The purpose of this work is to better understand public attitudes to data integration and the willingness of the New Zealand public to share their information directly or indirectly. More specifically, to understand how individuals from different demographic groups might perceive data re-use and integration, reveal any differences in perception of operational and statistical uses of data, and compare acceptability thresholds around this data use by the public. A further purpose is to examine the situations in which improved information might influence acceptability thresholds around data use, and to identify any barriers to confidence in Statistics NZ as a custodian of integrated data. By gauging the level and extent of public concerns, the reasons for those concerns, and the important distinctions between them, public sector agencies will be better positioned to anticipate public requirements and respond appropriately.
A multi-method, qualitative approach was chosen to investigate these complex concepts across a diverse range of groups. The in-depth qualitative approach also ensured participants understood the processes of data integration, so that they could engage thoughtfully and in greater depth with this topic. The qualitative research comprised of three stages, including: 1) in-depth narrative interviews in Wellington and Christchurch; 2) workshops across three urban centres (Wellington, Gisborne and Invercargill); and finally 3) an on-line discussion with different experts. Recruitment for the interview and workshop stages of the research actively targeted social groups of interest, including Māori, Pasifika, retirees, the unemployed, and the self-employed, but also included New Zealand residents who did not belong to these groups.
This research found that, fundamentally, data integration acceptability appears to be largely influenced by individuals’ own personal experiences with, and trust in, operational data sharing, the formation and use of statistics, as well as government agencies. Based on the research findings it is apparent that general data integration acceptability thresholds do exist. Participants appeared to gauge acceptability primarily based on the need for the information, how the data would be used and by whom. They were also interested in the value of the data integration, whether the benefits would be greater than the costs and risks, and how any potential risks might be mitigated.
Data integration tended to be seen as relatively more acceptable if there was a clear and appropriate need for it, if it was in the public interest, and it produced positive outcomes that had individual or public benefit. Participants’ emphasised that organisations involved would need to be highly trustworthy, professional, and competent. Strict procedures and protocols would need to exist around access and use, and databases would need to be completely secure and confidential. Statistical data integration was more acceptable if the data is completely de-personalised and anonymous. People tended to feel that data integration is more acceptable if the public is informed about what is happening and why. If personal, sensitive, or complex data is going to be integrated some participants felt that people should have the right to give or withdraw their informed consent.
Data integration tended to be seen as relatively unacceptable if there was no demonstrable need or purpose. People also tended to feel that integration would be unacceptable if it could be misused, or resulted in harmful or unfair outcomes. Examples of such outcomes include: if integrated data was used for direct commercial gain; to take advantage of vulnerable people; or for profiling, stereotyping, or disadvantaging certain groups or types of people, or people from particular places. People felt uncomfortable if poor quality data was used in a misrepresentative way, and some were unhappy about data being used for spying and surveillance.
If data was integrated in an acceptable way then most participants felt that this would be valuable and beneficial. People felt that integrated data systems could be more reliable, current and accurate than those currently used, and could result in more informed, fair, efficient and effective decision-making and service provision.
Most of the research participants had a high level of trust in Statistics New Zealand as a professional, competent and trustworthy custodian of data. However, some of the research participants had low levels of trust in Statistics New Zealand. Those with low levels of trust tended to feel this way if their experience with statistics was negative, such as if they felt that they personally, or where they live, had been stereotyped, stigmatised, or disadvantaged by generalisations based on statistics. Some also felt that statistics, in general, were not a useful or meaningful way to assess how well people are doing, or how happy they are, in a broader sense.
In order to retain and gain the public’s trust, Statistics New Zealand should take every care to actively demonstrate that they meet the acceptability criteria expected by the wider public if, and when, they conduct data integration.