This workshop will nurture scholarly debate about the transformative impact of artificial intelligence on the essential academic practice of conducting literature reviews, including possible ethical concerns and risks. It will also allow practical hands-on exploration of the subject. A brief overview of current AI approaches—symbolic AI (rule-based expert systems) and connectionist AI (neural networks)— and corresponding solutions to support literature reviews, will highlight their respective strengths and limitations. Hybrid neuro-symbolic systems, which combine logical reasoning with pattern recognition to address transparency and performance issues, will be introduced. The focus will then be ARTIREV (www.scanlitt.com), a hybrid AI tool integrating a bibliometric expert system with fine-tuned generative AI (SOCRATES). ARTIREV addresses key shortcomings in existing bibliometric software and generalist generative AI, offering improved transparency, exhaustivity, and reliability. Attendees will be afforded practical experimentation with ARTIREV to conduct, on the spot, a literature review on the subject of their choice. This will allow participants to critically assess the capabilities and potential for academic research of the proposed tool, while benchmarking it against any other AI solution of their choice. Overall, the workshop will encourage discussion, grounded in attendees’ practical, first-hand experience of AI’s role in shaping the future of scholarly work.
