Oct 2026· Zenodo (CERN European Organization for Nuclear Research)· 4 references
Ethics and Social Impacts of AI
Abstract
Artificial intelligence is collapsing the historical separation between statecraft and warcraft. This third volume of the series on Sovereign AI in the developing Global South examines how algorithmic systems are restructuring state authority in domestic governance and armed conflict. It first analyses "algorithmic statecraft": biometric digital public infrastructure and the risk of function creep, with India's Aadhaar and Kenya's Huduma Namba as cases, and predictive policing as a form of actuarial justice that can codify structural discrimination. The article then turns to "algorithmic warcraft": AI decision support systems used for target generation in Gaza, automation bias and the "triage trap" that hollow out meaningful human control, and bias in military AI. It traces the democratisation of lethality through commercial and AI-enabled drones in Myanmar, Sudan, Libya and the Sahel, Bangladesh's border-security modernisation in response to regional spillover, and generative AI as an instrument of cognitive warfare. It closes with the fractured diplomacy of the Global South in the UN Group of Governmental Experts on lethal autonomous weapons systems, and argues that sovereign resilience requires contextualised AI frameworks under strict civilian oversight together with a coordinated push for binding international norms.
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
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
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
In Compton Lecture, the distinguished legal scholar warns of potential “loss of the Enlightenment” while suggesting ways innovations can meet our civic and cultural needs.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
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