RESEARCH / AREAS OF INQUIRY

Open questions.
Rigorous thinking.

Exploring human and AI consciousness, the boundaries of cognition, and the connections between minds, machines, and the physical world.

I think in systems: how the parts fit together, what feeds back into what, and where an idea from one field might illuminate another. Unexpected associations often give me a starting point. Turning them into precise, testable questions is the next step.

How we perceive, decide, and act.

Experimental psychology

Rigorous scientific methodology in cognitive and behavioural research. Experimental design and the study of human cognition connect my research with the systems I build.

The experience behind the mechanism.

Consciousness & perception

Investigating the fundamental nature of conscious experience and perceptual processes through experimental psychology and neuroscience methodologies.

Could an artificial system have experience?

AI consciousness

I also research AI consciousness: whether artificial systems could have subjective experience, how we might recognise it, and what would count as evidence. This connects questions about awareness and cognition with the architectures of the systems we build, and the distinction between convincing behaviour and experience itself.

Invite me to speak about AI consciousness

Unusual questions. Careful methods.

Psi research

Scientific investigation of anomalous phenomena including telepathy, presentiment, and retrocausal effects. My focus is on experimental methods, statistical interpretation, and what the evidence can support.

Retroactive practice

Can later practice show up in earlier performance?

Normally, we practise first and perform better afterwards. Retroactive practice is the proposed reverse: an association between practice that happens later and performance already measured. With Dick Bierman, I investigated this using a Go/NoGo task, in which participants respond to certain shapes and withhold their response to others.

First, measure performance.Participants respond to two shapes. Their reaction times are recorded.
Then, choose the practice.One of those shapes is randomly selected for a second task, providing additional practice after the first task is complete.
Look back at the first task.Compare the earlier responses to the shape later practised with those to the shape that received no further practice.

What we found

In our 2014 paper, the 67 participants analysed had responded about 2% faster to the shape that would later be practised. The strongest statistical evidence came from the 35 participants classified as intuitive thinkers: the results section reports p = 0.001, one-tailed. The rational-thinking group did not show a significant effect.

I see this as strong evidence consistent with retroactive practice in the intuitive group, and a finding worth pursuing. Establishing its robustness calls for independent, preregistered replication. Our paper also examines ambiguities in the original analysis plan and their implications for interpreting the results.

Read the published study

Bierman & Bijl (2014), Journal of Scientific Exploration, 28(3), 437–452. Results: pp. 444–445; discussion: pp. 448–451.

Looking for the structures underneath.

Physics modeling

Developing theoretical models for fundamental physics, exploring the mathematical structures underlying physical reality and consciousness.

A better way through difficult problems.

Problem space optimization

Methodologies for navigating complex solution spaces, combining computational approaches with cognitive strategies for effective problem-solving.

Human understanding. Machine capability.

AI systems architecture

Designing effective human–AI interactions and prompt engineering strategies for large language models and autonomous AI systems.

AI & automation services