BMC Medical Ethics· 2021Q1
Privacy and artificial intelligence: challenges for protecting health information in a new era
- 932citations
- Q1SCImago
- 2021year
Short summary
Private companies implementing healthcare AI may compromise patient privacy due to inadequate safeguards and the risk of re-identification of anonymized data by new algorithms.
AI-generated from the title and abstract; the full text is not read.
Key points
- Private entities increasingly control healthcare AI, leading to concerns about patient data access, use, and protection.
- Recent public-private AI partnerships have demonstrated inadequate privacy safeguards.
- New AI algorithms can re-identify previously anonymized patient health data, increasing breach risks.
- Regulation is lagging behind AI technology, highlighting the need for stronger patient agency, consent, and anonymization methods.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. BMC Medical Ethics, 2021 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Health Informatics
Health InformaticsMedicine