ChatGPT Changes Everything

“The Horror. The Horror.”

– Colonel Walter E. Kurtz (Marlon Brando), Apocalypse Now

During the writing of this book, a technological revolution exploded unto the scene with the advent of Generative AI (GenAI), ChatGPT, and Large Language Models (LLMs). These cutting-edge advancements brought to life the promises and fears surrounding AI, captivating the public’s imagination. The astounding popularity and rapid adoption of OpenAI’s ChatGPT were unimaginable. People marveled at its human-like ability to respond to a vast range of questions, unleashing their creativity as they sought ChatGPT’s assistance in crafting poems, love letters in the style of Romeo, legal briefs, and even blog posts.

However, amid the excitement, there was an undercurrent of trepidation fueled by popular movies like The Terminator, Eagle Eye, I, Robot, and The Matrix, which predicted ominous AI consequences. This impending...

What are ChatGPT and GenAI?

GenAI is an AI system that relies on unsupervised or semi-supervised learning algorithms to create new and original digital content (e.g., articles, program code, poetry, photographs, artwork, and music) by learning from existing data or content.

ChatGPT (GPT stands for Generative Pre-trained Transformer) is a GenAI chatbot launched by OpenAI in November 2022. It is built on OpenAI’s GPT family of LLMs and fine-tuned with supervised and reinforcement learning techniques.

ChatGPT uses supervised learning to train its LLM. The supervised learning model uses the labeled data gleaned from websites and digital books to identify statistical language patterns buried in the massive data sets to train an LLM. The LLM then leverages these statistical language patterns and Natural Language Processing (NLP) to generate human-like responses.

ChatGPT also uses Reinforcement Learning from Human Feedback (RLHF) to continue to refine and enhance the relevance...

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In this chapter, we want to focus on the secret to successful AI and data literacy—empowering your people. This may well be the most challenging chapter in the book because it forces the Citizen 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 is over, and AI will win.To quote 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 will be uncomfortable because everyone desires to work with people like themselves. It’s easier...

A history lesson on team empowerment

In the 1805 Battle of the Trafalgar, British Admiral Lord Nelson faced the superior forces of the combined French and Spanish naval armada. The French and Spanish naval armada was determined to clear a path for Napoleon to invade England, and only Lord Nelson stood in their way. Lord Nelson was severely outnumbered and outgunned, so he needed to reframe his battle strategy to overcome these debilitating disadvantages. In 1805, the standard method of naval warfare involved ships lining up parallel to each other to maximize the effectiveness of their cannons. Naval battle in the Age of Sail was a simple game of math—firing more cannonballs more quickly than your opponent was the best way to ensure victory.

Figure 9.1: Traditional Naval Warfare Formation

Given his underdog situation, Lord Nelson decided on a different naval engagement strategy. Instead of the traditional parallel arrangement, he arranged his ships perpendicularly and drove them...

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Citizen empowerment #1: Internalize your mission

“Begin with an end in mind.” – Stephen Covey, 7 Habits of Highly Effective People

Understand what you are trying to accomplish. What is your mission – your passion? What fires you up in the morning and makes you want to attack the day. Then contemplate how it creates value for others (e.g., stakeholders, constituents). Leading organizations have mission statements, a brief statement or phrase that clearly articulates why the organization exists.

Here are some of my favorite mission statements:

• TED: Spread ideas.
• JetBlue: To inspire humanity in the air and on the ground.
• American Heart Association: To be a relentless force for a world of longer, healthier lives.
• Patagonia: Build the best product, cause no unnecessary harm, and use business to inspire and implement solutions to the environmental crisis.
• Nordstrom: To give customers the most compelling shopping experience possible.
• LinkedIn: Create...

Thriving with GenAI

GenAI models will reward individuals who can apply knowledge rather than those who can memorize and regurgitate knowledge.

The definition of success is changing. No longer will memorization and regurgitation of knowledge be sufficient. Instead, success will be defined by people who know how to apply knowledge to deliver meaningful, relevant, and ethical business, operational, and societal outcomes.

The roles that will prosper and excel in a world of AI are the roles that integrate and blend an understanding of data and analytics with their areas of expertise by:

• Identifying (envisioning) where and how AI can be applied to their professions to deliver more meaningful, relevant, and ethical business and operational outcomes.
• Driving cross-organizational alignment and consensus on the variables, metrics, and desired outcomes against which AI effectiveness will be measured.
• Defining a comprehensive, healthy AI utility function to avoid...

Homework Assignment Review

Remember the spider chart we created at the end of Chapter 1? As mentioned, improving our AI and data literacy starts by understanding where we sit and in what areas we need more education and training. To facilitate that analysis, I had created the AI and data literacy Radar Chart in the following figure to assess where we sit today:

Figure 9.9: AI & Data Literacy Radar Chart

Given everything you’ve learned throughout the book, let's retake the assessment. I’ve included the guidelines in the following table to help you complete your AI and data literacy radar map:

Figure 9.10: AI & Data Literacy Radar Guidelines

Hopefully, you made progress in improving your AI and data literacy across the different categories of literacy. For those areas you didn’t make the progress you would have liked to make, well, you might want to re-read the associated chapters.

Summary

As you have seen in this chapter, creating Citizens of Data Science requires empowering everyone in the organization and giving everyone a voice in where and how AI is designed and deployed to drive meaningful, relevant, responsible, and ethical outcomes.That means that we need to celebrate our personal mission and walk in the shoes of our stakeholders and constituents. We need to embrace an "and" mentality and foster the organizational improvisation necessary to put people in the right places where they can be successful and grow. Ultimately, Citizens of Data Science must nurture their natural human traits of curiosity, creativity, and innovation to thrive in a world more and more dominated by AI and data. ADDMy final point in the book is this: You have all the tools and skills necessary to succeed, but your success is ultimately on you. The minute you start to blame others for your problems, you abdicate control of your life. Please don’t do it. Own your mistakes...

References

1. Pause Giant AI Experiments: An Open Letter: https://futureoflife.org/open-letter/pause-giant-ai-experiments/

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