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You're reading from  AI & Data Literacy

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Published inJul 2023
PublisherPackt
ISBN-139781835083505
Edition1st Edition
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Author (1)
Bill Schmarzo
Bill Schmarzo
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Bill Schmarzo

Bill Schmarzo, The Dean of Big Data is a University of San Francisco School of Management Executive Fellow and an Honorary Professor at the School of Business and Economics at the National University of Ireland-Galway where he teaches and mentors students in his courses “Big Data MBA” and “Thinking Like a Data Scientist". He is the author of Big Data: Understanding How Data Powers Big Business, Big Data MBA: Driving Business Strategies with Data Science, and The Art of Thinking Like a Data Scientist. He has written countless whitepapers, articles and blogs, and given keynote presentations and university lectures on the topics of data science, artificial intelligence/machine learning, data economics, design thinking and team empowerment.
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Cultural Empowerment

In this chapter, we want to focus on the secret to successful AI and data literacy – empowering yourself and your people. This may well be the most challenging chapter in the book because it forces Citizens of Data Science to embrace a very uncomfortable and even troubling concept – ambiguity.

Ambiguity – the quality of being open to more than one interpretation – is the key to human, society, and organizational evolution. If everyone has the same perspectives and same opinions, if our thinking is just a clone of everyone else’s thinking, then human evolution and growth are over, and AI will win.

To quote popular American self-help author Peter McWilliams:

“Be willing to be uncomfortable. Be comfortable being uncomfortable. It may get tough, but it’s a small price to pay for living a dream.”

This chapter may be uncomfortable for some readers as it delves into the innate human tendency...

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Ethics is understanding and applying the moral principles of right and wrong that govern a person’s behavior or actions.ADDTo sum up, we'll discuss the following topics in this chapter:

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Understanding ethics

Ethics are the moral principles governing a person’s behavior or actions, the principles of right and wrong generally accepted by an individual or a social group. Or as my mom used to say, “Ethics is what you do when no one is watching.”AI ethics, on the other hand, is a field of study that focuses on AI's ethical development, application, and management. AI ethics involves identifying and exploring the potential unintended consequences of AI and considering how AI can be used fairly and responsibly to benefit society.

Proactive vs. passive ethics

An essential characteristic of ethics is that ethics is proactive, not passive. Ethics is proactive in compelling appropriate actions considering society's moral standards versus just abdicating appropriate actions to someone else. And if you don’t know the difference between passive and active ethics, then it’s time for a bible lesson refresher – The Parable of the Good...

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Ethical behaviors make for good economics

Society can achieve positive economic outcomes driven by the ethics of fairness, equality, justice, and generosity. The Bible, as well as other religious doctrines, is full of ethical lessons that are economic lessons based upon a more holistic definition of value. Yes, the Bible is a masterpiece of economics lessons on how society can deliver more relevant, meaningful, responsible, and ethical outcomes.Economics is defined as a framework for the creation and distribution of wealth or value. Let's illustrate this with an example. A study conducted in Massachusetts highlights the potential value of a fairness program known as Meals for All Students. The state currently allocates $2.4 billion each year to address student mental health issues, diabetes, obesity, and cognitive development challenges. By implementing the School Meals for All initiative, the annual cost would amount to $100-120 million, yielding a substantial return on...

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Minimizing unintended consequences

Unintended Consequences are unforeseen or unintended results that can result from an action or decision. Unintended consequences can occur when insufficient consideration is given to the second and third-order potential outcomes of even the best-intended initiatives and decisions. There are many examples of good intentions gone wrong yielding unintended consequences such as:

  • The SS Eastland, a badly-designed, ungainly vessel, was intended to be made safer by adding several lifeboats. Unfortunately, the extra weight of the lifeboats caused the ship to capsize, trapping and killing 800 passengers below the decks.
  • The Treaty of Versailles dictated surrender terms to Germany to end World War I. Unfortunately, the terms empowered Adolf Hitler and his followers, leading to World War II.
  • The Smokey Bear Wildfire Prevention campaign created decades of highly successful fire prevention. Unfortunately, this disrupted normal fire processes vital to the...

Summary

“You are what you measure, and you measure what you reward.”All this discussion about how we can build AI models that deliver meaningful, relevant, responsible, and ethical outcomes has gotten me thinking about the bigger societal ramifications.What would be the ramifications to society if we paid our leaders on the metrics that mattered most? How would that change the laws and regulations that got written, the actions that leadership took, and the decisions that government and social agencies made?Here’s an interesting point to contemplate: while we can go through this detailed process to create AI models that act ethically, what are we doing to solve the bigger problem of creating incentive systems to get humans to act ethically?That one is on all of us to become better humans…ADD

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Published in: Jul 2023Publisher: PacktISBN-13: 9781835083505
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Author (1)

author image
Bill Schmarzo

Bill Schmarzo, The Dean of Big Data is a University of San Francisco School of Management Executive Fellow and an Honorary Professor at the School of Business and Economics at the National University of Ireland-Galway where he teaches and mentors students in his courses “Big Data MBA” and “Thinking Like a Data Scientist". He is the author of Big Data: Understanding How Data Powers Big Business, Big Data MBA: Driving Business Strategies with Data Science, and The Art of Thinking Like a Data Scientist. He has written countless whitepapers, articles and blogs, and given keynote presentations and university lectures on the topics of data science, artificial intelligence/machine learning, data economics, design thinking and team empowerment.
Read more about Bill Schmarzo