We live in an age defined by uncertainty, and by our relentless attempts to master it. Too often, disciplines are treated as separate silos: philosophy apart from mathematics, mathematics apart from engineering and science apart from society. Yet look closer, and a common thread emerges, one that runs through our history of grappling with the unknown and extends into the technologies shaping our everyday lives.
From ChatGPT to Alexa and Siri, artificial intelligence and data science are no longer abstract concepts, they’re embedded in how we work, shop, speak and live. Alongside this transformation, demand for skilled data scientists has soared, with the profession often described as ‘the sexiest job of the 21st century’.
Predicting the Unknown bridges a crucial gap in the literature by tracing how uncertainty has been understood across time and disciplines and how those ideas evolved into today’s fields of data science, machine learning and AI. Drawing on history, philosophy, mathematics and engineering, the book explains how past perspectives continue to shape the technologies of the present, and points towards the challenges and opportunities of the future.
Accessible and intellectually stimulating, this is a book for both the curious reader who wants to understand AI without equations, and for technical experts seeking historical context for the systems they work with today.
You’ll discover:
how data science, AI and machine learning fit into the bigger picture of our struggle to understand and predict the unknown;
the historical roots of modern ideas in philosophy, mathematics and engineering;
engaging narratives that connect human curiosity to the cutting-edge technologies now reshaping society.
Dr. Stylianos (Stelios) Kampakis is a data scientist, educator, and blockchain expert with over a decade of experience. He has advised decision-makers across industries, from startups to global organisations including the US Navy, Vodafone and British Land. His expertise spans fintech (fraud detection and valuation models), sports analytics, health-tech, medical statistics, AI, predictive maintenance and blockchain technologies, with two patents currently pending.
Dedicated to education and mentoring, Stelios has guided many aspiring professionals into successful data science careers. He is a member of the Royal Statistical Society, an honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor to London Business School and CEO of the Tesseract Academy. He also works as a tokenomics auditor with Hacken.
A well-known voice in the field, Stelios has published two highly rated books, built a personal website that attracts over 10,000 visitors each month and is recognised as a data science influencer on LinkedIn.
‘Kampakis’ book clearly and readably covers the essence of uncertainty and the human efforts to address it, written for both professional data scientists and anyone attempting to predict life’s unknowable and unexpected outcomes.’ (Harry J. Foxwell, Computing Reviews, November 29, 2023)
