Call for Papers

AI, Sovereignty, Law and Economics

Artificial intelligence is transforming the conditions under which power, economic resources, institutional authority, and decision-making are exercised, distributed, and regulated. The development and deployment of AI systems raise not only technological and social questions, but also fundamental legal and economic issues concerning sovereignty, regulation, responsibility, competition, ownership, autonomy, accountability, and control.

AI systems increasingly operate within infrastructures that cross national borders and involve both public institutions and private actors. Data, computational resources, language models, digital platforms, and other technological infrastructures are often developed and controlled by a limited number of large companies operating across multiple jurisdictions. This raises fundamental questions concerning the capacity of states and public institutions to regulate AI systems, the distribution of economic and technological power, and the conditions under which individuals, firms, and communities can exercise meaningful autonomy.

If sovereignty traditionally implies the capacity to exercise authority over a territory, a population, and the institutions governing social and economic life, how should this concept be understood in an environment in which essential technological infrastructures are privately owned, transnational, and increasingly mediated by artificial intelligence? To what extent can a state or linguistic community be considered technologically sovereign if it depends on data, AI models, computational infrastructures, or digital services developed and controlled elsewhere?

These questions also have important implications for law and economics. Who bears responsibility when decisions are made or mediated by AI systems? How should liability and accountability be allocated among developers, providers, deployers, public authorities, and users? How does the concentration of AI infrastructures affect competition, market power, and access to essential technological resources? What forms of regulation are appropriate when AI systems operate across jurisdictions and challenge traditional distinctions between public authority and private economic power?

This issue of Exetasis, an independent journal, aims to explore the relationship between AI and sovereignty from a legal, economic, sociolinguistic, and interdisciplinary perspective. It seeks to examine both the transformation of existing forms of sovereignty and the possibility that artificial intelligence may require a reconsideration of concepts such as regulatory authority, economic autonomy, accountability, competition, ownership, and technological sovereignty.

Contributions addressing, among others, the following topics are particularly welcome:

1. AI, Technological Sovereignty, and Economic Dependence
AI, state sovereignty, and technological dependence;

technological sovereignty and economic autonomy;

control over data, computational resources, language models, and digital infrastructures;

relations between states, public institutions, technology companies, and other private actors;

AI infrastructures and the distribution of economic and technological power;

the concept of “AI sovereignty” and its legal and economic implications;

technological dependence and the autonomy of states and linguistic communities;

concentration of AI resources and infrastructures within privately controlled systems;

strategic dependence on foreign AI technologies and infrastructures;

public and private control over critical AI resources;

AI and the changing relationship between territorial sovereignty and transnational economic power.

2. AI, Regulation, Authority, and Decision-Making
legal regulation of AI systems and algorithmic decision-making;

allocation of responsibility and accountability in AI-mediated decisions;

AI and public administration;

AI in education, the judiciary, and other public institutions;

the use of AI in the exercise of public authority;

the legitimacy of institutional decisions mediated or produced by AI systems;

algorithmic decision-making and administrative law;

transparency, explainability, and procedural fairness;

AI, due process, and access to justice;

liability for decisions and actions involving AI systems;

the relationship between human decision-making and automated systems;

cross-border AI systems and conflicts between different regulatory regimes;

the challenges posed by AI to existing concepts of jurisdiction and legal responsibility.

3. AI, Markets, Competition, and Economic Power
AI and the concentration of economic and technological power;

competition law and AI;

market power and access to computational resources;

AI and barriers to entry;

the economic consequences of concentration in AI infrastructures;

dominant firms and control over data, models, platforms, or computational capacity;

AI and the structure of digital markets;

mergers, acquisitions, and concentration in the AI sector;

access to data and computational resources as a condition of competition;

public procurement and the use of AI technologies;

economic dependence on private AI providers;

AI and the distribution of economic rents;

the relationship between innovation, competition, and regulation in AI markets;

the role of public investment and public infrastructure in reducing technological dependence.

4. AI, Data, Ownership, and Linguistic Resources
legal and economic governance of data used to develop AI systems;

ownership and control of linguistic and computational resources;

intellectual property and AI-generated or AI-assisted content;

copyright, training data, and language models;

access to data and the economics of AI development;

control over linguistic corpora and other language resources;

AI, linguistic diversity, and economic incentives;

minority languages and the distribution of technological resources;

the economic value of linguistic data;

private appropriation and public access to linguistic resources;

data governance and technological sovereignty;

the relationship between proprietary AI infrastructures and collective linguistic resources.

5. AI, Individual Autonomy, and Legal Protection
AI and individual autonomy;

predictive systems, recommendation systems, and automated influence;

AI and informational self-determination;

surveillance, personal data, and algorithmic monitoring;

AI and epistemic autonomy;

the relationship between human agency and automated decision-making;

algorithmic profiling and individual rights;

linguistic discrimination and algorithmic bias;

AI, equality, and non-discrimination;

language choice, identity, and AI-mediated communication;

accent, dialect, sociolect, and the representation of linguistic variation in AI systems;

consumer autonomy and AI-mediated markets;

the legal protection of individuals subject to automated decisions.

6. AI, Language, and the Reconfiguration of Sovereignty
theories of sovereignty and their application to AI and language;

sovereignty, power, and algorithmic control of linguistic practices;

distributed and transnational forms of technological and linguistic sovereignty;

the relationship between public sovereignty and private technological power;

AI and the transformation of the relationship between authority, autonomy, and control;

the production and regulation of linguistic practices through AI;

language ideologies and AI governance;

standardization, normalization, and algorithmic homogenization of language;

AI and the reproduction or transformation of linguistic and economic hierarchies;

the relationship between linguistic power and technological infrastructure;

the possible need for new legal and economic concepts to understand sovereignty, language, and power in the age of artificial intelligence.

7. AI Governance and New Models of Sovereignty
national and supranational approaches to AI governance;

AI regulation and the limits of territorial jurisdiction;

regulatory competition between jurisdictions;

international governance of AI infrastructures;

public-private governance of AI;

self-regulation, co-regulation, and public regulation;

the role of international organizations in AI governance;

AI and the transformation of the relationship between state authority and private economic power;

technological sovereignty as a legal and economic concept;

the relationship between digital autonomy, economic security, and state sovereignty;

new institutional models for governing transnational AI infrastructures;

the possible emergence of new forms of economic, technological, or institutional sovereignty.

The list of topics is not exhaustive. Contributions from law, economics, political economy, public policy, political theory, sociology, sociolinguistics, linguistics, linguistic anthropology, communication studies, ethics, epistemology, and related fields are particularly encouraged.

Abstract Submission
Authors are invited to submit an abstract of 300–500 words, accompanied by a brief biographical profile and institutional affiliation.

Abstracts should clearly present the legal, economic, sociolinguistic, or interdisciplinary question addressed, the main argument, and, where appropriate, the relevant theoretical and methodological framework.

Deadline for abstract submissions: December 20, 2026.

Abstracts should be sent to the Exetasis editorial board at:

editorial@exetasis.net

Please indicate the following in the subject line of the email:

CFP — AI and Sovereignty

Selected abstracts will subsequently be invited to submit a full paper of approximately 8,000 words. Full submissions will undergo the editorial evaluation process established by Exetasis.


Exetasis
Independent Journal