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Get to Know Critical Thinking and Data-Driven Decision-Making

Learning Objectives

After completing this unit, you’ll be able to:

  • Define critical thinking and how to use it in the decision-making process.
  • Explain what data-driven decision-making is.
  • Describe the power of using critical thinking, data analysis, and artificial intelligence together.

This module was produced in collaboration with OneNine AI. OneNine AI is bringing the power of AI to everyone. Learn about partner content on Trailhead (log in required).

Critical thinking and data-driven decision-making are fundamental skills that help you work ethically and effectively with artificial intelligence (AI). In this module, you explore these fundamental skills, learn about decision-making and AI models, and see how AI is helping organizations make data-driven decisions across diverse industries. Let’s get started.

So What Is Critical Thinking?

Critical thinking is the process of analyzing, evaluating, and synthesizing information, evidence, and arguments to make well-informed, reasoned decisions. It involves the ability to think clearly, objectively, and independently, and to consider various perspectives and potential outcomes. Critical thinking leads to wise decisions and effective problem solving.

Lit light bulb among many unlit light bulbs.

Click the tabs below to learn about key characteristics of critical thinkers.

The Role of Critical Thinking in Decision-Making

Critical thinking is like having a trusted guide on your decision-making journey. It helps you gather evidence, think logically, and weigh your options before choosing a path. The qualities of being analytical, curious, open-minded, research-focused, and logical prepare you to practice critical thinking.

When you apply critical thinking in decision-making, you usually do the following activities.

  • Gather information: Critical thinking begins with the collection of information. When you face a decision, seek out relevant data, facts, and evidence to understand the problem or opportunity at hand.
  • Evaluate information: Examine the gathered information closely. Distinguish between credible and unreliable sources, separate fact from opinion, and evaluate the quality of the data. This analysis enables you to make a decision based on a solid foundation.
  • Identify assumptions: Identify any underlying assumptions or beliefs that might influence your decision-making. Question your own preconceptions and biases and consider how these factors might affect the choice.
  • Evaluate pros and cons: Engage in a process of weighing the advantages and disadvantages of each option. Consider potential benefits, risks, and consequences to make a decision that aligns with your goals.
  • Problem solve: Decision-making often involves solving a problem or addressing a challenge. Critical thinking, with its blend of analytical and creative skills, gives you the problem-solving tools you need to break down a complex issue into manageable parts. It helps you determine which elements to focus on, and it inspires creativity in the process. This creative approach allows you to identify potential solutions and choose the most appropriate course of action.

The art of asking questions is involved in each of these activities. In fact, asking questions is the cornerstone of critical thinking, as it paves the way for clarity, objectivity, and the pursuit of the most rational and ethical choices. Questions enable you to probe deeper, challenge assumptions, and uncover hidden truths.

Through skillful questioning, you can dissect complex issues, separate facts from opinions, and evaluate the validity of arguments. This process not only uncovers valuable insights but also ensures that decisions are well-informed and based on a thorough understanding of the matter at hand. (More about the art of questioning in unit 2.)

What Is Data-Driven Decision-Making?

You just learned that gathering and analyzing information is an important part of decision-making for critical thinkers. Data lets you make decisions based on facts rather than a best guess.

To make data-driven decisions, you follow a process: Understand your goals, ask questions, gather data, study the data to find patterns, make a choice based on the patterns and trends, and evaluate the results. As you can see, critical thinking is involved at every step.

Process automation robot pointing to symbols of what it can automate: list, briefcase, customer service, email.

Critical thinking is the ability to evaluate information, understand it, and make informed decisions based on facts. Critical thinkers are curious, ask questions, and think outside the box. They’re open to different ideas and don’t jump to conclusions.

For example, an ecommerce company collects data on customer behavior, analyzes it to understand shopping trends, and uses this information to improve the user experience. It uses the information to personalize product recommendations, streamline the checkout process, offer targeted promotions, and enhance website navigation.

This data-driven approach not only caters to individual customer preferences but also optimizes the website’s overall performance, leading to increased customer satisfaction and higher conversion rates.

Use Critical Thinking, Data, and AI Together

Critical thinking helps you ask the right questions, data provides critical facts and information, and AI processes the data quickly.

AI is like a supercharged assistant for critical thinking. It can quickly analyze tons of data, spot patterns, and make predictions to support your decision-making. While this assistant can speed up your decision-making process, you need to be aware of potential ethical implications. When using data and AI, you need to consider ethical questions like privacy, fairness, and transparency. Critical thinking helps you make ethical choices.

Person holding light bulb with AI lettering representing the aid AI can provide in decision-making.

You’ve learned the basics about critical thinking and data-based decision-making. And you’ve seen how critical thinking plays a key role when you work with data and AI. Next, let’s delve into the art of asking great questions.


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