Oct 2026· Proceedings of the ACM on Human-Computer Interaction· Vol 10, pp. 1 - 33· 0 citations· 160 references
Ethics and Social Impacts of AI
Abstract
As generative AI (GenAI) technologies become increasingly integrated into professional settings, it is critical to understand how these tools are experienced by individuals who are more likely to encounter harm, violence, and trauma in the workplace. Black women, in particular, continue to face systemic discrimination in hiring, promotion, and everyday interactions within predominantly white work environments. In this paper, we center the voices of 21 Black women working in the U.S. tech sector to explore how they engage with GenAI technologies to navigate workplace dynamics. Drawing on Black feminist epistemologies, our findings suggest that these women use GenAI as survival tools that help them manage hostile work environments and negotiate complex social interactions. GenAI supports their communication strategies, enhances productivity, and bolsters their efforts in responding to workplace discrimination rooted in misogynoir, the distinct, intersecting form of racism and sexism that specifically targets Black women. At the same time, these tools also reinforce existing power structures and do not address the fundamental need for Black women to show up as their full, authentic selves. We conclude by outlining Black feminist–informed directions that center resistance, survival, and collective world-building beyond hostile tech workplaces.
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
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