Dr David Bozward

Tag: Responsible AI

  • Is the UK Curriculum Ready for Artificial Intelligence?

    Is the UK Curriculum Ready for Artificial Intelligence?

    Artificial intelligence is already changing how young people learn, communicate and prepare for employment. Pupils use AI-powered search engines, recommendation systems, writing assistants and image generators, often without fully understanding how these technologies work or the risks they create. The important question is therefore no longer whether schools should teach AI, but how AI should be incorporated into the curriculum safely, consistently and credibly.

    At present, AI education for under-18s across the UK remains fragmented. It can appear within computing, digital literacy, personal development and subject-specific activities, but there is no consistent entitlement ensuring that every young person develops an appropriate level of AI literacy.

    England’s existing computing curriculum develops programming, algorithms, computational thinking and digital safety. However, it does not yet provide a clear progression in AI knowledge. The government has committed to replacing GCSE Computer Science with a broader Computing GCSE incorporating AI and is considering a new Level 3 qualification in Data Science and AI. Secondary relationships, sex and health education also now includes consideration of AI chatbots, deepfakes, misinformation and disinformation.

    Scotland currently offers the clearest formal pathway. The Scottish Government’s guidance states that young people should have opportunities to learn about, understand and use AI as part of the 3–18 curriculum. The Scottish Qualifications Authority offers National Progression Awards in Computing Technologies at SCQF Levels 4, 5 and 6. These can include dedicated Artificial Intelligence units. Its National Progression Awards in Data Science also cover data citizenship, machine learning and generative AI.

    Wales embeds digital competence across the Curriculum for Wales and provides resources addressing AI bias, safe use and ethical decision-making. The WJEC AS and A Level in Digital Technology includes the development of AI, expert systems, large datasets and the social implications of automated technologies. Northern Ireland has concentrated on responsible-use guidance, teacher adoption and research into AI-supported literacy, rather than creating a separate school AI subject.

    Several regulated specialist qualifications are now available. The AIB Level 2 Award in Understanding AI is open to learners aged 14 and above. It covers AI concepts, training data, machine learning, bias, fairness and responsible use. For learners aged 16 and above, the AIB Level 3 Award in AI – Concepts, Ethics and Applications provides a more critical examination of AI systems, ethics, law and digital rights. The much larger AIB Level 3 Diploma in Applied AI includes programming, data preparation, AI models, responsible practice and project development.

    NOCN also offers a Level 2 Award in AI Awareness and a larger Level 2 Certificate in AI Awareness for learners aged 16 and above. These focus particularly on workplace applications, risks, responsible use and career development.

    Schools can supplement formal study through programmes such as Raspberry Pi Foundation and Google DeepMind’s Experience AI, aimed at 11–14-year-olds. The iDEA Bronze and Gold Awards also contain badges covering AI, machine learning, computer vision, chatbots and fake-news detection. These provide valuable enrichment, although they are not regulated qualifications.

    The most significant gap is the absence of a widely adopted, full-sized Level 2 AI qualification for 14–16-year-olds that receives the same recognition as other GCSE or Technical Award options. A short Level 2 Award may be taught at GCSE difficulty, but that does not make it equivalent to a full GCSE in size, curriculum coverage or school performance measures.

    Every learner now needs more than prompt-writing skills. An effective curriculum should include data literacy, model training and testing, bias, hallucinations, privacy, cybersecurity, copyright, environmental impact and human accountability. Young people should learn when AI is useful, when it should not be used and how its outputs can be independently verified.

    The UK has begun to recognise AI literacy as an essential educational outcome. The next step is to turn scattered initiatives into a coherent pathway from primary education through to Level 3 study. AI should become a core component of modern education—not simply a specialist option for pupils already interested in computer science.

  • Governance by AI: The Next Corporate Governance Challenge

    Governance by AI: The Next Corporate Governance Challenge

    Corporate governance has always been built around one core assumption: companies are run by people.

    Shareholders appoint directors. Directors oversee executives. Executives manage teams. Teams deliver the work. Governance systems, board papers, delegated authority, audit trails, risk registers and accountability frameworks all assume that human beings make the important decisions.

    Artificial intelligence is beginning to challenge that assumption.

    Most current discussion focuses on AI governance: how organisations should use AI responsibly, safely and ethically. That is important, but it is not the whole issue. A deeper challenge is now emerging: what happens when AI does not simply support management, but becomes part of the management system itself?

    This is the shift from governance of AI to governance by AI.

    AI systems can already analyse markets, generate forecasts, assess risks, screen customers, monitor cyber threats, recommend suppliers, automate workflows and support strategic decisions. As autonomous agents develop, they will increasingly be able to initiate actions, make recommendations, execute decisions and adapt processes with limited human involvement.

    That creates a new governance problem.

    The question is no longer only:

    How do we make sure AI is safe and responsible?

    It is also:

    How do we govern an organisation when AI is making or influencing material business decisions?

    This is where the concept of delegated machine authority becomes important. Delegated machine authority occurs when a business gives AI systems decision rights that would previously have belonged to people. This could include approving transactions, reallocating resources, changing prices, prioritising customers, flagging risks or triggering operational actions.

    The risk is not that AI suddenly becomes a legal director. It does not. Human directors and officers remain accountable. The risk is that practical decision-making moves into AI systems while formal accountability remains with humans who may not fully understand, monitor or control those systems.

    This creates what can be called the Autonomous Governance Gap: the gap between governance systems designed for human managers and organisations increasingly managed through autonomous AI systems.

    To close that gap, boards will need a new governance framework. This should include seven core elements.

    First, companies need an AI decision-rights architecture. Boards must define what AI may analyse, recommend, decide or execute, and which decisions must remain human-only.

    Second, there must be a clear human accountability chain. Every AI system with material influence should have a named human owner, executive sponsor and board oversight route.

    Third, organisations need decision provenance: a corporate “black box” recording what the AI decided, what evidence it used, what alternatives were considered, who approved it and what happened afterwards.

    Fourth, AI-managed activity requires continuous assurance, not just annual review. Boards need live visibility of performance, drift, risk, compliance, cyber exposure and unintended consequences.

    Fifth, AI decisions must remain aligned with corporate purpose, stakeholder duties and risk appetite. Optimisation is not the same as judgement.

    Sixth, there must be meaningful human intervention rights: pause, override, escalation and shutdown mechanisms.

    Finally, AI governance must adapt as models, data, agents and business processes change.

    The next generation of corporate governance will not be about replacing boards with AI. It will be about ensuring that boards remain capable of governing companies where AI has become part of management.

    That is the real governance challenge ahead.