Why 95% Of AI Projects Fail and How to Change the Odds
Drawing on two decades of work building AI systems for medicine discovery, Lee Clewley argues that the success of AI models rests on three principles.
Jan 12, 2026
Welcome to Real World Data Science, a new project from the Royal Statistical Society, in partnership with the American Statistical Association. We bridge the gap between rigorous analysis and real time relevance, meeting the pace and complexity of today’s data driven world with the RSS’s trademark steadying presence.
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Is data science a new and exciting set of skills, necessary for analyzing 21st century data? Or is it (as some have claimed) a rebranding of statistics, which has carefully developed time-honored methods for data analysis over the past century? In this article, we use two popular data science algorithms to examine the difference between data science, statistics, and other occupations.
Jonathan Auerbach, David Kepplinger, and Nicholas Rios ask, ‘What is data science?’
The Pulse
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Applied Insights
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Generative AI is based on neural networks, which are so-called ‘black boxes’. This makes it difficult or impossible to explain the inner workings of the model which has potential implications if in the future you are challenged to justify decisioning or guidance based on the model.
Excerpt from the UK government’s framework for the use of generative AI
Foundations & Frontiers
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People & Paths
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