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)
12
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13
Index

What is economics? What is “value”?

Economics is the branch of knowledge concerned with the production, consumption, and transfer of wealth or value. Defining value, however, is a tricky proposition. Most organizations have historically relied upon traditional financial measures of value creation, such as:

  • Revenue
  • Gross Profit Margin
  • Operating Profit Margin
  • Net Present Value (NPV)
  • Internal Rate of Return (IRR)
  • Return on Investment (ROI)
  • Return on assets (ROA)
  • Debt-to-equity ratio
  • Earnings per Share (EPS)

As discussed in Chapter 5, many of these financial measures are lagging indicators; their results depend on the performance of related independent or leading indicators. Organizations must embrace a broader range of measures that define value than just financial measures. If not, these organizations risk creating AI models that result in severe confirmation bias and potentially dangerous unintended consequences.Organizations that want to embrace AI as an engine of meaningful...