Dr. Daniel Tigard

Wissenschaftlicher Mitarbeiter, Lehrstuhl für Ethik der Medizin und Gesundheitstechnologien | Technische Universität München

Daniel Tigard is a Senior Research Associate in the Institute for History and Ethics of Medicine at the Technical University of Munich. His published work addresses topics in ethical theory, such as moral conflicts, moral agency and responsibility, with applications to issues in bioethics. More recently, he works on ethical issues in emerging technology, particularly AI and robotics.

Publikationen

  • Breuer, Svenja; Braun, Maximilian; Tigard, Daniel; Buyx, Alena; Müller, Ruth (2023)

    How Engineers’ Imaginaries of Healthcare Shape Design and User Engagement: A Case Study of a Robotics Initiative for Geriatric Healthcare AI Applications

    Zeitschriftenaufsatz
    Projekt: RR-AI
  • Braun, Maximilian; Breuer, Svenja; Tigard, Daniel; Müller, Ruth (2022)

    Embedded Ethics and Social Sciences in HRI Research: Scenarios and Subjectivities

    Konferenzpapier
    Projekt: RR-AI
  • Braun, Maximilian; Breuer, Svenja; Tigard, Daniel; Müller, Ruth (2022)

    Embedded Ethics and Social Sciences

    Konferenzpapier
    Projekt: RR-AI
  • Breuer, Svenja; Braun, Maximilian; Ritt, Konstantin; Tigard, Daniel (2021)

    Embedding Ethics and Social Science Into Telemedicine Research, Development, and Implementation

    Konferenzpapier
    Projekt: RR-AI
  • Tigard, Daniel; Ritt, Konstantin; Breuer, Svenja; Braun, Maximilian (2021)

    Embedding ethics into every step of emerging technologies

    Internetdokument
    Projekt: RR-AI
  • Fiske, Amelia; Tigard, Daniel; Müller, Ruth; Haddadin, Sami; Buyx, Alena; McLennan, Stuart (2020)

    Embedded Ethics Could Help Implement the Pipeline Model Framework for Machine Learning Healthcare Applications.

    Zeitschriftenaufsatz
    Projekt: RR-AI
  • Braun, Maximilian; Breuer, Svenja; Tigard, Daniel; Upperton, T.

    Responsible Robotics. Die Rolle von Robotik im Gesundheitswesen

    Graue Literatur / Bericht / Report
    Projekt: RR-AI