My research revolves around one persistent concern: what happens to knowledge adoption, human communication, learning, and labor when a technology mediates the relationship. I began with technology-mediated communication, moved into eLearning, and now work primarily on the implications of artificial intelligence across higher education, workforce readiness, and the future of work. This progression reflects one continuous intellectual trajectory rather than three distinct ones.
The digital divide runs through all of it. Every mediating technology distributes its benefits unevenly. I am particularly interested in who is left on the disadvantaged side of that distribution and how to address it, as well as what the resulting gap does to communication, learning, employment, and society at large.
In eLearning, particularly asynchronous instruction, I focus on a design challenge that remains unresolved: how to deliver instruction that is genuinely effective yet economical enough to scale. Moreover, too often, institutions leave it to faculty to develop and subsidize the cost, even though it is the institution that captures the value.
The effects of artificial intelligence
Regarding artificial intelligence in higher education, two primary questions occupy my work. The first is epistemological: are students truly learning when they employ AI, or has the appearance of learning replaced its substance? The second, and more consequential, is curricular: what should universities be teaching? Higher education continues to prioritize knowledge and skills that automated systems now execute faster and at minimal cost. If graduates can only reproduce what machine models generate, their professional value proposition collapses. How curricula must adapt to uniquely human capabilities (and precisely define those capabilities) remains an urgent institutional challenge.
The transformation of work and labor represents the operational half of this dilemma. The economic and structural shifts brought on by AI will likely surpass those of the Industrial Revolution. What form these disruptions take, how they are distributed across occupations and skill levels, and who captures the resulting gains are the central questions driving my current projects.
The uses of artificial intelligence
When a model contributes to a work, the question is not whether the output is original but who holds authorship of the judgment behind it. Alongside that conceptual question, I study what these systems can be trusted to do in practice, from grading academic work to detecting objects in aerial imagery, and where their reliability breaks down. The applied studies are collaborations with colleagues in China and are methodological as much as substantive.
The digital divide
Every mediating technology distributes its benefits unevenly. I am interested in who ends up on the disadvantaged side of that distribution, what the resulting gap does to communication, learning, and employment, and what it would take to close it. Part of this work is historical, including an ongoing study of computing in Cuba.
Method
I use both quantitative and qualitative approaches, including survey design, structural modeling, semi-structured interviews, conceptual and scenario analysis, and historical inquiry.
Current projects
Nine manuscripts are under review at peer-reviewed journals as of August 2026. Target venues are not listed, since submissions move.
Artificial intelligence, labor, and the economy
- Ferran, C., & Ferran-Heredia, J. I. The AI revolution and the future of labor, wages, and value appropriation: Historical lessons and forward projections.
- Ferran, C. The bifurcated future: Capital concentration versus public appropriation in the age of artificial intelligence.
- Ferran, C. Technological stewardship in the machine age: An integrative ethical framework for AI governance via Magnifica Humanitas.
Higher education
- Ferran, C., & Cooney, M. A. The shared governance-speed dilemma: How university presidents navigate generative AI integration.
- Ferran, C., & Heredia-Ferran, M. H. What students obtain from university: An integrative framework for understanding multidimensional college outcomes and institutional stratification.
Knowledge management
- Ferran, C. Teams or communities, twenty-five years later: Knowledge management in the platform and AI era.
Computing history and the digital divide
- Díaz Batista, J. A., & Ferran, C. Cuba’s computing history: Human capital, knowledge durability, and technological capability under structural exclusion, 1959–2023.
Applied computer vision
- Shan, D., Zhang, M., Ferran, C., Liu, D., & Zhang, T. ISWO-APF: A hierarchical 3D path planning algorithm based on improved spider wasp optimization and artificial potential field for multiple UAVs.
- Shan, D., Qiu, Z., Cai, D., Ferran, C., Tong, X., & Liu, D. Bridging the scale gap: A multi-scale feature enhancement framework for UAV aerial image object detection.
Representative work
Nine published works, grouped by line of inquiry. The complete record is on the curriculum vitae.
Technology-mediated communication
- Ferran, C., & Watts, S. (2008). Videoconferencing in the field: A heuristic processing model. Management Science, 54(9), 1565–1578.
Knowledge management
- Ferrán-Urdaneta, C. (1999). Teams or communities? Organizational structures for knowledge management. In Proceedings of the ACM SIGCPR Conference on Computer Personnel Research (pp. 128–134). Association for Computing Machinery. Cited in more than three hundred academic articles.
The digital divide
- Ferran, C., & Salim, R. (2008). Fragilidad pragmática: ¿Las tecnologías de la información reducen el subdesarrollo o se adaptan a él? Economía, 33(25), 13–45.
- Ferran, C., & Ferran, B. (2008). El análisis regional frente al avance tecnológico y la redistribución espacial de actividades económicas. Revista BCV, 22(1), 137–162.
- Ferran, C., & Salim, R. (2003). The Internet and the digital divide. Asian Information-Science-Life, 2(1).
Higher education and online instruction
- Ferran, C., Alanís González, M., Esteves, J., Gómez Reynoso, J. M., & Guzmán, I. (2019). AMCIS 2017 panel report: Experiences in online education. Communications of the Association for Information Systems, 45, 1–17.
- Zhao, J., & Ferran, C. (2016). Business school accreditation in the changing global marketplace: A comparative study of the agencies and their competitive strategies. Journal of International Education in Business, 9(1), 52–69.
Artificial intelligence
- Ferran, C. (2026). The politics of creative attribution: Generative artificial intelligence, human agency, and the ethics of co-creation. AI and Ethics, 6(5), 469. https://doi.org/10.1007/s43681-026-01320-y
Collaboration
I am always interested in scholarly collaboration. If your research intersects with any of these questions, I welcome inquiries regarding joint projects, manuscript development, and interdisciplinary dialogue across all career stages. Write to [email protected].