Research

The conditions that let groups think well

My work asks how knowledge moves through groups, how voice and authority shape what becomes actionable, and what helps diverse perspectives remain useful in a shared decision.

01

Doctoral research

Current focus

Diversity and influence in group decision-making

What helps a group combine different knowledge without quietly collapsing into the same framing?

The question

I study information diversity, confidence, influence, dissent, and collective accuracy in group settings. My doctoral project examines these dynamics when AI becomes part of the process, asking not simply whether a tool produces a good answer, but what it changes about the group’s own reasoning.

The approach

The work combines sociological analysis with computational methods, experimental thinking, and agent-based modelling. I am interested in the mechanisms behind outcomes, especially who gains influence and which forms of knowledge remain visible.

Human-AI interactionGroup decision-makingAgent-based modellingInformation diversity
02

Master’s research

Completed study

Community knowledge and cluster farming

What do smallholder farmers understand about collective farming arrangements that formal adoption models fail to see?

The work

I designed and conducted a community knowledge-based assessment of smallholder farmers’ perceptions of cluster farming in southwestern Nigeria, combining qualitative and quantitative evidence.

Why it matters

Institutional assessments often treat farmer reluctance as an information deficit. Community knowledge reveals a more complex picture shaped by trust, risk, memory, local conditions, and previous collective arrangements.

03

Knowledge systems

Ongoing inquiry

Digital agriculture and local variation

Digital tools can reach farmers that extension services never could, while making advice more centralised and less responsive to local observation.

The tension

Uniform recommendations can scale quickly, but agricultural knowledge is shaped by soil, weather, labour, markets, history, and highly local risk. A system can broaden access while narrowing what counts as relevant knowledge.

The design question

What would an advisory system look like if it treated farmers not only as recipients of guidance, but as observers whose distributed knowledge should flow back into the system?

04

Forthcoming chapter

Anticipatory governance

Innovation systems and African futures

When institutions prepare for the future, who gets to define the future they are preparing for?

The contribution

A co-authored chapter with Geci Karuri-Sebina and Olugbenga Adesida examines anticipatory innovation systems across African contexts and how institutions can move from reaction toward foresight.

The collective question

Future-making depends on knowledge that is often distributed, informal, and excluded from institutional planning. Better anticipation requires more than forecasting; it requires better ways of including what different communities already know.

How I work

Methods in conversation

01

Participatory research

Working with communities to surface experience, interpretation, and knowledge that formal measures can overlook.

02

Computational inquiry

Using Python, R, data analysis, NLP, and agent-based models to explore patterns and mechanisms.

03

Systems thinking

Studying outcomes as products of relationships, structures, feedback, and context rather than isolated variables.

04

Fieldwork

Keeping research grounded in the realities, histories, constraints, and practical judgments of people involved.