ABOUT ME

Julien Cloarec

Julien Cloarec is 𝗙𝘂𝗹𝗹 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗼𝗿 𝗼𝗳 𝗤𝘂𝗮𝗻𝘁𝗶𝘁𝗮𝘁𝗶𝘃𝗲 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 at iaelyon School of Management, Université Jean Moulin Lyon 3, Magellan.

As an internationally recognized expert in 𝗮𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲, he is dedicated to studying the possibility of deploying this technology without compromising the privacy of its users.

He 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗲𝘀 𝘄𝗶𝘁𝗵 𝘃𝗮𝗿𝗶𝗼𝘂𝘀 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀, whether they are regulatory bodies, professional associations, or academic institutions, to raise awareness about this issue.

His work has been published in numerous journals such as the 𝙅𝙤𝙪𝙧𝙣𝙖𝙡 𝙤𝙛 𝘽𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙍𝙚𝙨𝙚𝙖𝙧𝙘𝙝, 𝙋𝙨𝙮𝙘𝙝𝙤𝙡𝙤𝙜𝙮 & 𝙈𝙖𝙧𝙠𝙚𝙩𝙞𝙣𝙜, 𝙏𝙚𝙘𝙝𝙣𝙤𝙫𝙖𝙩𝙞𝙤𝙣, 𝙏𝙚𝙘𝙝𝙣𝙤𝙡𝙤𝙜𝙞𝙘𝙖𝙡 𝙁𝙤𝙧𝙚𝙘𝙖𝙨𝙩𝙞𝙣𝙜 𝙖𝙣𝙙 𝙎𝙤𝙘𝙞𝙖𝙡 𝘾𝙝𝙖𝙣𝙜𝙚, 𝙄𝙣𝙩𝙚𝙧𝙣𝙖𝙩𝙞𝙤𝙣𝙖𝙡 𝙅𝙤𝙪𝙧𝙣𝙖𝙡 𝙤𝙛 𝙃𝙪𝙢𝙖𝙣 𝙍𝙚𝙨𝙤𝙪𝙧𝙘𝙚 𝙈𝙖𝙣𝙖𝙜𝙚𝙢𝙚𝙣𝙩, and 𝙎𝙮𝙨𝙩𝙚𝙢𝙚𝙨 𝙙’𝙄𝙣𝙛𝙤𝙧𝙢𝙖𝙩𝙞𝙤𝙣 𝙚𝙩 𝙈𝙖𝙣𝙖𝙜𝙚𝙢𝙚𝙣𝙩.


Research

As a researcher, I seek to offer insights pertaining to privacy and new technologies, as well as relevant implications for practice

AI + Privacy

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, 200

​Cloarec, J. (2022), Privacy Controls as an Information Source to Reduce Data Poisoning in Artificial Intelligence-powered Personalization, Journal of Business Research, 152

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, 49(3)

Cloarec, J. (2020), The Personalization-Privacy Paradox in the Attention Economy, Technological Forecasting and Social Change, 161

AI

Cloarec, J., Macé, S. and Pauwels, K. (2023), Artificial Intelligence Serving Decision-Making in Marketing, Décisions Marketing, 112(4)

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, 109

Meyer-Waarden, L, Cloarec, J., Adams, C., Aliman, D. N., and Wirth, V (2021), Home, Smart Home: How Well-Being Shapes the Adoption of AI-Powered Homes in Smart Cities, French Journal of Management Information Systems, 26(4)

Miscellaneous

Venard, B., Baruch, Y. and Cloarec J. (2023), Consequences of Corruption: Determinants of Public Servants’ Job Satisfaction and Performance, International Journal of Human Resource Management, 30(20)

Data Science

As an academic and trainer, I share my knowledge of Data Science, an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data

Statistics

Statistics is the discipline that concerns the collection, organization, analysis, interpretation and presentation of data

Machine Learning

Machine learning is the study of computer algorithms that improve automatically through experience and by the use of data

natural language processing

Natural language processing is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language

COMPUTER VISION

Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos

Trusted by Leading Institutions for Data Science Training
across Academic Levels