CHI 2025
Bay Area
PhD
Edinburgh
Design Researcher / University of Edinburgh

Charlotte Bird

Studying how people adopt, trust, and use AI tools in creative work

01
File / Personnel
About
I'm a PhD candidate in Design Informatics at the University of Edinburgh and a Baillie Gifford Scholar at the Centre for Technomoral Futures. I study how people adopt, trust, and use AI tools in their work.
Education
  • PhD Design Informatics, Edinburgh
  • MSc Computer Science (AI), Newcastle
  • BA Literature, Newcastle
Skills
  • Research: Semi-structured interviews (40+), usability studies, contextual inquiry, diary studies, longitudinal research, surveys, benchmarking, thematic analysis, statistical analysis
  • Artifacts: Personas, journey maps, insight decks, design recommendations, stakeholder briefings, policy reports
  • Technical: Python, SQL, R, Qualtrics, Figma, Miro, MAXQDA; built full-stack research prototypes
  • AI expertise: 4 years studying AI adoption and trust; built AI tools; understand models technically
Collaborators

Four years leading primary research with creative practitioners.

Adobe BBC Turing Institute Ada Lovelace Institute UK Government
02
Record / Work
Experience
Student Researcher, AIUX Team Google DeepMind, London
Apr 2026 -- Oct 2026

Research role on creativity within the AIUX team.

Research Assistant Adobe & University of Edinburgh
2024 -- 2025

Partnered with Adobe to study how creative professionals adopt AI tools.

  • Longitudinal study with professional designers.
  • Co-authored publications upcoming at DIS and CSCW 2026.
Research Assistant BRAID Programme (BBC, Ada Lovelace Institute, AHRC)
2023 -- 2024

Qualitative research on generative AI adoption across creative industries, working directly with BBC and Ada Lovelace Institute stakeholders.

  • Outcomes include exhibitions and comprehensive map of UK AI artistry.
  • 20 interviews with AI artists (thesis content).
Research Assistant Ada Lovelace Institute & AHRC
2023

First deep dive into AI risks -- developed frameworks that informed both policy and product decisions.

  • Created a risk taxonomy for generative AI through structured review of 70+ sources across technical, legal, and social science domains.
  • Identified 3 systematic gaps in existing frameworks (dialect bias, ageism, moderation harms) with no prior empirical coverage.
  • Published at AIES 2023 (200+ citations); research directly informed UK Government policy on AI regulation.
03
Archive / Output
Publications
CHI
2026

From Blank Box to Creative Partner: Designing Ecological On-Ramps for First-Time AI Artists

C Bird, C Moruzzi, E Luger
PDFDOI
CHI
2026

Drawing the Drift: Visual Storytelling as Method for Human-AI Becoming-With

C Bird
PDF
DIS
2026

Mapping Imaginaries: A Futures Workshop for Creative Practices with Generative AI

P Bagchi, C Moruzzi, C Bird, KC Chan, B Dixon, L Herman, K Morrison et al.
PDFDOI
CSCW
2026

Exploring the Impact of AI-Powered Creativity Support Tools on Professional Creative Workflows

C Moruzzi, C Bird, L Herman
PDFDOI
CHI
2025

Diffraction, Creativity and AI: Towards New Methods for Design Research

C Bird
PDFDOI
CHI
2024

Artists and AI: Creative Interactions and Tensions

C Bird
PDFDOI
CHI
2024

Creativity, Ethics, User-Generated Content and AI

C Bird
PDF
AIES
2023

Typology of Risks of Generative Text-to-Image Models

C Bird, E Ungless, A Kasirzadeh
PDFDOI
ICCC
2023

Evaluating Prompt Engineering as a Creative Practice

C Bird
PDFDOI
Full list on Google Scholar
04
Index / Writing
Blog
Loading posts...