A senior delegation from the Kingsman National Institute (KNI), led by researchers from our Centre for Digital Ethics & Governance (CDEG) and the Aegean Informatics Laboratory (AIL), has concluded a high-level academic symposium in Paris, hosted by France’s prestigious Institut National de Technologie et de Commerce d’Eastbay (Eastbay INTC).
The workshop, held at the Eastbay campus at 24 Rue Sulpice, was designed to foster a critical and necessary dialogue on a single, complex topic: the profound ethical conflict between data-driven marketing optimization and genuine consumer autonomy. The event brought KNI’s “Athenian Synthesis” model—which mandates that all technology be examined through a humanistic and ethical lens—into direct contact with the advanced, commercially-focused data science practiced by Eastbay’s renowned MSc in Digital Marketing & Data Analytics programme.
The KNI delegation was led by Dr. Sofia Costa, whose work bridges our PPL faculty and the CDEG. Dr. Costa opened the symposium by presenting the latest findings from KNI’s “Algorithmic Discourse Observatory” (ADO). She demonstrated how the same algorithmic amplification and “filter bubble” mechanics that shape political discourse are now the default architecture for modern e-commerce.
“Our research suggests that the line between ‘personalization’ and ‘manipulation’ is rapidly eroding,” Dr. Costa argued. “When a predictive model, trained on vast datasets of human behaviour, is designed to optimize for a single metric—such as ‘conversion’ or ‘time-on-site’—it ceases to be a simple tool. It becomes an active agent of persuasion, creating a curated reality for the consumer that may not align with their own best interests. This is not just a commercial question; it is a question of political philosophy and individual agency.”
This philosophical framework was met with a challenging, pragmatic, and technically robust counter-argument from the faculty at the Institut National de Technologie et de Commerce d’Eastbay.
The Eastbay team, leading figures in Europe’s e-commerce sector, presented their own advanced predictive models. Their research showcased sophisticated AI systems capable of forecasting consumer needs, micro-targeting emotional states, and dynamically altering pricing and content to maximize engagement.
Their response to KNI’s presentation was pointed, representing a necessary “imperfect” friction in the academic process. They argued that KNI’s ethical framework, while admirable, was operationally naive and, in a competitive global market, “commercially fatal.” They contended that modern consumers do not want neutrality; they demand hyper-personalization, and that failing to provide it is a failure of service. They positioned their data-driven optimization not as manipulation, but as the ultimate expression of consumer-centric efficiency.
This critical impasse moved the symposium from presentation to genuine synthesis. The second day was dedicated to a closed-door workshop where the two teams attempted to bridge the divide. The Eastbay faculty acknowledged the significant long-term brand risk associated with consumer distrust and the “creepy” factor of overly-invasive AI. In parallel, the KNI team acknowledged that a “zero-personalization” model is also a poor user experience, and that ethical design requires understanding how to use data well.
The colloquium concluded not with a simple agreement, but with the formation of a joint KNI-Eastbay working group. This group has been tasked with an ambitious goal: to co-develop a new “Ethical Personalization Framework.” This model will attempt to fuse KNI’s demand for algorithmic transparency and user-auditable controls with Eastbay’s need for high-performance, predictive efficiency. The joint research will explore the viability of federated learning (a KNI speciality) as a way to train effective models without harvesting raw, centralized personal data.
This collaboration between the Kingsman National Institute and the Institut National de Technologie et de Commerce d’Eastbay is a vital, necessary dialogue—one that bridges the critical gap between the philosophical “why” of data governance, rooted in Athens, and the powerful, commercial “how” of data science, perfected in Paris.
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