Trust, but Verify: Informed Consent, AI Technologies, and Public Health Emergencies

Abstract

To use technology or engage with research or medical treatment typically requires user consent: agreeing to terms of use with technology or services, or providing informed consent for research participation, for clinical trials and medical intervention, or as one legal basis for processing personal data. Introducing AI technologies, where explainability and trustworthiness are focus items for both government guidelines and responsible technologists, imposes additional challenges. Understanding enough of the technology to be able to make an informed decision, or consent, is essential but involves an acceptance of uncertain outcomes. Further, the contribution of AI-enabled technologies not least during the COVID-19 pandemic raises ethical concerns about the governance associated with their development and deployment. Using three typical scenarios—contact tracing, big data analytics and research during public emergencies—this paper explores a trust-based alternative to consent. Unlike existing consent-based mechanisms, this approach sees consent as a typical behavioural response to perceived contextual characteristics. Decisions to engage derive from the assumption that all relevant stakeholders including research participants will negotiate on an ongoing basis. Accepting dynamic negotiation between the main stakeholders as proposed here introduces a specifically socio–psychological perspective into the debate about human responses to artificial intelligence. This trust-based consent process leads to a set of recommendations for the ethical use of advanced technologies as well as for the ethical review of applied research projects.

The Reconstruction of Human Fingerprints From High-Resolution Computed Tomography Data: Feasibility Study and Associated Ethical Issues

“…Our study complements previous imaging studies that assessed the ethical implication associated with the risk of reidentification of the participants using MRI data [ 2 ] and highlights the risks of modern high-resolution imaging modalities, such as x-ray μCT, accidentally producing identifiable information. We argue that data sets containing high-resolution CT images of the human hands should be considered “sensitive” and thus handled and shared with appropriate care, as data subjects and imaging scientists may not be able to identify a priori all implications of further processing [ 9 ]. Relevant bodies (eg, institutional ethics committees or data protection committees) should consider this aspect of high-resolution CTs when reviewing research or clinical imaging protocols and make their recommendations according to the currently applicable law and local code of practice.…”

Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk

“…Pickering therefore challenges the use of informed consent (Pickering, 2021 ). He develops an alternative conception of “trust‐based consent” starting from Eyal's observation that informed consent does not automatically promote trust in medical care (Pickering, 2021 , p. 10; drawing on Eyal, 2014 ).…”

“…Pickering therefore challenges the use of informed consent (Pickering, 2021 ). He develops an alternative conception of “trust‐based consent” starting from Eyal's observation that informed consent does not automatically promote trust in medical care (Pickering, 2021 , p. 10; drawing on Eyal, 2014 ). Instead, Pickering views trust as a “constant negotiation” between a trustor's willingness to trust and the trustee's display of indicators of trustworthiness (Pickering, 2021 , p. 11).…”

“…He develops an alternative conception of “trust‐based consent” starting from Eyal's observation that informed consent does not automatically promote trust in medical care (Pickering, 2021 , p. 10; drawing on Eyal, 2014 ). Instead, Pickering views trust as a “constant negotiation” between a trustor's willingness to trust and the trustee's display of indicators of trustworthiness (Pickering, 2021 , p. 11). Drawing on work in the domain of management and organizational studies, Pickering offers a behavioral approach to trust and consent: trustees must find ways to continuously demonstrate their trustworthiness indicators to the trustor (Pickering, 2021 , pp.…”

Ethical Considerations in Artificial Intelligence: A Comprehensive Disccusion from the Perspective of Computer Vision

“…Upholding individual autonomy is a core principle in ethical computer vision practices. It means respecting people's right to control their own information and make decisions about how their data is used [6]. In scenarios where facial recognition or image analysis is involved, obtaining informed consent from individuals is not just important but essential.…”