Privacy and artificial intelligence: challenges for protecting health information in a new era
- PMID: 34525993
- PMCID: PMC8442400
- DOI: 10.1186/s12910-021-00687-3
Privacy and artificial intelligence: challenges for protecting health information in a new era
Abstract
Background: Advances in healthcare artificial intelligence (AI) are occurring rapidly and there is a growing discussion about managing its development. Many AI technologies end up owned and controlled by private entities. The nature of the implementation of AI could mean such corporations, clinics and public bodies will have a greater than typical role in obtaining, utilizing and protecting patient health information. This raises privacy issues relating to implementation and data security.
Main body: The first set of concerns includes access, use and control of patient data in private hands. Some recent public-private partnerships for implementing AI have resulted in poor protection of privacy. As such, there have been calls for greater systemic oversight of big data health research. Appropriate safeguards must be in place to maintain privacy and patient agency. Private custodians of data can be impacted by competing goals and should be structurally encouraged to ensure data protection and to deter alternative use thereof. Another set of concerns relates to the external risk of privacy breaches through AI-driven methods. The ability to deidentify or anonymize patient health data may be compromised or even nullified in light of new algorithms that have successfully reidentified such data. This could increase the risk to patient data under private custodianship.
Conclusions: We are currently in a familiar situation in which regulation and oversight risk falling behind the technologies they govern. Regulation should emphasize patient agency and consent, and should encourage increasingly sophisticated methods of data anonymization and protection.
Keywords: Artificial intelligence; Bioethics; Health law; Privacy.
© 2021. The Author(s).
Conflict of interest statement
The author declares that in addition to his primary academic position he has a concurrent position as the Privacy Officer of immunization software company CANImmunize.
References
-
- Radiological Society of North America. Artificial intelligence shows potential for triaging chest X-rays. 2019. https://www.rsna.org/en/news/2019/January/AI-for-chest-x-rays. Accessed 15 Mar 2021.
-
- European Society of Cardiology. Machine learning overtakes humans in predicting death or heart attack. EurekAlert! 2019. https://eurekalert.org/pub_releases/2019-05/esoc-mlo050719.php. Accessed 15 Mar 2021.
-
- Armitage H. Artificial intelligence rivals radiologists in screening X-rays for certain diseases. Stanford Medicine News Center. 2018. https://med.stanford.edu/news/all-news/2018/11/ai-outperformed-radiologi.... Accessed 15 Mar 2021.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Research Materials
