My work in human-centered AI grows from longstanding research on narrative, identity, memory, philosophy, multilingual communication, and digital media. I examine how artificial intelligence systems interpret language, participate in storytelling, mediate personal and collective data, and influence learning and institutional practices.
This work combines scholarly inquiry with applied experimentation. It includes research and conference presentations on AI-assisted storytelling and archives, early curriculum development connecting machine translation and Python, AI-assisted program redesign, and the development of a digitally enabled entrepreneurial project.
The projects below demonstrate how I approach unfamiliar, interdisciplinary problems and how I translate the result into usable content, documentation, or systems.
Curriculum design · AI literacy · Machine translation · Cross-disciplinary collaboration
Challenge
As machine translation became part of students’ everyday work, language students needed to understand not only how to use these systems, but also how machine translation, coding, data, cultural knowledge, and human interpretation interact.
My role
In 2018, I conceived an interdisciplinary redesign of an advanced translation course. Working with a computer-science specialist, we co-designed a module connecting Python, machine translation, big data, artificial intelligence, and cultural interpretation.
Outputs
Measurable learning outcome in Python and machine translation
A design intended to be transferable to other liberal-arts courses
Significance
Developed before the current generative-AI boom, the project demonstrates my early engagement with AI literacy and human–machine communication. This approach continues to guide my work: people learn to use emerging technologies responsibly through experimentation, critical evaluation, and an understanding of where human context remains essential.
Data-informed strategy · Organizational change · Curriculum · AI-assisted analysis
Challenge
Two programs I directed required redesign to respond more effectively to changing student needs, enrollment patterns, curricular complexity, and institutional resource constraints. The goal was to improve coherence and efficiency while preserving educational quality and the distinctive strengths of each program.
My role
I led the analysis and redesign process. I identified the central problems, assembled and interpreted relevant evidence, consulted stakeholders, developed proposed structures, and translated the recommendations into materials for institutional review and implementation.
Outputs
Analysis of existing program structures and requirements
Student-centered pathways through the curriculum
Significance
This work demonstrates my ability to use AI as one component of a rigorous decision-making process—not as a replacement for expertise, but as a tool for organizing complex evidence, exploring alternatives, and accelerating responsible program development.
Entrepreneurship · Product strategy · Privacy-conscious storytelling
Challenge
Reusable products are designed to circulate among people, but their histories are normally lost as they move from one person to another. I wanted to create a product that could preserve and extend those human connections by tracking the product's journey through stories.
My role
I founded the company, developed the product concept, brand positioning, website structure, digital-storytelling model, user journeys, privacy requirements, moderation process, and technical documentation. Without a formal engineering background, I used AI-assisted development to translate the concept into product requirements, workflows, documentation, and a GitHub-ready web application package.
Outputs
Digital product-passport model
QR and NFC access and analytics requirements
Privacy and moderation requirements
GitHub-ready repository and deployment documentation
Significance
The project demonstrates my ability to move from an unfamiliar technical problem to a structured, documented digital product. It brings together entrepreneurship, narrative design, privacy, user experience, cross-cultural communication, and AI-assisted development.
Responsible AI · Narrative · Privacy · Testimony · Intergenerational data
Challenge
Generative AI can make personal and collective archives more searchable, accessible, and interactive. It can also remove stories from their original contexts, infer information about people who never consented, reproduce archival bias, or generate seemingly complete narratives from incomplete evidence. These risks become especially important when testimony concerns families, communities, trauma, political violence, or future generations.
My role
For the past decade, I have researched digital storytelling, collective memory, and the effects of technological platforms on personal and public narratives. Since 2023, I have increasingly focused on AI-assisted storytelling and archives through conference presentations, international research, and ongoing writing.
Outputs
Selected presentations include:
“Restituted Grandchildren and Intergenerational Data Rights: Ethical Safeguards for Digital Testimonies in Argentina in the Age of Generative AI.” UNESCO Symposium on the Principles for Ethical Use of Digital Testimonies of Victims and Witnesses of Mass Violence, June 2026.
📍 Paris, France
“Secrets Sequenced: Podcasting Family Genetics and the Narrative Turn in DNA Disclosure.” Narrative Conference, June 2026.
📍 Aarhus, Denmark
“AI-Assisted Algorithmic Networked Memory.” Modern Language Association Convention, January 2024.
📍 Philadelphia, PA
“Ethical Questions Raised by AI-Assisted Autobiographical Story Archives.” Modern Language Association Convention, January 2024.
📍 Philadelphia, PA
“Digital Collections of Personal Stories: Building Collective Intimacy.” Modern Language Association Convention, January 2022.
📍 Washington, DC
Significance
This project develops a human-centered framework for evaluating AI use in story archives. It emphasizes that responsible systems must account for context, relationships, and relational privacy. The work is relevant to responsible AI, model behavior, trust and safety, privacy, archival design, and the evaluation of systems operating in sensitive and culturally complex environments.