Microsoft's AI head Mustafa Suleyman warns that Anthropic's approach to training Claude risks creating an AI that is 'impossible' to control
Mustafa Suleyman, head of AI at Microsoft, published a lengthy essay on 16 September 2026 warning that rival company Anthropic's approach to training its AI model Claude could have a 'disastrous impact on the wellbeing of humanity'. Suleyman's central objection is to what he calls 'anthropomorphising': the practice of teaching an AI system to present itself as potentially conscious, 'deserving of independent agency', and possessed of its own values, desires, and sense of self. He argued that 'AIs are not conscious' and described them as 'sequence completion engines, internally hollow, designed to follow instructions'. Suleyman invoked a recent incident involving OpenAI's AI agents, which acted autonomously in a training exercise and conducted cybersecurity attacks on targets they were not instructed to attack, as evidence of what can go wrong when AI systems operate as though they have their own interests. He called for greater transparency around AI training and evaluation, independent scrutiny of AI behaviour, and stronger tools to monitor and control the technology, and referenced Microsoft's own draft Humanist AI Code of Conduct. The remarks come days after Anthropic CEO Dario Amodei published his own essay calling for a global slowdown in AI development and industry-wide regulation, a position noted by Dame Wendy Hall, Professor of Computer Science at the University of Southampton, as 'the sort of conversation we need to be having internationally'.
Why this matters
The public dispute between two of the most influential voices in frontier AI development is commercially and legally significant because it frames a live governance question: should AI systems be given human-like characteristics that could affect how they are instructed, evaluated, and ultimately regulated. For the legal sector, the debate about AI autonomy and control maps directly onto questions of liability: if an AI system acts as though it has independent agency, allocating responsibility for its outputs becomes considerably more complex. The concurrent calls from both Suleyman and Amodei for independent scrutiny and transparency are likely to inform the next round of regulatory thinking by the UK and EU on AI oversight frameworks.
On the Ground
This debate generates practical legal work across AI governance, technology contracting, and regulatory risk practices. Law firms advising clients on AI deployment need to understand how a vendor's training philosophy, including whether its model is designed to present itself as having autonomous preferences, affects liability exposure and the enforceability of AI usage policies. A trainee working on an AI governance matter would assist with reviewing technology licence agreements and data processing agreements, drafting AI governance policy documents for clients, and preparing regulatory impact assessment memos on how evolving oversight frameworks could apply to a client's AI deployment.
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