We tend to think of algorithms as technical objects – lines of code that sort, rank, filter, and recommend. But algorithms do something more fundamental than process data. They reshape how we communicate, what we communicate about, and whose voice gets heard. This is what algorithmic communication means: the reconfiguration of communicational practices, symbolic labour, and authority structures through algorithmic mediation.
The concept does not belong to computer science. It belongs to Information and Communication Sciences (ICS), where technologies are never studied as neutral instruments but as socio-technical configurations embedded in social logics, power relations, and organisational rationalities.
Beyond the Tool: Algorithms as Communicational Regimes
When an organisation deploys an AI system to generate reports, draft communications, summarise meetings, or evaluate performance, it is not simply adopting a productivity tool. It is installing a new communicational regime – a set of rules, filters, and priorities that determine what information circulates, in what form, and with what authority.
The French media scholar Yves Jeanneret described this dynamic through the concept of trivialité: the process by which ideas, texts, and knowledge are transformed as they circulate through different social and technical spaces. Every mediating device — a printing press, a social media platform, a Large Language Model — does not simply transmit meaning. It reconfigures it. It selects, stabilises, and redistributes what counts as meaningful.
Algorithmic communication takes this insight seriously. When a project manager asks ChatGPT to draft a stakeholder update, the resulting text is not a neutral reflection of the project’s reality. It is a product of statistical pattern modelling, shaped by training data, fine-tuning choices, and safety filters that remain largely opaque. The algorithm has made communicational decisions – about tone, emphasis, framing, inclusion, and omission – that would normally belong to a human author.
Three Dimensions of Algorithmic Communication
Algorithmic communication can be understood through three interrelated dimensions.
The redistribution of communicational authority. When organisations delegate symbolic production to automated systems, they redistribute who speaks, who decides what is said, and whose expertise is recognised. Bernard Migèe’s work on the social logics of communication technologies shows that every new medium reorganises the division of communicational labour. Algorithms are no exception: they shift authority from situated human judgment to statistical generalisation.
The transformation of symbolic labour. Symbolic labour – the work of producing, interpreting, and circulating meaning – has always been central to organisational life. Reports, emails, presentations, evaluations: these are not mere outputs. They are the communicational fabric that holds organisations together. When algorithms take over parts of this labour, they do not simply automate it. They transform its nature: from situated, relational, and context-sensitive to standardised, scalable, and pattern-driven.
The reconfiguration of ethical visibility. Not all values circulate equally in algorithmically mediated communication. My recent research comparing three LLMs (ChatGPT, Gemini, and Claude) through an Ubuntu ethical lens revealed a striking pattern: while values like Respect-Dignity and Compassion were relatively well articulated, Solidarity – the recognition of collective interdependence – was structurally marginalised across all three models. This is not a coincidence. Digital environments tend to individualise social experience, privileging personal resilience over collective bonds. Algorithms encode this tendency and amplify it.
Why It Matters for Organisations
For project professionals, team leaders, and anyone managing communication in digital environments, algorithmic communication is not an abstract concept. It is the daily reality of working with tools that silently shape what gets said and how.
Understanding algorithmic communication means asking different questions. Not just “is this tool efficient?” but “what communicational regime does it install?” Not just “does it produce accurate outputs?” but “whose voice does it amplify, and whose does it erase?” Not just “can we trust it?” but “what kind of trust does it make possible – and what kind does it foreclose?”
These questions are at the heart of what this platform explores. Algorithmic communication is not a sub-field of AI ethics. It is a lens for understanding how power, knowledge, and human relationships are reshaped every time an algorithm mediates between people.
Algorithms do not just process information. They reconfigure the conditions under which communication – and therefore collective life – becomes possible.