The expansion of artificial intelligence systems constitutes one of the foremost legal challenges of the twenty-first century. This article advances an original theoretical category: the principle of the anthropological sovereignty of law. According to this principle, final legal decisions producing legal effects, or comparably significant effects on fundamental rights, must remain attributable to a competent and accountable human decision-maker acting within the framework of law. Artificial intelligence may assist that decision-maker, but it cannot become an autonomous or parallel source of decisional authority. This requirement rests on the distinctively human capacity to understand the existential significance of legal conflict and to assume responsibility for its resolution. Two corollaries follow: the semantic irreducibility of law, according to which legal meaning cannot be reduced to computational output, and the human reserve of judgment, which gives the principle its institutional and procedural dimension. The article explains and defends the use of the term sovereignty in contrast to related concepts such as dignity, human centrality, and the primacy of the person. It then tests the thesis against some of the strongest arguments in favour of extensive reliance on artificial intelligence in legal decision-making, including Kahneman, Sibony and Sunstein’s theory of noise and Casey and Niblett’s proposal of microdirectives. The analysis subsequently applies this framework to Regulation (EU) 2024/1689 (the AI Act), interpreted as the most systematic legislative articulation to date, within European law, of the requirement of human control over algorithmic decision-making. The principle is then examined in relation to the principal legal professions — advocate, judge, civil-law notary and legal adviser — in order to identify what remains irreducibly human in the exercise of each function. The concluding section addresses the objection that the proposed category merely renames legal personalism. It argues, instead, that the principle of the anthropological sovereignty of law translates the axiological core of personalism into an operational legal category capable of responding to an interlocutor that traditional personalism never had to confront: artificial intelligence.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
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