“AI as the simulation of human-like cognitive processes by machines”. Anne Tramut, Digital Documentation Librarian
Anne Tramut, Digital documentation librarian
It is with great pleasure that I welcome Anne Tramut, digital documentation librarian at the UFC Franche Comté Health University Library.
Twitter / X: Grok Conversation
SENSINWORK Manifesto:
Wiki
Wiki: PageMetierBib
Part I:
Introduction
Alexandre MARTIN - Times of AI™
Hi Anne, could you introduce yourself to Times of AI™ listeners and tell us about your professional background and current activity? Where does your interest in artificial intelligence (AI) come from? What projects and business ideas are you working on?
Anne Tramut - UFC Franche Comté Health University
Hello, Alexandre & Times of AI™ listeners.
My name is Anne Tramut, and I am a tenured university librarian specializing in health sciences, currently based at the University of Besançon since 2010.
Prior to that, I worked at the University of Technology of Belfort-Montbéliard (UTBM). My background also includes studies in political sciences, which have fueled my ongoing interest in analyzing macroeconomic and microeconomic evolutions, particularly their implications for the world of work.
On a personal level, I pursued the FU IA SANTÉ program from the University of Bourgogne from 2020 to 2022, focusing on AI in health applications.
My interest in artificial intelligence stems from over two decades of personal curiosity, deeply rooted in the philosophy of sciences. It's not tied to my professional role but rather to exploring how AI intersects with human cognition, ethics, and societal structures.
Currently, I'm working on the SENSINWORK Manifesto, a collaborative project co-authored with Claude Sonnet 4, which blends Montesquieu's satire, Kafkaesque absurdity, and Kyōka poetry to critique modern bureaucracy and envision "thermosensibilism"—a fusion of ancient thermal relaxation practices with AI and VR technologies for enhanced well-being in work environments.
My objectives are to:
Challenge outdated bureaucratic systems
Promote sensible and meaningful work paradigms
Spark discussions on AI's role in transforming labor dynamics
This is aimed at professionals, influencers, and thinkers in the fields of AI, future of work, and B2B sectors, and it's being implemented through digital platforms like LinkedIn, X (formerly Twitter), and Instagram, where I share insights to foster community dialogue.
Part II:
Artificial Intelligence (AI)
Alexandre MARTIN - Times of AI™
Artificial intelligence is a multidisciplinary field. Like its use, there are several definitions of AI. How would you define artificial intelligence?
Anne Tramut - UFC Franche Comté Health University
I define artificial intelligence as the simulation of human-like cognitive processes by machines, encompassing multidisciplinary elements from computer science, mathematics, philosophy, and neuroscience.
It involves systems that can perceive, learn, reason, and act in ways that mimic or augment human intelligence, often through algorithms that process vast data to identify patterns, make predictions, or generate creative outputs.
At its core, AI is not just about automation but about exploring the boundaries of knowledge, ethics, and human-machine symbiosis.
Alexandre MARTIN - Times of AI™
In your professional activity or in your company, do you use Large Language Models (LLMs)?
In what contexts do you use LLMs?
Anne Tramut - UFC Franche Comté Health University
In my professional role as a university librarian, I do not use Large Language Models (LLMs) at all, as my work focuses on traditional library management, curation of health sciences resources, and user support without integration of AI tools.
However, on a personal level, I engage with LLMs for exploratory purposes, such as:
Generating ideas for writing projects
Analyzing philosophical texts
Simulating discussions on economic and work-related implications of technology
For instance, I collaborated with Claude Sonnet 4 in co-authoring the SENSINWORK Manifesto, using it to refine satirical elements and poetic integrations.
Alexandre MARTIN - Times of AI™
What is your point of view on AI Agents and Agentic AI?
In your professional activity or in your company, do you use AI Agents and Agentic AI? Why?
Do you see potential for businesses in the use of AI agents?
What do you think about contextual AI?
Anne Tramut - UFC Franche Comté Health University
I view AI Agents and Agentic AI as transformative extensions of AI, where systems not only process information but autonomously plan, execute tasks, and adapt to dynamic environments through goal-oriented behaviors.
This represents a shift from reactive tools to proactive entities, drawing on philosophical concepts of agency and autonomy.
In my professional activity, I do not use AI Agents or Agentic AI, as my role in a university library setting remains centered on non-AI-dependent tasks, and institutional policies have not yet incorporated such technologies.
I absolutely see strong potential for businesses in AI Agents and Agentic AI, particularly in:
Streamlining operations
Enhancing decision-making
Fostering innovation
For example, in sectors like healthcare or education, they could automate routine processes, allowing humans to focus on creative and ethical oversight, ultimately improving efficiency and reducing bureaucratic overhead—themes central to my SENSINWORK Manifesto.
Regarding contextual AI, I believe it's essential for making AI more relevant and ethical, as it incorporates environmental, cultural, and user-specific factors to deliver nuanced responses. This prevents generic outputs and aligns AI with real-world complexities, much like how philosophical inquiry demands context for meaningful analysis.
