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Six lessons for an AI assurance profession to learn from other domains - part three: features of effective certification schemes

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We are looking at professionalisation and certification as part of our programme of work to support the vision laid out in our roadmap to an effective AI assurance ecosystem. As discussed in part one, it will be helpful to learn …

Six lessons for an AI assurance profession to learn from other domains - part two: conditions for effective certification

Posted by: and , Posted on: - Categories: Algorithms, Artificial intelligence, Assurance

Lesson two: Broad community building is crucial  Community building that emphasises skills, communication, and diversity is crucial for ensuring that certification is reliable and accountable. Other sectors, like cybersecurity and healthcare, as well as cross-sector communities organised around ESG and …

Six lessons for an AI assurance profession to learn from other domains - part one: how can certification support trustworthy AI?

The UK government's recently published approach to AI regulation sets out a proportionate and adaptable framework that manages risk and enhances trust while also allowing innovation to flourish. The framework also highlights the critical role of tools for trustworthy AI, …

Working with the ICO to encourage the adoption of PETs

Posted by: , Posted on: - Categories: Algorithms, Artificial intelligence, Data, Ethical innovation

Last year, the CDEI launched a responsible data access programme to address the challenges organisations face to access data they need in a responsible way. A key component of this programme is our work to encourage adoption of Privacy-Enhancing Technologies …

Improving responsible access to demographic data to address bias

Posted by: and , Posted on: - Categories: Algorithms, Artificial intelligence, Bias, Data, Demographic data, Intermediaries, Trust

Following our review into bias in algorithmic decision-making, the CDEI has been exploring challenges around access to demographic data for detecting and mitigating bias in AI systems, and considering potential solutions to address these challenges.  Today we are publishing our …

Fairness Innovation Challenge: Call for Use Cases

Building and using AI systems fairly can be challenging, but is hugely important if the potential benefits from better use of AI are to be achieved.  Recognising this, the government's recent white paper “A pro-innovation approach to AI regulation” proposes …

From principles to practice: Launching the Portfolio of AI Assurance techniques

Posted by: and , Posted on: - Categories: Algorithms, Artificial intelligence, Assurance, Trust, Trustworthy innovation

Today, we are pleased to announce the launch of DSIT’s Portfolio of AI Assurance Techniques. The portfolio features a range of case studies illustrating various AI assurance techniques being used in the real-world to support the development of trustworthy AI. …

From Roadmap to Reality: Insights from Industry on Advancing AI Assurance

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As set out in the Government’s National AI Strategy, the UK aims to establish the most trusted and pro-innovation system for AI governance in the world. A key component of getting this light-touch and pro-innovation governance right, is delivering on …

Developing the Algorithmic Transparency Standard in the open

Today the Central Digital and Data Office (CDDO) and the Centre for Data Ethics and Innovation (CDEI) are sharing an updated version of the Algorithmic Transparency Standard on GitHub. Sharing the updated Standard on GitHub will allow interested stakeholders to …