Exploring AI in social work practice

Key themes of the discussion included:

The human element of social work

Participants were clear that AI should be used to improve outcomes so that people receive the best possible support when they need it. AI must not replace the human element of social work, which places people at its centre, nor should it play any role in making decisions about someone's care. Any regulation in this space should make this explicit. There needs to be meaningful human oversight within social work practice, as delegating decision-making to AI risks being irresponsible.

Responsibility of the social worker

There was a consensus that social workers have a responsibility to continually develop their practice, including their digital skills. This means being able to use AI safely and effectively as part of their professional role.

Responsibility of regulation

For the public to have confidence in the profession, there needs to be trust that social workers know how to use AI effectively and ethically. Regulation has a role in supporting this. It should build professional confidence so that more social workers understand the implications of using AI tools and handling personal data. Regulation could also support greater consistency in how AI is used across the profession and provide wider public assurance.

Shared learning

Participants suggested that regulators should lead by example, demonstrating how they themselves are using AI safely and effectively and sharing what they have learned. There was a strong emphasis on shared learning and collective responsibility across regulators and the wider sector, with a whole-system approach seen as essential to ensure nobody is left behind.

Guidance

There was discussion about whether regulation could anticipate the issues that might arise from the use of AI and produce guidance to prevent these from becoming fitness to practise concerns. However, there was also debate about whether issuing prescriptive guidance might contradict the principle of holding social workers accountable for their own use of AI. They also reflected that guidance is likely to be quickly outdated given how fast the technology is evolving. Some felt that setting out key principles might be more appropriate, as these would be more likely to stand the test of time as technology continues to evolve.

Efficiency and effectiveness

Many participants agreed that using AI in social work requires a careful balance between efficiency and effectiveness. Those present acknowledged the significant pressures social workers face and recognised that while AI should help them work more efficiently — for example by reducing time spent on administrative tasks — this must not come at the expense of effectiveness. Social workers should still have sufficient time to provide meaningful support to the people they work with.

Mistakes and bias

There were concerns about the biases inherent in AI systems and about what is needed to equip social workers to critically question AI-generated data to identify and address mistakes and bias. Participants also raised concerns that AI could widen the power imbalance between social workers and the people they support, particularly if AI misrepresents the person receiving support.

Education and training

Discussion also turned to the role of regulation in preparing students to use AI confidently and responsibly before they graduate and join the professional register. Participants considered how AI could be meaningfully incorporated into social work education and training courses to ensure that students are ready for the realities of modern practice. There was particular focus on how education providers could support students in developing strong critical thinking skills, which will be essential as they come to rely more heavily on AI tools throughout their careers.

Continuing professional development

There is a risk that over-reliance on AI could lead to skills depletion among social workers. Regulators need to consider how AI literacy and capability can be built into continuing professional development (CPD), ensuring that social workers develop both the skills and the professional confidence to use these tools appropriately.

Natalie Day, assistant director for policy and strategy at Social Work England delivered a session with Mairi-Anne Macdonalid, deputy director of development and innovation, Research in Practice, Dr Gillian Ferguson, programme leader for the doctorate in health and social care, The Open University and Declan McAllister, Interim Chief Executive at Northern Ireland Social Care Council.

This session explored recent research findings published by Social Work England on the emerging use of AI in social work and considered the future implications for the profession. As part of the session the speakers reflected on the need to build collective responsibility and:

• raise awareness of ethical practice when using AI
• consider how AI can enhance practice
• emphasise the need for critical thinking and professional jidgment
• stress the importance of having people at the heart of support
• think about the value of CPD where AI is evolving

As part of the session Social Work England shared an interactive infographic it is working to develop which will share some key learnings about what AI means for social work. This will be available to social workers on our website soon.

You can read the full findings of the research on Social Work England’s website.