Legitimate interest is one of the six lawful bases under the GDPR that businesses can use to process personal data. It's the most flexible basis but comes with an added responsibility to protect the rights and interests of data subjects. This basis is often appropriate when data is used in ways that individuals would reasonably expect and with minimal privacy impact.
Limitations and Considerations
While legitimate interest offers flexibility, it's not a one-size-fits-all solution. It requires a detailed and documented assessment, considering the nature of the data, the processing's impact, and the individual's reasonable expectations. Sensitive information (special categories of personal data), such as health information, demands a more compelling justification for processing under legitimate interests.
When is Legitimate Interest Assessment (LIA) Required?
LIA is required when a business processes personal data based on legitimate interests. This basis is often considered when explicit consent is not feasible or appropriate. It's particularly relevant in scenarios like fraud prevention, network security, or indicating potential criminal acts.
Components of a Legitimate Interest Assessment
A legitimate interest assessment involves a three-part test:
Purpose test: identifying the legitimate interest behind the data processing.
Necessity test: assessing if the processing is essential for the purpose identified.
Balancing test: weighing the business' interests against the individual's interests and rights.
Practical Recommendations
- Document your LIAs: maintain a clear record of the LIA process and decisions, as this helps in demonstrating compliance with the GDPR.
- Be specific: clearly define the purpose of data processing. Vague or broad purposes make it challenging to justify the necessity and balance interests effectively.
- Evaluate alternatives: consider if the same objectives can be achieved with less data or through less intrusive means.
- Regular reviews: reassess the LIA if there are significant changes in data processing or its context.
- Transparency: be open about your data processing activities and the basis for them, ensuring transparency with data subjects.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
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