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The current evolution of Artificial Intelligence, particularly Generative AI, represents a pivotal moment in technology—one that I believe is as significant as the rise of the internet. My journey in User Experience and Information Architecture began in the early 2000s, a period of rapid development where we were defining the very first interaction patterns for the digital world. I see a parallel dynamism in AI today. I am deeply motivated to contribute my experience to help shape the new, intuitive, and human-centred interaction patterns these advanced systems require. This involves not only leveraging my expertise to create effective interfaces but also addressing the specific complexities inherent in machine learning and generative AI. Key considerations in my approach include ensuring system alignment with human goals and values, mitigating potential risks such as skills degradation, critically evaluating the limitations of current AI capabilities, and strategically integrating robust human-in-the-loop frameworks for the responsible development, ongoing evaluation, and ethical governance of these intelligent systems.
This section showcases key projects undertaken as part of my focused learning and practical application in the field of Artificial Intelligence. These endeavours reflect a commitment to understanding not just the technological capabilities of AI, but also the critical aspects of designing systems that are effective, ethical, and work seamlessly with human users.
Below, you will find summaries of these projects, each with a link to a more detailed exploration of the methodologies, insights, and outcomes.
HCI for AI Systems Design – University of Cambridge
HCI for AI Systems Design – University of Cambridge
This project was undertaken as part of the "Human-Computer Interaction (HCI) for AI Systems Design" course at the University of Cambridge. The focus was on developing a systematic approach to designing complex AI-driven systems within a manufacturing context. Key aspects included function modelling, defining human-AI system boundaries, automation and interaction strategy development, risk assessment, and ensuring interpretability and ethical governance.
The project culminated in a detailed design report for an AI system intended to predict and manage machine failures, optimise resource allocation, and enhance operational efficiency, all while keeping the human operator central to the decision-making process.
Read the full project write-up and key learnings here
Capstone LLM Project – Google AI Intensive
Capstone LLM Project – Google AI Intensive
This capstone project was developed for the "Gen AI Intensive Course with Google," a programme focused on the practical application of generative AI capabilities. My project, presented as a Kaggle notebook, involved the creation of an AI art coach powered by a Large Language Model (LLM).
The Art Coach is designed to provide users with timed creative prompts and exercises, drawing inspiration from a curated selection of classic art textbooks. Artists can engage with these exercises offline, then photograph and upload their work along with any personal notes. The LLM then analyses the submitted artwork and commentary to offer personalised suggestions for engaging and enjoyable follow-on creative activities. This demonstrates a practical application of LLMs for personalised learning and creative augmentation.
This project showcased the ability to translate theoretical AI knowledge into a tangible, interactive tool and navigate the end-to-end development of an AI-focused endeavour.
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