Designing Sustainable Decisions: UX and Data Visualisation for a GenAI-Powered Sustainability Tool

Context:
Every product carries an environmental story — the energy extracted, the materials consumed, the emissions released across its entire life. Life Cycle Assessment (LCA) is the established methodology for mapping and quantifying that story, tracking impacts from raw material extraction through manufacturing, use, and end of life. Yet despite its importance, LCA remains largely invisible to the engineers and designers who make the decisions that matter most. It is slow, specialist, and typically arrives too late in the design process to influence outcomes.

This internship addresses that gap directly. Researchers at the German Research Center for Artificial Intelligence (DFKI) — a core partner in the STELEC project — have developed a GenAI-powered tool that enables engineers to sketch out high-level life cycle analyses through natural language conversation, requiring no specialist LCA knowledge. The tool is already being tested with teams developing wearable technologies.

Aims:
This project seeks to address the question: what should engineers see, and how should they see it, to make the best sustainability decisions? The researcher will explore how to redesign the user experience of this GenAI sustainability tool — specifically, how to visualise complex, dynamic life cycle data in ways that are clear, compelling, and genuinely useful to hardware engineers in the early stages of product development. This internship is a live research collaboration between Imperial’s Strategic Futures Design Lab and DFKI, embedded within the STELEC project.

This is a genuinely hard design problem. LCA data is inherently complex: it involves multiple impact categories, uncertainty ranges, temporal change, and trade-offs between competing environmental priorities. Most existing sustainability dashboards present a single score or a simplified summary — but this can obscure the very uncertainties and trade-offs that designers most need to understand. The challenge is to represent that complexity honestly and usefully, without overwhelming or misleading the user.

The student will lead this work, and approach this challenge through human-centred design research — generating and testing UX concepts and data visualisation approaches, from early sketches through to interactive prototypes, working alongside researchers and real users. They will draw on the intersection of human-computer interaction (HCI), information design, and sustainable design thinking.

The research will contribute to the growing academic literature on sustainability decision support tools, data visualisation for environmental communication, and the design of AI-assisted engineering tools. It will also produce directly usable design outputs for the STELEC project’s ongoing tool development. The internship will culminate in co-authorship of an academic paper and a non-expert-facing blog post / news article.

This project is significant not only for e-textiles but for sustainable design more broadly. As AI tools increasingly enter the engineering design process, the question of how environmental data is framed and presented will shape the sustainability decisions of the next generation of products.