Government’s use of Algorithms
In October 2018 the Department of Internal Affairs and Statistics New Zealand released their report into the use of algorithms by Government agencies. The report finds that Government agencies are applying a range of safeguards and assurance processes in the use of algorithms. However, the report also states the importance of preserving appropriate oversight by individuals and notes there are opportunities for increased collaboration and sharing. For a copy of the report, click here.
The report discusses the benefit in the use of algorithms, before outlining, in a number of case studies, how algorithms have been used by agencies to solve particular issues. It concludes with a number of recommendations for the future use of algorithms by government agencies.
Human oversight is a key recommendation of the report. This recommendation echoes the requirements of the EU’s recently enacted data protection laws in relation to the use of algorithms, which provides in Article 22 that individuals should not be subjected to a decision based solely on automated processing.
A key part of the report is the restatement and discussion of how agencies stacked up against the six principles for the safe and effective use of data and analytics released by the Privacy Commissioner and the Government’s Chief Data Steward in May 2018. These principles are:
- Collecting and using public data must deliver a clear public benefit
- Such use of public data must be done in a transparent way
- Understand the limitations of the data analytics
- Retain human oversight in the process
- Ensure the data is fit for purpose
- Focus on the people behind the data and how to protect them from misuse of the data.
Click here for more information from the Privacy Commissioner and Chief Data Steward on those principles.
Application to private sector
In our view, these principles have useful application not just to public sector data analytics, but to any data analytics project. For private sector projects, the first two principles can be re-worded to refer to the purpose for which the data is being collected and the role of the algorithm in the decisions being made being made clear to the persons from who the data is collected.
We recommend you consider these principles whenever algorithms are used to analyse data and make predictions of future outcomes.
If you want any further information on any of these matters please get in touch with your usual Lane Neave contact or a member of Lane Neave’s corporate team.
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