Sep 2026· Cambridge University Press eBooks· 0 citations
Abstract
Disclosure laws aim to empower individuals to make better decisions, yet in practice they often overwhelm readers with excessive and inaccessible information. Disclosure Laws in the Digital Era explains why traditional regulatory approaches fall short and how technological advances offer new opportunities to evaluate and improve disclosure quality. Through a comprehensive study of the U.S. franchise disclosure regime, Uri Benoliel demonstrates how AI and big data standards can assess whether disclosures genuinely help prospective franchisees understand key risks. Benoliel proposes a forward-looking framework that integrates technology into disclosure design, offering more reliable and scalable methods for regulatory oversight. Combining doctrinal analysis, empirical insights, and policy recommendations, the book offers valuable insights for scholars of disclosure, franchising, consumer protection, and contract law, as well as for policymakers, regulators, and legal practitioners seeking to strengthen transparency and informed decision-making in the digital era.
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
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
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