Data-Driven Education Insights

  This article analyzes data from the PISA 2018 assessment, focusing on student performance in reading, math, and science across 10 countries. The study compares four bottom-performing countries with six top-performing countries to explore performance gaps and the influence of various factors. Data Overview Countries : Bottom performers: Kazakhstan (QAZ), Dominican Republic (DOM), Morocco (MAR), Panama (PAN) Top performers: Hong Kong (HKG), Korea (KOR), Chinese Taipei (TAP), Macao (MAC), United Kingdom (GBR), United States (USA) Sample Size : 67,946 students [42,640 from non-OECD countries & 25,306 from OECD countries; 33,591 female students & 34,355 male students] Key Findings 1. Overall Performance Gap Students from bottom-performing countries consistently scored lower in all subjects (reading, math, and science) compared to those from top-performing countries. The gap in scores between these groups is significant, as illustrated in Figure 1. Bar chart comparing average readi

  Russell, S. (2020). Human compatible: Artificial intelligence and the problem of control . Penguin Books. Buy the book here . Highlights: The standard model of AI, where machines optimize a fixed objective, is fundamentally flawed and becomes untenable as AI becomes more powerful. To ensure AI remains beneficial, machines should be designed to be uncertain about human preferences and learn them through observation, leading to deferential and cautious behavior. The three principles for beneficial machines are: the machine's only objective is to maximize the realization of human preferences, the machine is initially uncertain about those preferences, and human behavior is the only source of information about human preferences. Inverse reinforcement learning (IRL) is a key technique for machines to learn human preferences from observed behavior. The off-switch problem (machines resisting being turned off) can be solved by machines that are uncertain about human preferences, as they