The Wall of Shame
Warnings and real accounts about the worst of humanity that has been personally encountered, observed, and experienced.
Learn the lengths that people will go to in order to intentionally cause suffering for others, so you may avoid becoming either perpetrator or victim.
The Definitive AI Resources Repository
A curated compilation of artificial intelligence resources, selected to assist with research, governance, and innovation. This repository synthesises perspectives from world-leading institutions, providing researchers, policymakers, and technology professionals with a comprehensive navigational guide to the online AI knowledge landscape.
The Science and Methodology of Electoral Forecasting: Analysing Predictive Models in American Presidential Elections
Electoral forecasting represents one of the most complex challenges in political science, combining quantitative analysis with qualitative assessment of numerous variables that influence voter behaviour. This essay examines the methodological…
Why Nations Fail (Daron Acemoglu and James A. Robinson) – Book Summary, Notes & Highlights
Discover Why Nations Fail by Daron Acemoglu and James A. Robinson, an insightful analysis of how institutions shape the prosperity or poverty of nations. Learn why inclusive institutions foster success, while extractive ones lead to economic failure. A must-read for those interested in global economics and development.
My Experience with JSTOR’s New AI Research Tool: A Cambridge Student’s Review
Discover a Cambridge student’s hands-on review of JSTOR’s AI research tool beta. Learn how this innovative tool transforms academic research with smart features and time-saving capabilities.
AI Governance Frameworks: A Comparative Analysis
Explore a detailed comparison of global AI governance frameworks, including the EU AI Act, US AI Bill of Rights, and other key regulatory approaches shaping the future of artificial intelligence.
The Role of Diversity in Mitigating AI Bias
Discover how diversity in AI development teams and datasets helps combat algorithmic bias. Learn practical strategies for creating more inclusive AI systems in 2024 and beyond.