"Big data provides information about the population's needs and allows for better social policies"

 

Espoo is the second largest city in Finland after the capital, Helsinki. With half a million inhabitants, it is one of the world's leading cities in terms of putting mass data processing tools into action to improve policy and social budgetary planning, and to welcome newcomers, whose numbers have risen considerably in recent years.

Having access to data, specifically big data, and knowing how to work with them using machine learning helps us to gather more in-depth and real knowledge about citizens' needs, and this can be used to plan prevention policies, just as they do in Espoo. However, despite all the benefits of using big data and artificial intelligence to extract patterns and predictive models, in the area of social services it is still not a particularly widespread practice internationally.

For this reason, the iSocial Foundation has organized a series of discussions on data mining and social services, in collaboration with the UOC. The iSocial Foundation was set up in 2018 in Barcelona with the specific aim of fostering innovation in the social services sector in Catalonia. Working behind the scenes of the series, the first to be run in Catalonia in this field, is Toni Codina, director of iSocial and former general manager of the Taula d’entitats del Tercer Sector Social de Catalunya (Catalan Board of Third Social Sector Organizations, 2007-2018).

 

 

Espoo is the second largest city in Finland after the capital, Helsinki. With half a million inhabitants, it is one of the world's leading cities in terms of putting mass data processing tools into action to improve policy and social budgetary planning, and to welcome newcomers, whose numbers have risen considerably in recent years.

Having access to data, specifically big data, and knowing how to work with them using machine learning helps us to gather more in-depth and real knowledge about citizens' needs, and this can be used to plan prevention policies, just as they do in Espoo. However, despite all the benefits of using big data and artificial intelligence to extract patterns and predictive models, in the area of social services it is still not a particularly widespread practice internationally.

For this reason, the iSocial Foundation has organized a series of discussions on data mining and social services, in collaboration with the UOC. The iSocial Foundation was set up in 2018 in Barcelona with the specific aim of fostering innovation in the social services sector in Catalonia. Working behind the scenes of the series, the first to be run in Catalonia in this field, is Toni Codina, director of iSocial and former general manager of the Taula d’entitats del Tercer Sector Social de Catalunya (Catalan Board of Third Social Sector Organizations, 2007-2018).

 

It's a sector under construction. Although it's the fourth cornerstone of the welfare state and the last to be created, it's still an unfinished system in which there are still serious difficulties related to funding. You only have to look at the Law on dependency in Spain, which has still not been fully implemented and which has severe budgetary and organizational shortfalls. At the same time, the local administrations, town councils and county councils, which manage the main social services and are on the frontline, find it very difficult to provide services at the level that society needs, and the leaders of the Catalan Government don't have enough leverage right now.

Without a doubt. Big data provides knowledge, evidence that would enable administrations to get a better understanding of the population's needs in every region. Based on the data and using artificial intelligence algorithms, we can firstly extract patterns that would be too difficult to extract manually; secondly, we can analyse trends, and, finally, we can predict the evolution of needs in the various areas of social intervention, from home care for the elderly to energy poverty, support services for disabled people, care for children suffering abuse, and many more.

Unfortunately, and unlike other sectors such as education and healthcare, social services today are still very bogged down in providing a response to emergencies. This never-ending spiral of action and reaction in response to new social needs and challenges hinders planning, prevention and the investment of resources, time and effort in medium- and long-term innovation. As a result, the generation of knowledge has to be leveraged to help social services to plan better, to draw up public budgets more efficiently, to design better social policies and to strengthen preventive policies. In addition, big data also enables progress in the personalization of services thanks to the knowledge gained and the categorization of the various user types.

Public funds devoted to social services in the last fifteen years have grown exponentially, both in local governments and the Catalan Government. They even increased during the crisis, when the social situation in Catalonia was in a state of emergency, which meant social services were one of the few budgetary items that weren't affected by cuts.

However, despite this budgetary increase, the system hasn't moved forward in tandem with the organizational point of view. The system is still not particularly efficient, in the sense that we have little knowledge and scarce evidence to aid decision-making, on both the large and small scale.

It's most certainly to do with the fact that the system is permanently overwhelmed, both institutionally and in the everyday work of the social workers helping people. But that isn't the only reason. Political instability, budgetary extensions and jurisdictional conflicts are also factors contributing to the system's weakness.

In the case of home care, which is the second largest contract for many town councils after cleaning, the councils usually don't have enough information to be able to plan such a major expenditure. They don't know how demand for this service will evolve, so they're drawing up annual budgets in the dark. By contrast, the healthcare sector has been working with big data for fifteen years and knows, for example, that in the next decade, the number of strokes in Catalonia will double. Armed with this information, the whole healthcare system is gearing up to adapt to this new scenario.

Yes, it's the first time we've held talks in Catalonia that put the focus on social services. We started the series of discussions on 25 September and it finishes on 10 March. It's attended primarily by managers and experts from town councils and third sector organizations that are looking to find out how to use mass data processing to improve their day-to-day work, in much the same way that the commercial sector and the healthcare sector have done.

Social services are still very much a cottage-industry sector, where social workers provide very personalized care for people in vulnerable situations, where there are few automated processes. In fact, automation is often seen as a threat and not as a necessary and useful aid. There are still too many fears and questions regarding the use of big data in social services, and during this series of discussion our aim is to try and tackle them and to provide answers.

First of all, we wanted to illustrate and explain the benefits that introducing big data and artificial intelligence can bring to the social services sector, such as strengthening preventive policies, which everyone agrees is hugely important, or the personalization of services and the design of a catalogue of services that can be adapted to the various user profiles.

Secondly, we wanted to discuss the limits and risks of setting out on this path, taking into account several points of view: the ethical viewpoint, a practical viewpoint based on how professionals work, and that of respecting and guaranteeing service user's rights.

Absolutely. Especially considering that in this case we're dealing with more fragile people who are at a greater risk of their rights being infringed: elderly people with cognitive deterioration, young people with mental health disorders, newly-arrived families with little knowledge of the language and environment, homeless people, etc. Consequently, we have to be much more careful to ensure that we protect these people's rights when we use their data, even though big data generally works on the basis of anonymized data.

The UOC has helped us to organize the series of discussions through the Health Data Science area at the eHealth Center, both in designing the contents and in moderating some of the debates. In addition to this, we've started to promote joint research projects with various professors and researchers in this field. This will help us gain a greater understanding of the opportunities that big data can offer to drive forward specific areas of social services.

Up until now the UOC had conducted research into big data focusing on healthcare, so at iSocial we're pleased to hear that it's also starting to focus on the social services sector as part of the University's role in society, as its contribution could be very significant in helping our society to progress.