Julien Cloarec

Full Professor of Quantitative Marketing

Bio

About Me

I am Full Professor of Quantitative Marketing at iaelyon School of Management, Université Jean Moulin Lyon 3, France.

As an internationally recognized expert in artificial intelligence, I am dedicated to ensuring AI can be deployed without compromising user privacy. I collaborate with regulatory bodies, professional associations, and academic institutions to raise awareness, influence policy, and promote responsible AI development that balances innovation with privacy protection.

My work has been published in numerous journals such as Technological Forecasting and Social Change, Technovation, Journal of Business Research, Psychology & Marketing, and Transportation Research Part A.

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Research

Responsible Artificial Intelligence

My research focuses on the intersection of responsible AI, privacy, and technology adoption, particularly addressing the psychological and ethical challenges linked to AI-powered innovations. I explore how users navigate the personalization-privacy paradox, balancing the benefits of personalization with privacy concerns. Additionally, I investigate the psychological barriers and algorithmic aversions that impact the adoption of AI technologies, such as brain-machine interfaces and autonomous vehicles.

AI-Powered Personalization

Medical Artificial Intelligence

Transportation and Smart Cities

Sustainable Artificial Intelligence

List of Publications

Click on a publication in the list to directly access the PDF

Gordillo Chávez, D., Cloarec, J. and Meyer-Waarden, L. (2024), Opening the Moral Machine’s Cover: How Algorithmic Aversion Shapes Autonomous Vehicle Adoption, Transportation Research Part A: Policy and Practice

Cloarec, J., Meyer-Waarden, L. and Munzel, A. (2024), Transformative Privacy Calculus: Conceptualizing the Personalization-Privacy Paradox on Social Media, Psychology & Marketing

Cloarec, J., Cadieu, C. and Alrabie, N. (2024), Tracking Technologies in eHealth: Revisiting the Personalization-Privacy Paradox through the Transparency-Control Framework, Technological Forecasting and Social Change

Cloarec, J., Macé, S. and Pauwels, K. (2023), Artificial Intelligence Serving Decision-Making in Marketing, Décisions Marketing

Cloarec, J. (2022), Privacy Controls as an Information Source to Reduce Data Poisoning in AI-powered Personalization, Journal of Business Research

Cloarec, J., Meyer-Waarden, L. and Munzel, A. (2022), The Personalization–Privacy Paradox at the Nexus of Social Exchange and Construal Level Theories, Psychology & Marketing

Meyer-Waarden, L. and Cloarec, J. (2022), “Baby, You Can Drive My Car”: Psychological Antecedents that Drive Consumers’ Adoption of AI-powered Autonomous Vehicles, Technovation

Meyer-Waarden, L, Cloarec, J., Adams, C., Aliman, D. N., and Wirth, V (2021), Home, Sweet Home: How Well-Being Shapes the Adoption of AI-Powered Apartments in Smart Cities, Systèmes d’Information et Management

Cloarec, J. (2020), The Personalization-Privacy Paradox in the Attention Economy, Technological Forecasting and Social Change

Data Science

I am an internationally renowned data science instructor, catering to a diverse range of stakeholders.

Statistics

Specializing in the collection, organization, analysis, interpretation, and presentation of data, statistics is the foundation for making informed decisions.

Machine Learning

Focusing on developing computer algorithms that continuously improve through experience and the use of data, machine learning drives intelligent automation.

NLP

Engaging in the interactions between computers and human language, natural language processing blends linguistics, computer science, and AI to enhance communication.

Computer Vision

Exploring how computers gain high-level understanding from digital images or videos, computer vision is at the intersection of various scientific disciplines, pushing the boundaries of visual perception.

Frequently Asked Questions

Find answers to commonly asked questions about my research, supervision, and collaboration opportunities.

How can I apply for a PhD under your supervision?

If you’re interested in pursuing a PhD under my supervision, I strongly encourage you to reach out to me before starting your Master’s thesis. I prefer to supervise Master’s students who are considering continuing with a PhD under my guidance. You can either join a Master’s program at iaelyon School of Management for your thesis, or ensure that your institution allows for external supervision.

Do you offer internships or research assistant positions?

Occasionally, I do offer internships or research assistant positions for students who are eager to gain hands-on experience in my research areas. These opportunities are typically reserved for students who have demonstrated a strong academic background and a keen interest in my work. Please contact me with your CV and a brief statement of interest if you would like to explore this possibility.

What’s the best way to learn programming?

I don’t recommend generic online courses. The best way to learn programming is by doing. Start by asking yourself, « What do I want to achieve? » Once you have a goal, search for existing code notebooks or examples online that are related to your objective. Experiment with them, understand how they work, modify the code, and observe the outcomes. This hands-on approach is the most effective way to learn.

Can you provide data science training for my organization?

Yes, I have extensive experience as a data science instructor, having trained a wide variety of audiences, from research labs to corporate teams, on how to effectively leverage data science. Please contact me to discuss how we can tailor a training program to meet your organization’s specific needs.