I believe technology should be evaluated not only by what it can do, but by how well it serves the people who depend on it.
Explore my work: AI Response Quality Evaluation — case studies and scoring rubric
I'm a human services professional, disability advocate, and technology evaluator transitioning into AI quality assurance and responsible AI.
My professional background spans client intake, case documentation, digital literacy, public benefits, and disability advocacy. During my AmeriCorps service with Delaware State Libraries, I prepared an assessment of the Northstar Digital Literacy program, applying analytical and reporting skills to a real-world technology initiative.
Living with a disability has also shaped my perspective. Adaptability, problem-solving, and recognizing barriers are not simply professional interests for me; they are skills I've developed throughout my life.
- AI response evaluation and quality assurance
- Large language model (LLM) testing
- Accuracy, consistency, and error identification
- Responsible AI and algorithmic fairness
- Accessibility and inclusive technology
- Human-centered evaluation and documentation
- Analytical evaluation: Assessing technology and documenting findings
- Quality and accuracy: Careful reading, structured review, and attention to detail
- Human-centered judgment: Understanding the consequences of technology decisions for real people
- Documentation: Experience with client records, reports, and data management
- Accessibility: Disability advocacy and practical understanding of barriers to technology use
- A.A.S. in Human Services — Delaware Technical Community College
- CompTIA A+ Certified
- CompTIA ITF+
- Google AI Essentials
- Google/Coursera training in responsible AI
- Partners in Policymaking — Delaware Developmental Disabilities Council
I am a member of the Tech Council of Delaware and actively follow discussions surrounding AI governance, accountability, accessibility, and the responsible adoption of emerging technologies.
This GitHub profile documents independent projects demonstrating AI evaluation methods, structured quality reviews, accessibility analysis, and evidence-based recommendations. Two completed case studies are available in my AI Response Quality Evaluation repository.
My goal is to make my evaluation process transparent, reproducible, and useful to organizations developing trustworthy AI systems.
Based in Wilmington, Delaware | Interested in remote AI evaluation, quality assurance, and responsible AI opportunities.