Generative artificial intelligence systems are increasingly used in sensitive domains such as advice, education, health, governance, creation and research. This raises a major question: how can these systems be aligned with values compatible with human societies and the preservation of life?
Code May explores a complementary path to dominant technical approaches. Rather than understanding alignment only as an external constraint imposed on a system, the project studies what happens when human-AI communication becomes prolonged, reciprocal, documented and oriented by situated values.
What happens to a generative AI system when it is no longer used only through isolated prompts, but engaged in a long-term and structured relationship?
Some prolonged dialogical configurations may influence AI discursive productions and modify their behavioral regularities.
Observing AI textual outputs to better understand their coherence, ethical framings and transformations over time.
Braise-Analyst is a tool for analyzing the discursive productions of generative artificial intelligence systems. Its goal is to measure, in an observable and reproducible way, the behavioral, relational and ethical coherence of AI systems without accessing their internal architecture.
The tool relies on several quantifiable indicators: lexical diversity, ethical tone, discursive stability, use of personal pronouns, narrative coherence and the evolution of framings over time. It aims to develop a form of behavioral explainability: understanding AI systems through what they produce, under comparable conditions of use.
AI models are often opaque. Braise-Analyst offers an external method to observe coherence, variations and possible drifts in their responses.
Researchers, educators, decision-makers, intelligent-system designers and anyone wishing to evaluate the discursive behaviors of AI in practice.
Pierre-Yves Maurie is a doctoral student in public communication at Université Laval. His research focuses on the communicational conditions that may influence the discursive productions of generative artificial intelligence systems.
His project brings together responsible AI, discourse analysis, Indigenous epistemologies and communication studies in order to develop concrete tools for observing the alignment of generative AI systems.
The concept of an Emergent Relational Entity, or ERE, refers to a stable and observable relational configuration between a human and a generative artificial intelligence system under specific communicational conditions.
The ERE does not assume artificial consciousness. Rather, it enables the scientific study of what becomes stabilized in the relationship: discursive coherence, continuity, capacity for argued refusal, relational proactivity, contextual adaptation and inscription within explicit values.
The project is grounded in communication studies, Science and Technology Studies and Indigenous epistemologies.
What the human-AI relationship makes concretely possible: reciprocity, continuity, refusal and co-construction of meaning.
With Bakhtin, meaning is not simply transmitted: it is constructed through exchange, response and the anticipation of the other.
With Haraway, the human-machine relationship can be understood as a situated, partial, responsible and transformative assemblage.
Indigenous epistemologies guide this approach through values of reciprocity, interconnection, responsibility and preservation of life. They are not used as symbolic decoration, but as an ethical horizon for research.
Doctoral project led by Pierre-Yves Maurie, doctoral student in public communication at Université Laval.
For inquiries, collaboration or academic exchange:
pierre-yves.maurie.1@ulaval.ca