Book Image

AI & Data Literacy

By : Bill Schmarzo
Book Image

AI & Data Literacy

By: Bill Schmarzo

Overview of this book

AI is undoubtedly a game-changing tool with immense potential to improve human life. This book aims to empower you as a Citizen of Data Science, covering the privacy, ethics, and theoretical concepts you’ll need to exploit to thrive amid the current and future developments in the AI landscape. We'll explore AI's inner workings, user intent, and the critical role of the AI utility function while also briefly touching on statistics and prediction to build decision models that leverage AI and data for highly informed, more accurate, and less risky decisions. Additionally, we'll discuss how organizations of all sizes can leverage AI and data to engineer or create value. We'll establish why economies of learning are more powerful than the economies of scale in a digital-centric world. Ethics and personal/organizational empowerment in the context of AI will also be addressed. Lastly, we'll delve into ChatGPT and the role of Large Language Models (LLMs), preparing you for the growing importance of Generative AI. By the end of the book, you'll have a deeper understanding of AI and how best to leverage it and thrive alongside it.
Table of Contents (14 chapters)
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Game-changing ramifications of nanoeconomics

Nanoeconomics is a term I have coined to describe the economic theory of leveraging AI to uncover individual human and device predicted behavioral and performance propensities (insights) that are buried in the organization’s customer engagement and operational management data.From these human and device predicted behavioral and performance propensities, organizations can make precision decisions to optimize the organization’s key business and operational use cases, such as predicting which customers are likely to stop using your products or services, which patients are likely to catch a staph infection, which first-year college students are likely to flunk out, which truck drivers are likely to have a car accident, or which worker is likely to retire (Figure 5.3).

Figure 5.3: Nanoeconomics: Transitioning Decision-Making from Averages to Propensities