Research and Development

Our main research themes aim to reduce the pain of compliance, increase the gain associated with AI deployments, and reduce the cost of AI Assurance.  These are pursued in support of issues arising from PRIDAR work.  Recent themes are are shown below
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Design Research

• ComputeNovelty - users driven novelty, safety design in open ended systems
• Framework For Change -  Socio-Technical Framework for AI development
• CALMS  a method of mitigating Bias and Risk of Harm in Large Language Models​
• DTxAI a method of reducing the risk in Digital Therapeutics AI 
• AutoPrevis - a method to automate pre-visualisations using GENAI tools​
• Public Interest AI 

Deployment Research​

• Midas a selection of AI Agents designed to improve the investment readiness of digital health firms
• HAL trained to guide users about potential hallucination in LLM dialogue
• PriorArt a method to manage Prior Art and Copyright infringements
• UXAI NHS AI Agent Design and Testing
• ASRI - Using Chatbots in Adult ADHD Self Reporting Information Gathering
• Arun - increases the reach of VR based well-being support​
• AutoESG trained to automate ESG evidence gathering and reporting

• Eli trained to elicit discussion about AI Risks in line with the IDEA Protocol (PoC in 2024)

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​Assurance Research​​​

• PRIDAR - the first and most popular Framework for Visualising AI Risk for Investors​
• Model Transparency, Design and Reporting
• PRIDAR v BS 30440 v Standards thematic comparison 
• Compliance Team Scoping - an example based in the need for BS30440 compliance 
• BS 42001 v 30440 - Evidence Comparison​.

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