Diabetes and Driving: How Predictive Technologies Will Alter Ethical and Legal Responsibilities

In 2023, a 67-year-old man with long-standing type 1 diabetes experienced a severe hypoglycemic episode and drove into an outdoor dining area in Victoria, Australia, killing 5 people and injuring several others. Although the charges against the driver were dismissed, future cases involving new continuous glucose monitors enhanced with artificial intelligence that allow users to anticipate impairment before it occurs may have different outcomes. These biopredictive technologies transform hypoglycemia from a background risk into a more foreseeable event. This generates new conditional obligations to act on predictive warnings and, in some cases, obligations on those with higher risks to acquire such technologies. Furthermore, these individual responsibilities can generate corresponding state obligations to subsidize access and update licensing frameworks, ensuring safety without exacerbating inequity or stigma.

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Publication Details

Journal
Journal of Diabetes Science and Technology
Published
2026-09-06
DOI
https://doi.org/10.1177/19322968261468763
Primary Topic
Diabetes Management and Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Diabetes and Driving: How Predictive Technologies Will Alter Ethical and Legal Responsibilities

Danièle Pacaud, Fergus Cameron, Jamie Walvisch, Tasmia Hai et al.
Journal of Diabetes Science and Technology
Diabetes Management and Research
article

Diabetes and Driving: How Predictive Technologies Will Alter Ethical and Legal Responsibilities

Danièle Pacaud, Fergus Cameron, Jamie Walvisch, Tasmia Hai, Sinead Prince, Julian Savulescu, Matthew L. Baum
article en

Abstract

In 2023, a 67-year-old man with long-standing type 1 diabetes experienced a severe hypoglycemic episode and drove into an outdoor dining area in Victoria, Australia, killing 5 people and injuring several others. Although the charges against the driver were dismissed, future cases involving new continuous glucose monitors enhanced with artificial intelligence that allow users to anticipate impairment before it occurs may have different outcomes. These biopredictive technologies transform hypoglycemia from a background risk into a more foreseeable event. This generates new conditional obligations to act on predictive warnings and, in some cases, obligations on those with higher risks to acquire such technologies. Furthermore, these individual responsibilities can generate corresponding state obligations to subsidize access and update licensing frameworks, ensuring safety without exacerbating inequity or stigma.

Journal of Diabetes Science and Technology
Brigham and Women's Hospital (US), Royal Children's Hospital (AU), Harvard University (US), National University of Singapore (SG), University of Calgary (CA), The University of Western Australia (AU), University of Oxford (GB), Children's Hospital Research Institute of Manitoba (CA), Murdoch Children's Research Institute (AU), University of Manitoba (CA), McGill University (CA)
Wellcome Trust, National University of Singapore, National Research Foundation Singapore
Peace, Justice and strong institutions
Openalex Percentile: Top 11%
Diabetes Management and Research
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