[2603.20235] Writing literature reviews with AI: principles, hurdles and some lessons learned

Computer Science > Computers and Society arXiv:2603.20235 (cs) [Submitted on 8 Mar 2026] Title:Writing literature reviews with AI: principles, hurdles and some lessons learned Authors:Saadi Lahlou (1,2), Annabelle Gouttebroze (1), Atrina Oraee (1), Julian Madera (1) ((1) London School of Economics and Political Science (2) Paris Institute for Advanced Study) View a PDF of the paper titled Writing literature reviews with AI: principles, hurdles and some lessons learned, by Saadi Lahlou (1 and 4 other authors View PDF Abstract:We qualitatively compared literature reviews produced with varying degrees of AI assistance. The same LLM, given the same corpus of 280 papers but different selections, produced dramatically different reviews, from mainstream and politically neutral to critical and post-colonial, though neither orientation was intended. LLM outputs always appear at first glance to be well written, well informed and thought out, but closer reading reveals gaps, biases and lack of depth. Our comparison of six versions shows a series of pitfalls and suggests precautions necessary when using AI assistance to make a literature review. Main issues are: (1) The bias of ignorance (you do not know what you do not get) in the selection of relevant papers. (2) Alignment and digital sycophancy: commercial AI models slavishly take you further in the direction they understand you give them, reinforcing biases. (3) Mainstreaming: because of their statistical nature, LLM productions t...