Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
Using genomic data from 220 UK Holstein cows, researchers tested Random Forest and Multi-Layer Perceptron models against conventional gBLUP for predicting residual feed intake, a feed-efficiency trait. The ensemble of RF and MLP achieved the best reported performance with R2=0.39 and RMSE=0.086, while SHAP analysis identified distinct and overlapping candidate genes.
A mixed-methods study examined how 19 professional writers and 30 avid readers understood authenticity in writing produced with AI assistance. Writers completed short writing tasks using both personalized and non-personalized GPT-4 suggestions, while readers evaluated passages written independently or with either form of AI support.
By June 2026, a peer-reviewed paper analyzed how AI and AIGC are being integrated into newsrooms, from data mining to co-creation of news products, increasing efficiency and output volume while prompting questions about human professionalism and editorial control.
A preregistered survey experiment in German-speaking Switzerland with 599 participants tested how audiences perceive news excerpts described as human-written, AI-assisted, or fully AI-generated. Participants first rated quality without knowing the production method, then learned how their excerpts were produced and reported engagement intentions.
Published May 5 2024, this peer-reviewed review argues that ChatGPT and subsequent conversational bots should be assessed through a Sustainability, PrivAcy, Digital divide, and Ethics (SPADE) lens. It surveys issues and concerns raised over ChatGPT in those four areas and briefly discusses the recent EU AI Act in that context.
Published May 31, 2024 in PNAS Nexus, this peer-reviewed overview examines how generative AI could both exacerbate and ameliorate socioeconomic inequalities across information, work, education, and healthcare. It notes potential gains like democratized content creation, productivity boosts, personalized learning, and improved diagnostics alongside risks of misinformation proliferation and unevenly distributed benefits.
A December 2025 peer-reviewed paper in ShodhKosh examines management of AI-generated music intellectual property. It describes autonomous composition via deep-learning and neural networks, analyzes how human and AI creativity differ on intent and originality, and finds existing copyright regimes ineffective at assigning ownership and authorship to non-human creators.
A December 2025 review in Human Relations examined the growing use of artificial intelligence in recruitment and hiring and its implications for organizational inequalities. Using a hybrid scoping and problematizing approach, the authors synthesized multidisciplinary literature and found asymmetries in conceptualization, a heightened potential for AI to conceal inequalities, and ongoing contestation over regulation.
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