Extending capability through human-machine intelligence
I design how human and machine intelligence operate and make decisions together in real-world systems. As machines become more capable and more embedded, system outcomes are determined by how these interactions are structured in practice. Most systems are not designed at that level.
Technology Level: AI safety and alignment, autonomous systems, brain-computer interfaces, quantum computing, robotics, space operations.
System Level: Intelligence analysis, adversarial decision modelling, cognitive security, human-machine teaming, cyber, decision support.
Civilisation Level: Climate systems, pandemic response, off-world governance, civilisational resilience, catastrophic decision-making.
Breakthrough technologies fail from flawed decision architectures and misaligned human-system integration.
Most systems fail because cognition is not correctly distributed between humans, machines, and the artefacts they share. The decision architecture was never designed: humans do not trust or correctly interpret machine outputs, workflows do not support human-machine thinking, and feedback loops do not improve either side.
The common thread is modelling intelligence under pressure, where the stakes are high, the data is incomplete, and the thing you are modelling may be actively working against you. Get that right then
AI systems can model how humans behave, including when they're trying to deceive the system.
Intelligence operations work because analysts process uncertainty correctly.
Space missions hold because crew decision-making doesn't break under isolation and stress.
Quantum systems become usable because humans can trust outputs they cannot intuitively verify.
Climate interventions land because they are designed to shift behaviour at civilisation scale.
The Work I’ve Led
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Decision Architecture for AI and Autonomous Systems I design how humans and machines make decisions together. Who decides what, when, with what information, and what happens when it goes wrong. I've done this for AI systems, robotics, autonomous platforms, and intelligence tools.
Research Labs for Emerging Technology I build research labs that work on technologies before they exist. I've done this for IoT, cloud infrastructure, intelligent systems. Now I'm focused on brain-computer interfaces, space operations, and quantum.
Behavioural Intelligence for Critical Systems I build teams that model how adversaries think, how operators fail under pressure, and how institutions resist change. Then I design systems that account for all three.
Technology Assessment for Human-AI Integration I find where AI systems will be rejected, misused, or exploited before they're deployed. Then I fix the human-machine layer so they actually work in the real world.
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Genomics England Led product and decision architecture for integrating genomic data into clinical pathways at population scale. Led teams building decision support systems for clinicians making high-stakes diagnostic and treatment decisions under time pressure, with incomplete data, where errors have life-or-death consequences.
QuantumBlack / McKinsey Led design of AI decision support systems in critical environments: clinical diagnostics, trading, industrial operations. Led teams that shipped products where the technical models worked but failure occurred at the human layer: operators overriding algorithms under pressure, losing situational awareness when automation failed, rejecting tools that didn't fit their workflow.
HP Labs Led research at one of the world's premier corporate research labs. Led teams building experimental frameworks for IoT, cloud infrastructure, and intelligent systems before these categories existed. Stood up research labs for questions that were yet to be explored, defined problems that hadn't been named, and shaped what the technology landscape would look like a decade later.
About Me
Computer scientist. Psychologist. 25 years working on one problem: intelligence, human, machine, and the critical interface between them.
I studied computer science and psychology together in the mid-90s because I saw what was coming: that the future would be defined by how these two forms of intelligence interact, collaborate, compete, and combine.
I started in Silicon Valley, in 2000, building what didn't exist yet: early cloud infrastructure, IoT, intelligent systems, robotics. I Led and stood up research labs for questions that were yet to be explored. Then spent two decades applying that same thinking to genomics, AI, and large-scale transformation in high-stakes environments.
I have led research and product teams and built and shipped product, all in service of two questions:
How do you build systems that help humans make better decisions under pressure, with incomplete information, when the stakes are high and the margin for error is small?
Which problems will matter in 100 years, and what do we need to build now to solve them?
I have built and shipped products, coded systems, programmed hardware and software. I have been on the ground doing what needs to be done to get a product to launch and as a leader I have stood by teams at that last mile to do the same. I hold three patents and have written and spoken extensively on the intersection of tech and psychology.