For my CREST Silver Award, I independently designed and conducted a research study exploring how elderly care home residents engage with AI chatbot technology. Visiting a Hertfordshire residential care home, I surveyed 19 residents aged 60–100, analysing their technology habits, chatbot awareness, and accessibility needs. Results revealed widespread unfamiliarity with chatbots, with key barriers including fear of errors, privacy concerns, and low motivation to learn. The research concludes that motivation — not capability — is the primary obstacle to adoption, recommending voice-controlled, conversational AI with clear, slow speech as the most viable solution for this demographic.

Awarded a Merit with Distinction — the second-highest grade — in my school's Dawson essay competition. The essay investigates the origins of bias in AI systems, tracing how it emerges from training data, design decisions, and the demographics of the teams that build these systems. It examines real-world cases where bias has led to discriminatory outcomes in hiring, healthcare, and criminal justice, and argues that bias in AI is not a technical accident but a reflection of existing societal inequalities. The essay concludes by exploring what meaningful mitigation looks like — from dataset audits to diverse engineering teams — and what responsibilities developers and policymakers share.