Artificial intelligence does not generate destructive conflicts from nothing. It does, however, transform their reach, speed and quality. Where communication can be automated, personalised and synthetically produced, trust, authenticity and shared reference points come under pressure.

AI as a Factor in Social Conflict Dynamics

Artificial intelligence fundamentally changes the conditions of digital communication. It generates content, organises visibility, personalises address and accelerates responses. AI is therefore not merely a technical tool, but a factor in social conflict dynamics. In social media, political public spheres, organisations and digital decision-making spaces, it can reinforce patterns of polarisation, manipulation and exclusion.

AI does not arise outside social conflicts, but is embedded in structures of attention, power, inequality and trust. It intensifies destructive dynamics where digital communication spaces are already oriented towards emotionalisation, visibility, speed and polarisation.

Scaling Destructive Dynamics

This double movement is particularly visible in social media. Platforms do not structure public discourse neutrally, but through selection, recommendation and control of reach. AI can significantly amplify these logics: content can be produced more quickly, varied with greater precision, emotionally sharpened and disseminated on a mass scale.

Destructive behaviour is not thereby invented anew, but rendered scalable. Insult, disinformation, propaganda, deception and coordinated outrage acquire a technical form that increases reach, speed and adaptability.

Digital Fairness and Diffusion of Responsibility

AI systems operate with data, classifications and models that do not simply leave social predispositions behind. They can reproduce distortions, distribute visibility unequally, disadvantage certain perspectives and technically stabilise existing inequalities. Digital fairness therefore means more than protection against overt discrimination. It concerns the question of who is seen, heard, accurately classified and fairly treated in digital spaces.

Governance thus becomes a core question of modern conflict management. AI distributes responsibility across multiple levels — developers, platforms, organisations, regulatory bodies and users — without responsibility always remaining clearly attributable. This diffusion of responsibility can promote destructive dynamics.

Polarisation and Identity Loading

Particularly problematic is the connection between AI and polarisation. Polarisation arises not only through false information, but through affective group formation, moral demarcation and the loss of shared reference points. AI can intensify these processes by personalising content, addressing target groups with precision and calibrating communicative stimuli towards outrage, fear or belonging.

Conflicts thereby become more heavily loaded with identity. The other side appears then not as the bearer of a different position, but as a threat to one's own group, order or truth. Conflicts lose their capacity to be addressed at the factual level and become struggles over recognition, interpretive authority and belonging.

The Crisis of Authenticity

A new quality arises through synthetic communication. Texts, images, voices, videos, profiles and conversational contributions can be produced without their origin, intent or authenticity being immediately recognisable. This changes the fundamental communicative trust. When it remains unclear whether a contribution originates from a person, a bot, a model or a coordinated campaign, authorship and responsibility begin to slide.

Deepfakes, synthetic voices and artificial texts shift the conflict question from the individual statement to the trustworthiness of the communicative situation itself. The central question then becomes: who can be trusted at all — the visible person, the audible voice, the plausibly formulated text or the technical environment in which communication appears? It is precisely here that authenticity itself becomes the object of conflict.

Epistemic Uncertainty

AI generates an additional conflict dimension: epistemic uncertainty. It becomes more difficult to establish collectively what has occurred, who has spoken, which source is credible and which statement can be verified.

Destructive behaviour in such an environment need not persuade directly. It can operate merely by sowing doubt, weakening trust, delegitimising procedures and eroding shared reference points. The damage lies not only in the individual piece of false information, but in the lasting destabilisation of whether public communication is reliable at all.

Consequences for Conflict Management

For conflict management, this entails a twofold task. On the one hand, existing destructive dynamics must be recognised: escalation, humiliation, exclusion, manipulation, disinformation and polarising intensification. On the other hand, the conditions under which these dynamics are technically amplified, automated and synthetically staged must be understood.

Conflict management can therefore no longer confine itself to conducting conversations or mediation in the narrow sense. It must include digital infrastructures, platform logics, algorithmic visibility, governance questions and trust architectures in its analysis.

The decisive challenge is to respond to destructive AI dynamics not solely through technical means. Detection systems, labelling requirements, moderation and regulation are necessary, but insufficient. The actual conflict concerns the conditions for successful public life: trust, transparency, fairness, responsibility and the possibility of justified mutual understanding.

Under conditions of artificially produced communication, conflict management becomes a practice that not only orders disputes, but protects the foundations of reliable mutual understanding.

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