Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
On August 15, 2026, a peer-reviewed study reported a hybrid ensemble machine learning framework for assessing landscape ecological vulnerability to riverbank erosion. Using random forest, multilayer perceptron and bagging classifiers with multicollinearity-selected environmental and geomorphological parameters, the bagging ensemble achieved 0.97 AUC and 0.91 accuracy, mapping over half the area into high or very high vulnerability zones in Bihar and West Bengal.
By August 2026, researchers had used single-cell RNA sequencing of lung adenocarcinoma patients treated with neoadjuvant immunotherapy to map resistance-associated heterogeneity, identifying a malignant Cluster 2 enriched in non-responders with upregulated KRT17, S100A2, and CST6, and built a CoxBoost combined with survivalSVM prognostic model validated across seven independent cohorts.
This scoping review examined 41 empirical studies published from 2015 to March 2026 on AI for cancer symptom management in adult survivors. Twenty-one studies focused on model development using mainly unstructured electronic health record data, 18 on AI-enabled delivery using patient-reported inputs, and 2 on both, employing natural language processing, machine learning, and conversational AI for detection, monitoring, triage, decision support, personalised management, education and counselling.
Researchers applied an explainable AI framework to four years of routine air-quality and meteorological data from a single urban monitoring station to move beyond concentration-only analysis of PM10. The best ensemble model reached R2=0.913, and SHAP-based clustering revealed ten recurrent environmental settings linked to enhancement, reduction, or transitional PM10 behavior.
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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