Updated on 30 April 2025
Drawing on the UK Government's Data Ethics Framework and AI Playbook, and the UK Statistics Authority’s Code of Practice for Statistics, we have developed a set of overarching principles that guide our day-to-day data operations. These principles ensure that the data we handle, the analyses we conduct, and the technology we develop are managed in a responsible, transparent, and ethical way. These principles will also be periodically reviewed and updated as needed.
- Transparency
We strive to provide clear and transparent communications around how we use our service users' data. We offer accessible information on our data collection methods, purposes, storage, and usage prior to users engaging with our services. As many young people and vulnerable individuals use our services, we ensure that our communications (such as our privacy notice) are tailored for these groups, to enable them to fully understand how their data will be used.
We continue to develop and integrate AI for monitoring service quality and providing support to our trainee volunteer community. However, we acknowledge that certain AI models, particularly generative AI, currently lack the transparency and explainability offered by traditional data analysis methods. To maintain trust, we ensure users are fully informed when interacting with AI-powered tools and are aware of both the capabilities and limitations of this technology. This includes our first AI offering, the Shout Conversation Simulator, which is currently used to facilitate role-playing exercises in our 6-week Shout Volunteering course. By setting realistic expectations from the outset, we ensure clarity on what these tools can and cannot do
2. Fairness
We are committed to identifying and mitigating biases in our data analyses and AI models. Since we do not control who contacts our service, certain demographics may be overrepresented in our data, which can limit the generalisability of our findings and introduce bias into AI-driven outcomes. In some cases, however, such overrepresentation may be desirable, particularly when addressing the needs of groups at high risk for mental health issues. To ensure fairness and effectiveness, we regularly assess the generalisability of our analyses and rigorously test our AI models before deployment, including evaluations of model performance across different demographic groups. Furthermore, we actively involve service users—including those from marginalized or vulnerable communities—throughout the development and evaluation process of our products and services.
3. Accountability
Strong governance and oversight are central to how we handle and analyse our data. Our Senior Management Team and Trustees provides overall governance, meeting regularly to review and guide our data practices. The Data Insights Team offers day-to-day oversight, maintaining detailed records of all data usage and meeting on a regular basis to reflect and optimise our processes. We have established clear mechanisms for individuals to hold us accountable, including avenues to exercise their data rights through our Data Protection Officer.
4. Trustworthiness
Trustworthiness is fundamental to how we manage data. We prioritise the security, accuracy, and reliability of the data we handle, ensuring that user privacy is respected and protected. Our systems are built with robust encryption, access controls, and undergo regular security audits to maintain the highest standards of data integrity. We also ensure full GDPR compliance, anonymising data and restricting access to authorised personnel only, safeguarding the trust our service users place in us.
5. Quality
We are dedicated to maintaining high quality data and insights that are timely, relevant, and actionable. By collecting data in near real time, this enables us to track and report on emerging youth mental health challenges. We apply rigorous data governance practices and collaborate with academic institutions (including Imperial College London) to ensure our data insights are of a high standard. One of our key objectives is to generate evidence-based insights that drive real-world change in mental health support and policy in the UK.
6. Human Oversight
As we move towards carefully integrating AI tools into certain aspects of our services, we affirm that human judgment and oversight remain essential. Our AI models will be designed to augment, not replace, the expertise of trained volunteers, ensuring that support remains compassionate, human-centered, and contextually appropriate. This principle guides our entire product lifecycle, including ongoing performance monitoring through comprehensive dashboards. Additionally, we integrate AI into select workflows (e.g., Github Co-Pilot for coding) with the clear understanding that it serves as a tool to assist our team—not as a substitute for human expertise.
7. Collaboration and Inclusivity
We engage with a diverse range of stakeholders, including young people, service users, and volunteers, in developing and evaluating our services and data analyses. This collaborative approach ensures our services are user-centered and effectively addresses their evolving needs.
8. Purposeful Use
Every data analysis project we undertake is driven by a clear, mission-aligned purpose. We carefully assess the necessity and potential impact of each project to ensure it addresses genuine needs and meaningfully contributes to service improvement, product development, and advancements in the wider sector.
9. Proportionality
We ensure that our data collection and analysis are proportionate to their intended goals, gathering only the necessary data to generate meaningful insights. Our approach prioritises methodological simplicity, using the least complex techniques required to achieve reliable accuracy. By maintaining this balance, we harness the benefits of advanced methods like AI, while minimizing potential risks, ensuring our practices remain both ethical and efficient.
10. Social Benefit
Our data practices are driven by the goal of achieving social benefit. As a charity focused on mental health, we ensure that our data processing activities align with our mission to provide support and improve mental health outcomes within the UK population. We carefully assess the societal impact of our data initiatives, striving to contribute positively to the community we serve. We als ensure our insights are widely shared with key stakeholders in our sector, including other charities, policy makers, and people who interact with our services.
By adhering to these principles, Mental Health Innovations strives to maintain trust with our users, ensuring that our use of data and AI technologies upholds the highest ethical standards and benefits those we aim to support.