when AI is used for medical certainty purposes. We identify several challenges. Where AI is used to reduce medical uncertainties, it is likely to result in (a) patients being stripped down to their measurable data points, and being made disambiguous. Additionally, the widespread use of AI technologies in health care bears the risk of (b) human physicians being pushed out of the medical decision-making process, and patient participation being more and more limited. Further, the successful use of AI requires extensive and invasive monitoring of patients, which raises (c) questions about surveillance as well as privacy and security issues. We outline these several challenges and show that they are immediate consequences of AI-driven security efforts. If not addressed, they could entail unfavorable consequences. We contend that diminishing medical uncertainties through AI involves a tradeoff. The advantages, including enhanced precision, personalization, and overall improvement in medicine, are accompanied by several novel challenges. This paper addresses them and gives suggestions about how to use AI for certainty purposes without causing harm to patients.

Published
2024
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7. Transparent human – (non-) transparent technology? The Janus-faced call for transparency in AI-based health care technologies

Author

Ott, Tabea and Dabrock, Peter

Subjects
Genetics, Molecular Medicine, ddc:610, Genetics (clinical)
Abstract

The use of Artificial Intelligence and Big Data in health care opens up new opportunities for the measurement of the human. Their application aims not only at gathering more and better data points but also at doing it less invasive. With this change in health care towards its extension to almost all areas of life and its increasing invisibility and opacity, new questions of transparency arise. While the complex human-machine interactions involved in deploying and using AI tend to become non-transparent, the use of these technologies makes the patient seemingly transparent. Papers on the ethical implementation of AI plead for transparency but neglect the factor of the “transparent patient” as intertwined with AI. Transparency in this regard appears to be Janus-faced: The precondition for receiving help - e.g., treatment advice regarding the own health - is to become transparent for the digitized health care system. That is, for instance, to donate data and become visible to the AI and its operators. The paper reflects on this entanglement of transparent patients and (non-) transparent technology. It argues that transparency regarding both AI and humans is not an ethical principle per se but an infraethical concept. Further, it is no sufficient basis for avoiding harm and human dignity violations. Rather, transparency must be enriched by intelligibility following Judith Butler’s use of the term. Intelligibility is understood as an epistemological presupposition for recognition and the ensuing humane treatment. Finally, the paper highlights ways to testify intelligibility in dealing with AI in health care ex ante, ex post, and continuously.

Published
2022

8. Vulnerable Integrity - Theological-Ethical Reflections on Human Integrity and Integrity Violations.

Author

Ott, Tabea and Dabrock, Peter

Subjects
*THEOLOGY, *MEDICAL technology, *DIGITAL twins, *SOCIAL support, *HUMAN beings
Abstract

This paper presents a social-theologically informed interpretation of the term integrity, as it occurs in fundamental law. It explores the manifestations of integrity violations and proceeds to draw an inference: an integrity violation can directly emanate from a misconception regarding integrity itself, as well as the implementation of protective measures that follow it. Integrity in its wholeness dimension is understood as open-endedness and non-seclusion rather than as a substantial, clearly definable characteristic of a person. This openendedness and non-seclusion results from the relational constitution of an individual. Consequently, it follows that a violation of integrity occurs when the open-endedness and non-seclusion of a person and their relational Becoming is hindered. The new definition of integrity is particularly important when it comes to the governance of new health technologies, especially Digital Twins that can become representatives of a person. Human integrity is non-violated only when it is understood as open to relational Becoming and this Becoming shows its expression in the mutual enabling and support of self-articulation. [ABSTRACT FROM AUTHOR]

Published
2023
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10. Doing Gender – Ästhetische Inszenierungen auf der Schwelle

Author

Ott, Tabea Laura Aimée

Subjects
Transgender, Gender, Kunst, Sociology (General), Crossdressing, Social history and conditions. Social problems. Social reform, Kultur, HN1-995, HM401-1281
Abstract

Gemeinsamer Untersuchungsgegenstand aller Beiträge des Sammelbandes ist die ästhetische Inszenierung des Spiels mit Geschlecht entlang von zentralen Begrifflichkeiten wie Schwelle, Grenze und Fluidität. Der Band geht auf eine Ringvorlesung der Universität Koblenz zurück, zu der Wissenschaftler:innen verschiedener Disziplinen zum gemeinsamen Nachdenken über das Phänomen Transgender und Crossdressing eingeladen waren. Anne-Berenike Rothstein präsentiert in dem daraus hervorgegangenen Sammelband ein breites, chronologisch orientiertes Passepartout des bereits in die Antike zurückreichenden Phänomenbereichs der Auflösung und Überschreitung von Geschlechtergrenzen in Theater, Oper, Literatur, Film, bildenden Künsten und Popkultur. Durch die den Beiträgen zugrundeliegende, jeweils unterschiedliche Definition von Transgender und Crossdressing entsteht der Eindruck einer eklektischen Zusammenschau, in dem die Spannbreite eines kulturellen „Rereadings“ von Genderinszenierungen deutlich wird., Open Gender Journal, Vol. 5 (2021): Open Gender Journal

Published
2021

15. Wissenschaftliches Arbeiten im Medizinstudium aus Sicht der Studierenden

Author

Ratte, Antonius, Drees, Simon, and Schmidt-Ott, Tabea

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Fragestellung/Einleitung: Die Vermittlung von wissenschaftlichen Kompetenzen im Medizinstudium wird aktuell intensiv diskutiert [ref:1], [ref:2], [ref:3]. Ziel der vorliegenden Befragung war die Erfassung der Sicht der Medizinstudierenden auf dieses Thema. Dabei betrachteten[zum vollständigen Text gelangen Sie über die oben angegebene URL], Gemeinsame Jahrestagung der Gesellschaft für Medizinische Ausbildung (GMA) und des Arbeitskreises zur Weiterentwicklung der Lehre in der Zahnmedizin (AKWLZ)

Published
2015

17. A Review and Tutorial on Machine Learning-Enabled Radar-Based Biomedical Monitoring.

Author

Krauss D, Engel L, Ott T, Braunig J, Richer R, Gambietz M, Albrecht N, Hille EM, Ullmann I, Braun M, Dabrock P, Kolpin A, Koelewijn AD, Eskofier BM, and Vossiek M

Abstract

Radio detection and ranging-based (radar) sensing offers unique opportunities for biomedical monitoring and can help overcome the limitations of currently established solutions. Due to its contactless and unobtrusive measurement principle, it can facilitate the longitudinal recording of human physiology and can help to bridge the gap from laboratory to real-world assessments. However, radar sensors typically yield complex and multidimensional data that are hard to interpret without domain expertise. Machine learning (ML) algorithms can be trained to extract meaningful information from radar data for medical experts, enhancing not only diagnostic capabilities but also contributing to advancements in disease prevention and treatment. However, until now, the two aspects of radar-based data acquisition and ML-based data processing have mostly been addressed individually and not as part of a holistic and end-to-end data analysis pipeline. For this reason, we present a tutorial on radar-based ML applications for biomedical monitoring that equally emphasizes both dimensions. We highlight the fundamentals of radar and ML theory, data acquisition and representation and outline categories of clinical relevance. Since the contactless and unobtrusive nature of radar-based sensing also raises novel ethical concerns regarding biomedical monitoring, we additionally present a discussion that carefully addresses the ethical aspects of this novel technology, particularly regarding data privacy, ownership, and potential biases in ML algorithms., Competing Interests: The authors declare that they have no commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 The Authors.)

Published
2024
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