Charles Binkley

Charles Binkley

orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 July 2022 in IEEE Transactions on Technology and Society
Verified
Journal Article
Open access
HAHimanshi Allahabadi
Himanshi Allahabadi
JAJulia Amann
Julia Amann
IBIsabelle Balot
Isabelle Balot
ABAndrea Beretta
Andrea Beretta
CBCharles Binkley
Charles Binkley
RZRoberto V. Zicari
Roberto V. Zicari
The paper’s main contributions are twofold: to demonstrate how to apply the general European Union’s High-Level Expert Group’s (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare; and to investigate the research question of what does “trustworthy AI” mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient’s lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia (Italy) since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection, uses socio-technical scenarios to identify ethical, technical and domain-specific issues in the use of the AI system in the context of the pandemic.

6 October 2022 in New England Journal of Medicine
Verified
Journal Article
Open access
CBCharles Binkley
Charles Binkley
JRJoel Michael Reynolds
Joel Michael Reynolds
ASAndrew G. Shuman
Andrew G. Shuman
Qualitative evidence on the relationship between quality of life and disabilities suggests that subjective judgments regarding other people’s QoL are wrong more often than not.

3 October 2023 in The American Journal of Bioethics
Verified
Journal Article
Closed access
CBCharles Binkley
Charles Binkley
BPBryan C. Pilkington
Bryan C. Pilkington

2 May 2023 in The American Journal of Bioethics
Verified
Journal Article
Closed access
CBCharles Binkley
Charles Binkley
BPBryan Pilkington
Bryan Pilkington
We applaud Sedlakova and Trachsel’s work and their description of conversational artificial intelligence (CAI) as possessing a hybrid nature with features of both a tool and an agent (Sedlakova and...

17 June 2025 in npj Digital Medicine
Verified
Journal Article
Open access
PDF file
CBCharles Binkley
Charles Binkley
DBDavid Bouslov
David Bouslov
AZAli Zaidi
Ali Zaidi
LKLauren Kaye
Lauren Kaye
RWRalph Whalen
Ralph Whalen
JAJose Azar
Jose Azar
The success of AI solutions in health systems depends on governance from use case inception through deployment and auditing. This proposed early pipeline governance framework for vendor AI solutions highlights a four-pronged approach: strategic alignment, executive sponsorship, impact and value case assessment, and risk assessment. Each component can be scaled to health systems of any size and the risk and impact assessments can take place simultaneously or sequentially.

28 October 2021 in The American Journal of Bioethics
Verified
Journal Article
Closed access
JRJoel Michael Reynolds
Joel Michael Reynolds
CBCharles Binkley
Charles Binkley
ASAndrew G. Shuman
Andrew G. Shuman
Wilkinson (2021) argues that the use of frailty scores in ICU triage does not necessarily involve discrimination on the basis of disability. In support of this argument, he claims, “it is not the d...