Brittany Johnson, PhD
Assistant Professor in CS
Director of the INSPIRED Lab @ GMU
Principal Researcher @ ChatBlackGPT
Data and Technology Activist
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About Me
I am Dr. Brittany Johnson-Matthews, directing the INSPIRED Lab at George Mason University. My work bridges software engineering, human-computer interaction, and artificial intelligence with interdisciplinary insights to investigate socio-technical problems and solutions pertaining to developer productivity and software development/use, such as tool support, work environments, ethics, and software for social good.
I got my Ph.D. from NC State in 2017 and a B.A. in CS from College of Charleston in 2011. My research focuses on socio-technical problems in software development and use—from AI tool support to ethical considerations in software for social good.
Beyond Research
Creativity drives my life outside academia. Whether painting canvases or painting my nails, I find joy in opportunities for artistic expression. I'm passionate about mentoring others to reach their potential while staying true to their roots.

Research Focus: Interdisciplinary approaches to developer productivity, responsible innovation, and society-centered technology
Research Projects
My research tackles critical challenges in modern software development and use through interdisciplinary approaches that prioritize human-centered design and ethical AI implementation
Trustworthy AI Assistants
AI assistants like ChatGPT and Copilot have become ubiquitous in software development and show great potential. However, there are several challenges that remain to be addressed which undermining trust in these tools, thereby hindering effective human-AI collaboration. Building on insights from prior work, this research investigates approaches for improving the reliability and usability of AI assistants for software development tasks such as code generation and vulnerability repair.
LLMs, Vibes, & Well-Being
There is a growing trend of using general-purpose large language models (LLMs), such as ChatGPT, in software development workflows. One emerging phenomenon is vibe coding, which refers to a fluid, intuitive, and emotionally attuned development style shaped by conversational AI tools, music, mood, and ambient factors. This research investigates the technical and psychological aspects of general-purpose LLM use to promote a more balanced and adaptable approach to LLM-driven software development.
Risk Reduction in Open Source Software
Open source innovations have become central to the modern software landscape. The distributed, voluntary, and fluid nature of open source software development introduces unique challenges when it comes to ensuring quality of contributions and outcomes. This research investigates state-of-practice and mechanisms for reducing risk in the development and use of open source software such as practical stability metrics, automated documentation maintenance and assessment support, and responsible engineering practices.
Practical AI Model Maintenance Training
Artificial intelligence (AI) models are increasingly deployed across diverse domains, yet maintaining these models—through tasks such as testing, debugging, and repairing—remains a significant challenge. Furthermore, it remains unclear how current computer science (CS) education prepares students for the maintenance of these systems. This research investigates the extent to which model maintenance concepts are integrated into computer science curricula, how they are presented to students, and what gaps may exist in current educational and training practices.
Foundations for Culturally-Informed AI
AI assistants (e.g., Gemini, ChatGPT) are powerful tools that can be integrated into various contexts. Unfortunately, the power and benefits afforded by AI assistants are not evenly distributed. Recent years have seen the introduction of culturally-informed AI -- systems capable of going beyond predominantly Western narratives and values to support engagement from more niche communities. This research explores the landscape of culturally-informed AI and ways we can facilitate responsible design and development of these systems.
Students & External Collaborators
My research and impact are significantly amplified through the brilliant minds I have the pleasure of working with. Here are the individuals who contribute to our shared vision and drive innovation forward.
Current Students
Ph.D. Student, 5th year
investigating trust and reliability in AI assistants used for code generation
Ph.D. Student, 4th year
studying impacts of AI assistants on software practitioner well-being and productivity
Ph.D. Student, 4th year
exploring tools and techniques for facilitating responsible open source and AI innovation
Ph.D. Student, 4th year
studying the role and impact of AI on collaboration in open source software development
Ph.D. Student, 3rd year
investigating mechanisms for facilitating global engagement and minimizing risk in OSS
Ph.D. Student, 3rd year
studying AI maintenance education and training in CS curriculum and beyond
Fatemeh Vares
Ph.D. Student, 3rd year
exploring use and reliability of AI assistants for vulnerability detection, explanation, and repair
Undergraduate Researcher
studying governance in open source AI communities and supporting research on AI assistant reliability
Collaborators
Lafayette College, Dept. of Computer Science
expert in human-centered software engineering and developer tools
ChatBlackGPT, Founder & CEO
AI technology expert specializing in culturally-informed AI
George Mason University, Dept. of Psychology
expert in employee well-being, burnout, and work-nonwork balance
Independent Researcher
expert in intersectionality theory and reflexive methods in technological processes
Software Engineer
expert in open source ecosystems
Past Students
MS in CS, 2023
Software Engineer at Midas
MS in CS, 2023
Data Engineer at eQual Public Benefit Corporation
Connect & Collaborate
Publications & Research Impact
My research spans software engineering, human-computer interaction, and artificial intelligence with publications in top-tier venues.
Get In Touch
Interested in collaboration, mentorship opportunities, or discussing interdisciplinary research in software engineering and AI? I'd love to hear from you.

Research Areas: Software Engineering, Human-Computer Interaction, Artificial Intelligence, Open Source Software Development, Developer Productivity