Chevening Professional Relationships Essay Example: AI-for-good buzzword applicant

In Jordan's civic technology sector, I have learned that trustworthy tools depend on the relationships behind them. When I proposed an AI chatbot prototype, two colleagues challenged its accuracy and privacy handling. Rather than defend the design, I asked them to log specific failure cases and pull comparable examples from three regional deployments. We met weekly for a month; I synthesised their notes into tighter data retention rules and clearer user prompts. The habit stuck: I drafted a one-page design review template the team now runs before any release, and colleagues raise concerns earlier because they see their judgment shape the work. Outside my team, I built a slower relationship with a municipal IT officer I met at a digital services session in Amman. Over several months we traded feedback on each other's projects. She later invited me to co-design a chatbot for a public information rollout. I narrowed the scope to document queries, rewrote the privacy notice in plainer Arabic, and ran the pilot at two service desks serving roughly 1,000 residents in the first month. Her staff logged a noticeable drop in repeat counter visits for the same queries, and their notes surfaced two prompt fixes I would have missed alone. A digital rights advocate from a local tech forum now reviews our privacy checklist monthly; her flag on two data-minimisation clauses led me to shorten log retention from 90 to 30 days. At Edinburgh on the MSc Artificial Intelligence, I want to study audit methods for public-sector AI and ask peers in the Chevening AI and Governance group to critique a short Jordan case note. After returning, I will bring the revised note to our municipal partner and the advocate, trial one privacy safeguard on the next rollout, and review results together after three months.