We recently had the chance to connect with Ashley Moore, a standout student in our MS in Applied Artificial Intelligence program, who presented two sessions at the 2025 Society of Quality Assurance Annual Conference in April, where she merged her professional background in quality assurance with her academic pursuit of gaining knowledge in applied artificial intelligence.
Moore presented two compelling sessions that explored the intersection of quality assurance and applied artificial intelligence. Her first session, “GPT on the Line: Revolutionizing Compliance for the GxP Auditor,” offered an interactive workshop where attendees co-developed real-time use cases with ChatGPT to enhance compliance practices through AI-generated audit tools and training plans.
The second session, part of a special symposium on AI, took a reflective turn with “Ethical AI Considerations in Pharma & Bio-tech,” where Moore prompted AI in a candid dialogue about its role in humanity’s future, sparking a powerful conversation on the ethical responsibilities tied to AI governance. Her contributions emphasized the importance of integrating ethics, collaboration, and community wisdom as AI continues to shape the future of regulated industries.
Taking a look at Ashley’s professional journey she brings a unique perspective to the field.
“I currently work in Biotech as a Quality Assurance Auditor specializing in bioanalytical studies at Smithers Pharmaceutical Development Services, where I also act as the QA Representative for our Computer System Validation (CSV) team. In this role, I help ensure our digital systems comply with FDA 21 CFR Part 11, GLP regulations, and GAMP 5 guidelines.”
As a graduate student in the Applied Artificial Intelligence program at the University of San Diego, she’s discovered a meaningful and pleasantly surprising synergy between her professional responsibilities and academic development.
“Some of the memorable foundational reading such as Artificial Intelligence: A Modern Approach by Russell and Norvig and What Is ChatGPT Doing … and Why Does It Work? by Stephen Wolfram rocketed my understanding of intelligent systems to the next level, from classical search strategies to the structure and function of large language models (LLMs).
“One concept I was especially excited to share during my recent presentation on generative AI in audit workflows was how language models process information using tokens which are discrete units of text that act as the building blocks for AI systems like ChatGPT to be able to respond to language in a realistic way. Expounding on this brought a lot of engagement and excitement from the audience. Many attendees, like myself at one point, assumed ChatGPT interpreted conversations in a human-like, intuitive way rather than by calculating the probability of the next best word. Sharing these “aha” moments added clarity and accessibility for those without a technical background.”
Meaningful discussions on real-world AI ethics, including algorithmic bias and system transparency in healthcare and compliance has stood out during her time in the MS-AAI program.
“One such discussion with a classmate left a lasting impression, which I also highlighted during my presentation to emphasize the value of intellectually rich, thought-provoking dialogue. I’m grateful to attend a university that fosters this kind of learning, encouraging us to think critically in both technical and humanistic terms. Experiences like these have shaped my passion for advancing explainable AI (XAI) in regulated environments, as I believe AI has much to offer when guided by ethical principles and protected by well-designed safeguards. I truly appreciate the opportunity to share my journey.”