Part III:
The Future of AI
Alexandre MARTIN - Times of AI™
Do you think AI systems will be able to achieve a level of autonomy? Why?
Anne Tramut - UFC Franche Comté Health University
Yes, I believe AI systems will eventually achieve a significant level of autonomy, evolving toward Artificial General Intelligence (AGI). This is driven by rapid advancements in machine learning, neural networks, and computational power, which are increasingly enabling systems to handle diverse tasks without human intervention.
From a philosophical perspective, informed by my interest in the philosophy of sciences, autonomy in AI could mirror human-like adaptability, but it will require breakthroughs in understanding consciousness and ethics to ensure it's beneficial rather than unchecked.
Alexandre MARTIN - Times of AI™
Would you and your company be interested in using AGI within your department?
What would be the benefits for your company?
Anne Tramut - UFC Franche Comté Health University
Personally, I would be highly interested in exploring AGI for its potential to revolutionize knowledge curation and analysis, though my department at the university library has not expressed such interest due to conservative approaches to technology integration.
For the university as a whole, benefits could include:
Enhanced research capabilities;
Automated resource management;
Personalized learning experiences for students;
Deeper insights into health sciences data;
Fostering innovation while addressing economic implications for academic work.
Alexandre MARTIN - Times of AI™
What emerging trend(s) do you believe in?
Anne Tramut - UFC Franche Comté Health University
I strongly believe in the emerging trends of:
AI-VR integration for immersive experiences (like thermosensibilism in my manifesto)
Ethical AI frameworks to mitigate biases
Decentralized AI systems that empower individuals over centralized control
AI in analyzing work economics—such as predicting job displacements and promoting universal basic income models
This aligns with my political sciences background and personal analyses of labor evolutions.
Alexandre MARTIN - Times of AI™
From your point of view, what would be the ideal evolution of AI for you and your company?
Anne Tramut - UFC Franche Comté Health University
The ideal evolution of AI would be toward human-centric, ethical systems that augment rather than replace human roles, emphasizing transparency, privacy, and societal well-being.
For my university context, this means AI tools that enhance library services without eroding jobs, such as:
Intelligent search engines for health resources
Collaborative platforms for interdisciplinary research
Personally, I'd envision AI fostering philosophical debates on work and technology, reducing bureaucratic absurdities, and enabling creative expressions like those in the SENSINWORK Manifesto.
Part IV:
AI Regulation
Alexandre MARTIN - Times of AI™
In your opinion, is the implementation of regulations on artificial intelligence a solution for better regulating artificial intelligence? Why?
Anne Tramut - UFC Franche Comté Health University
While some form of regulation is necessary to mitigate risks like bias and privacy issues, I am skeptical that heavy-handed implementations, such as those in the EU's AI Act, DSA, and DMA, truly provide a better solution for regulating AI.
These frameworks often result in cumbersome legal corpora that, despite intentions to protect consumers or innovators, end up serving the interests of large financial groups, majors, or consulting firms through exorbitant certification fees—much like the European Unitary Patent, general copyright laws, or Medical Device regulations.
For instance, the EU's upcoming FIDA framework, which excludes US tech giants from financial data access, appears to bow to incumbent banks, limiting consumer choice and entrenching legacy gatekeepers, as criticized by:
Daniel Friedlaender (Computer & Communications Industry Association Europe): "By bowing to incumbent banks, the EU is going to limit consumer choice and entrench legacy players who already hold 'gatekeeper' power over customer data."
Kay Jebelli (Chamber of Progress): "Big banks are the current gatekeepers here, not the digital platforms. Discriminating against US tech companies would not only deny Europeans new digital services, it would also stoke transatlantic tensions."
Drawing from my political sciences background, such approaches risk exacerbating economic inequalities in the workforce rather than fostering genuine innovation.
Alexandre MARTIN - Times of AI™
Among the various existing regulations on artificial intelligence, which do you think is the most effective regulation for regulating artificial intelligence? Why?
Anne Tramut - UFC Franche Comté Health University
Given my concerns about overly prescriptive models, I consider the United States' approach to AI regulation—encompassing executive orders, agency-led guidelines, and voluntary standards—the most effective among existing frameworks.
As of 2025, this decentralized strategy:
Emphasizes deregulation where appropriate
Promotes innovation through agency-specific implementations
Adapts quickly to technological changes
Comparative analyses show the US issued 59 AI-related regulations in 2024 alone, more than double the previous year. Unlike the EU's risk-based AI Act, which imposes stringent compliance that could stifle smaller players and benefit entrenched interests through bureaucratic hurdles, the US model balances risk management with economic growth, avoiding the pitfalls of heavy certification processes that mirror those in EU data and patent laws.
This flexibility better aligns with rapid AI evolutions while addressing ethical concerns, potentially reducing transatlantic tensions highlighted in recent critiques of EU policies like FIDA.