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Technology and digital tools can help to centralise, cross-check and process data for better informed decision making in social care planning, design and delivery whilst Artificial intelligence (AI) can help to analyse the data and through algorithms advise social services professionals on the right type of support for people in need.

Promoting digitalisation in social services

“Two-thirds of UK-based care homes still use paper-based data collection, which makes it nearly impossible to use the data for large scale planning and decision making. It is now time for social services to make the investments to be at the forefront of the digital transformation,” explained Geoff Mulgan, Professor of Collective Intelligence at University College, London. Yet at this month's European Social Services Conference there was an increasing number of practice examples focused on the use of larger amounts of data and their assessment through algorithms to support decision making.

For instance, in Scotland the TURAS live data dashboard safety huddle was set up during Covid-19 to monitor the disease outbreaks in care homes. Pinneberg County Council in Germany uses digital data analysis generated through its PI Fokus App for better social planning and managed a much more targeted allocation of funds to where the needs are. The Dutch debt counselling services, Schuldhulp, uses data from payment failure of people to promote their services to people who may be very likely to have debt issues. Microsoft just one month ago has set up a digital personal assistant, that can assist people using digital devices and navigating the internet to make those more accessible. In the US data is analysed by AI to detect potential harm for children, allowing social services to intervene much earlier.

Joining up data in ONE platform

With the introduction of the Kanta system, Finland has made a big step forward to integrating different sources of data related to someone’s life and support so that social workers and people using social services can have seamless access to the person’s data and prevent them from having to repeat the same story over and over again. To make sure all data is collected in a consistent manner, Finland introduced Sosmeta – a harmonised data collection model for all social services. Antero Lehmuskoski, from the Finish Institute for Health and Welfare, outlined the key ingredients: 1. Conceptual clarity and agreed terminology for social services, 2. Documentation Training for social care professionals, 3. Close collaboration with IT-providers and developers and 4. Finland’s Client Information Act providing adequate safeguards for clients' rights and equality.

Data for independent living

Falls are the leading cause of injury-related loss of autonomy and death among older people,explained Vinay Venkatraman, Founder and CEO of Leapcraft, a Denmark-based company producing sensors.  But how can social services detect whether someone fell in their home? One way to do so is with using sensors we already have in our homes, as part of the internet of things. The region of Andalusia, Spain, is doing so with intelligent water meters in peoples’ homes to detect unusual use patterns. When this happens, a warning is triggered, and social services will contact the person or send a mobile unit or call the emergency services if necessary.

Harnessing the potential of AI

AI has the capability to anticipate and mitigate potential risks and can enable seamless connection between individuals and precisely tailor resources and interventions. Anamika Barman-Adhikari, Associate Professor at the University of Denver (US) has developed an artificial intelligence-based programme to predict substance use and maximising their positive friendships by allocating them AI-generated circles of support. This group-based Intervention has shown that AI-generated circles of support result in 40 to 70% reduction in substance use compared to random assignment. Despite those positive outcomes, AI cannot be blindly trusted. First experiences have shown that bias against families with disabilities and racial minorities can occur. “Effective utilisation of AI empowers social workers to excel in their core strengths of empathy, intuition, and experience, but it is our responsibility to prevent those systems from perpetuating historical injustices and biases”, concluded Anamika Barman-Adhikari.