Insights
Research, analysis, and field observations at the intersection of AI governance, collaborative systems, and human flourishing.
PEER-REVIEWED RESEARCH
Published Work
Bridging Policy and Science Action Boundaries
Policy Sciences, 2018 · Lead Researcher & Primary Writer
DOI: 10.1007/s11077-018-9311-y
A grounded theory study of how senior U.S. congressional legislative staff process policy-related information and make decisions. The RCL framework (Relevance, Credibility, Legitimacy) developed in this research has been applied to AI governance strategy in emerging markets — revealing why technically sound frameworks fail to gain traction, and what trust architecture is required for effective adoption.
→ Read the Research · → Read the Applied Analysis
Flood Forecasting GIS Water-Flow Visualization Enhancement (WaVE): A Case Study
Journal of Geographic Information System, 2016 · Primary Writer & Coordinating Editor
Journal of Geographic Information System, 8, 692–728
A case study of an AI and GIS-based flood forecasting visualization tool developed for U.S. Senate policymakers and field operations. The patented AI component was co-developed with engineers at Microsoft’s Azure Cloud Computing Program and GIS leader Esri.
→ Read the Research
ACADEMIC RESEARCH
Cambridge Dissertation
Collaborative Technologies and the Translation of Disruptive Innovation
Cambridge MPhil Dissertation, 2007 · Judge Business School, University of Cambridge
Supervised by Dr. Michael Barrett, Judge Business School
Proposed a modified model of disruptive innovation diffusion reversing Actor-Network Theory’s traditional bias toward the centre — arguing that the most durable innovations emerge from the periphery through self-enrollment by actors whose needs are not served by incumbents. The periphery-first innovation architecture framework explains why technically sound AI governance frameworks fail in emerging markets, and what collaborative architecture is required for effective adoption. The theoretical foundation of the iCatalyst applied research series.
→ Available on request · → Applied analysis: LinkedIn Article 2 ‘The Wrong Model for AI Diffusion’
FEATURED SERIES
The iCatalyst AI Governance Research Series
Two articles applying two decades of research — from a 2007 Cambridge dissertation on disruptive innovation to a 2018 peer-reviewed study on legislative decision-making — to the specific challenge of AI governance in emerging markets.
Article 1
Why AI Governance Fails in Emerging Markets
The gap isn’t technical. It’s relational. Based on the RCL framework from the 2018 Policy Sciences research.
Article 2
The Wrong Model for AI Diffusion
Grounded in the 2007 Cambridge dissertation on periphery-first innovation architecture.
FEATURED ESSAY
Why AI Governance Fails in Emerging Markets — And What Actually Works
The gap isn’t technical. It’s relational. Peer-reviewed research on legislative decision-making reveals why trust architecture — not framework quality — determines whether AI governance initiatives succeed on the ground. The RCL framework — Relevance, Credibility, Legitimacy — provides a diagnostic tool for why technically sound AI safety frameworks fail in developing-market ecosystems, and what collaborative architectures are required for effective adoption.
FIELD NOTES & ANALYSIS
From the Blog
Observations, analysis, and insights from 25 years of field experience. New posts regularly.