The future of the personalised state in Estonia. Scenarios up to 2040

Here, the term “personalised state” refers to a model where services and benefits are tailored to citizens’ life circumstances using their data and life events, while safeguarding their fundamental rights such as data protection, autonomy, privacy, transparency and equal treatment.

The personalised state is not the same as the digital state: public services can be personalised without digitalisation. Moreover, the public sector must ensure accessible communication and service channels for all citizens, including those who lack access to digital tools or prefer not to use them. However, digital development promotes personalisation, for example, by making new data analysis methods and privacy protection technology widely available.

The issue of proactivity and its extent becomes the focal point of personalisation. Proactivity means that the state, rather than the individual, initiates data processing and service provision based on the presumed will of the person. The state recommends benefits and services to citizens that, based on data analysis, are deemed to meet to their needs.

Estonia has taken a step towards proactivity by offering so-called event services, where data sharing between state institutions is triggered by life events such as childbirth, marriage or moving to Estonia. In such cases, the person receives a notification about the services and benefits applicable to them and they only need to confirm their wish to receive or use the said services and benefits. Applying to them separately is not needed. We can consider data processing initiated by state institutions with the aim of preventing negative life events for people, such as becoming unemployed, to be a further development of this logic.

There are two main directions for moving forward with the proactive (preventive) offer of services and benefits – either applicable to all by law or based on each person’s consent (see Figure 1).

The “applicable to all” direction requires creating a separate legal basis for data processing and is appropriate if there is a great public interest that justifies the secondary use of personal data (for a different purpose compared to the purpose of collection) and the infringement of fundamental rights is not disproportionately large. Using technologies that guarantee privacy can help reduce the infringement of fundamental rights.

In the consent-based direction, the person can decide for themselves whether they want to give permission for the processing of their data to receive offers for services and benefits customised to their situation and needs. They can, for example, decide to give consent to the sharing of their health data to receive offers for services preventing their individual health risks, but to not give consent to the sharing of their education data. Thus, the person would retain full control over the extent of data processing and participate as an equal partner in the decisions concerning their data. Challenges include the complexity of managing consents, the creation of parallel systems and the exclusion of population groups with lower digital skills.

Proactivity, as a form of state interference in a person’s autonomy that deviates from the current norms, requires a thorough and transparent public debate. We must critically assess whether there are ways to ensure transparency of proactive data use and for citizens to retain control over their data. The report underscores that proactive data use must always occur with citizens’ awareness and consent.

Figure 1. Solution options for proactive service provision

Based on the survey of the Foresight Centre, the residents of Estonia are moderately open to the personalisation of public services and benefits, but they are concerned about data security and afraid to lose benefits (see Figure 2). Personalised advice, more options and preventive offering of benefits and services in the event of risks are preferred as ways of personalisation of services. On the other hand, there is rather little support for data-based automatic decision-making and the so-called citizen account (a special-purpose account through which a person can use part of their taxes paid to purchase education, healthcare and other services privately, while the state reduces the provision of these services), for example.

Need-based or income-dependent benefits were considered acceptable by every other respondent. The support is significantly higher than average among the elderly and lower-paid people, whereas people with higher income support them less.

Figure 2. Acceptability of personalisation solutions
Source: prepared by the authors, based on the Norstat survey

Linking benefits to income could save the state up to 100 million euros per year, with minimal impact on relative poverty or inequality. Still, it would be less than the tax revenue that the additional percentage of economic growth would bring. Linking benefits to income has an impact on people’s behaviour. The hiding of income may increase and motivation to participate in the labour market may decrease. A significant concern is that individual income data is insufficient for fair decision-making. Taking household composition and assets into account would provide significantly greater accuracy, but these data are currently inaccurate or missing.

When analysing the possible future developments of the personalised state, developments in social inequality, the legal space and legal practices, the financial situation and prospects of the state and people’s trust in the state stood out as the most impactful factors. Considering these factors, three scenarios were prepared, aiming to create a picture of the different options and what risks and possibilities they entail.

In the “Available solutions” scenario, data leaks and misuses, along with declining trust in the state, lead to more restricted data use practices. At the same time, there is a growing demand in society for the state to be better at meeting the needs of different target groups and as a response, new benefits and services are added, creating a complex and fragmented system.

The state expands its consent service, initially designed for businesses, allowing individuals to permit the state to analyse their data and recommend suitable tailored benefits and services. Although the system improves the availability and effectiveness of services to some extent, it remains fragmented and the administrative burden remains high as not everyone is willing or able to give their consent and the consent management is complex as well.

The starting point of the “Limited resources” scenario is the very difficult situation of the state budget, requiring a focus on efficiency and resource savings. Receiving benefits is linked to people’s income level, considering that income per household member is the fairest approach. Although it allows combining various benefits which previously were separate benefits – for example, a single combined family benefit instead of the current child benefit, large family benefit and the single parent benefit – the resulting savings for the state remain smaller than hoped. Fluctuating benefit levels create uncertainty for people with unstable income, such as those in project-based or gig work.

In the “Data-based prevention” scenario, growing income and regional and educational disparities highlight the need for more effective social and public health risk prevention. The long-term prospects of state finances are affected by an ageing society and the low level of healthy life expectancy. More effective prevention of social and public health risks becomes unavoidable in order to rein in ever-increasing social costs and reduce inequality. The public broadly supports this, prompting and expanded legal framework to enable data reuse for targeted prevention efforts.

One by one, data-based prevention programmes for lifestyle diseases, job loss, early discontinuation of education and falling in debt and poverty start to be implemented. As a result, the state’s healthcare and social costs decrease in the long term, healthy life expectancy increases and people become more active on the labour market. However, many find that by data-based prevention, the state interferes too much in people’s private lives and there are increasing concerns about young people’s agency decreasing. Others, especially older residents, worry that the extensive reliance on automated data analysis reduces direct communication with officials.