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Kiron Ravindran

In this course, you’ll use Generative AI as a thinking partner to spot false patterns, challenge biased evidence, break apart misleading averages, and uncover logical flaws in headlines, dashboards, and data-driven claims. Along the way, you'll learn to recognize classic reasoning traps, from Simpson’s Paradox to base rate neglect, survivorship bias, and more.

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In this course, you’ll use Generative AI as a thinking partner to spot false patterns, challenge biased evidence, break apart misleading averages, and uncover logical flaws in headlines, dashboards, and data-driven claims. Along the way, you'll learn to recognize classic reasoning traps, from Simpson’s Paradox to base rate neglect, survivorship bias, and more.

By the end of the course, you'll be able to evaluate arguments using logic and evidence, not emotion or popularity; detect hidden assumptions, flawed comparisons, and biased sampling; and use AI tools to test claims, simulate opposing views, and sharpen your reasoning.

Whether you're a student, decision-maker, or lifelong learner, this course will help you use AI not just to think faster, but to think better.

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What's inside

Syllabus

Patterns That Fool Us
In this module, students will explore why not all patterns in data are meaningful. They’ll learn how randomness creates illusions that our minds instinctively misinterpret, how correlation can be confused with causation, and why spurious patterns often emerge when data is selected, framed, or misunderstood.
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Learners who complete Beyond the Obvious: How to Think in the Age of Generative AI will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst is crucial for translating complex datasets into actionable insights for businesses and organizations, a role where critical evaluation of information is paramount. This course, Beyond the Obvious: How to Think in the Age of Generative AI, helps build a foundational understanding for successfully identifying misleading patterns and data anomalies. Learners will enhance their ability to question the raw material they work with, discerning between correlation and causation, and recognizing how data selection or framing can distort conclusions, as explored in "Patterns That Fool Us" and "Bad Samples Bad Stories." This course also strengthens a Data Analyst's capacity to critically evaluate arguments and data-driven claims. The module "Using Generative AI to Think More Critically" directly prepares one to leverage AI tools to test assumptions and sharpen reasoning, ensuring more robust and trustworthy analyses.
Business Intelligence Analyst
A Business Intelligence Analyst is responsible for transforming raw data into meaningful insights that support business decision-making. This role demands a high degree of critical thinking to ensure the reliability and accuracy of reported information. Beyond the Obvious: How to Think in the Age of Generative AI helps build a foundation in spotting false patterns, challenging biased evidence, and breaking apart misleading averages, all of which are critical for a Business Intelligence Analyst. The modules "Patterns That Fool Us" and "Misleading Aggregates and Base Rates" directly equip learners to avoid common data interpretation pitfalls. The course's focus on evaluating arguments with logic and evidence and using AI tools to test claims and sharpen reasoning directly translates into creating more robust dashboards and trustworthy data-driven reports, enhancing the strategic value of BI.
Research Scientist
A Research Scientist designs and executes experiments, analyzes results, and draws evidence-based conclusions, often requiring an advanced degree. This course helps develop the rigorous critical thinking essential for a Research Scientist to navigate complex data and theoretical frameworks. It helps learners to scrutinize experimental designs and data collection methods for potential biases, as detailed in the "Bad Samples Bad Stories" module. Understanding how "Patterns That Fool Us" can lead to misinterpretations is key to forming valid hypotheses and drawing robust conclusions. Furthermore, the course's focus on evaluating arguments and detecting logical flaws is indispensable when peer-reviewing work or synthesizing existing literature. Using Generative AI to test claims and simulate opposing views can also be invaluable for refining research questions and validating methodologies.
Management Consultant
A Management Consultant advises organizations on improving performance, requiring astute problem-solving and evidence-based recommendations. This course helps build the critical thinking skills crucial for a Management Consultant to dissect complex business challenges and evaluate client-provided data or claims. The ability to spot false patterns, challenge biased evidence, and uncover logical flaws is directly applicable when analyzing market trends, operational inefficiencies, or strategic proposals. Modules like "Misleading Aggregates and Base Rates" prepare learners to question the superficial appearance of data, ensuring deeper, context-rich insights. Furthermore, the capacity to use Generative AI as a thinking partner to test assumptions and simulate different business scenarios, as taught in "Using Generative AI to Think More Critically," significantly enhances a consultant's strategic development and recommendation strength.
Policy Analyst
A Policy Analyst evaluates current policies and proposes new ones, relying heavily on data, research, and critical assessment of societal impacts. This role often requires an advanced degree. This course helps a Policy Analyst to critically examine the data and arguments underpinning policy decisions. Understanding how "Misleading Aggregates and Base Rates" can distort the perceived effectiveness of policies, or how "Bad Samples Bad Stories" can lead to flawed conclusions about populations, is essential. Learners will develop the capacity to detect hidden assumptions, flawed comparisons, and biased sampling in reports and proposals, leading to more robust and equitable policy recommendations. The module on "Using Generative AI to Think More Critically" provides crucial skills for leveraging AI to test policy assumptions and simulate disagreement, sharpening their analytical edge in a complex, evidence-driven environment.
Legal Counsel
Legal Counsel provides legal advice, represents clients, and constructs arguments in legal proceedings, often requiring an advanced degree. This course helps Legal Counsel to significantly sharpen their analytical and argumentative skills. The ability to evaluate arguments using logic and evidence, rather than emotion, is foundational to legal practice. Learners will gain proficiency in detecting hidden assumptions, flawed comparisons, and uncovering logical flaws within legal documents, case presentations, and witness testimonies. Modules that address classic reasoning traps like base rate neglect or biased sampling are directly applicable to assessing the strength of evidence and challenging opposing counsel's claims. Using Generative AI to test claims and simulate opposing views can also be a powerful tool for Legal Counsel in preparing cases and anticipating counterarguments, enriching their strategic approach to litigation.
Investigative Journalist
An Investigative Journalist uncovers hidden truths, meticulously researching and verifying information to expose wrongdoing or shed light on critical issues. This course helps an Investigative Journalist to critically evaluate sources and claims, which is fundamental to their work. The modules "Bad Samples Bad Stories" and "Patterns That Fool Us" directly equip learners to identify misinformation, recognize biased reporting, and understand how data can be manipulated or misinterpreted. The focus on evaluating arguments using logic and evidence, rather than emotion, is vital for constructing compelling and factually sound narratives. Furthermore, the ability to use Generative AI tools to test claims and surface alternative perspectives can be a powerful asset for an Investigative Journalist to cross-reference facts, challenge initial assumptions, and deepen their understanding of complex stories before publication.
Financial Analyst
A Financial Analyst evaluates financial data, market trends, and economic indicators to provide guidance on investment decisions or business performance. This course may be useful for a Financial Analyst in sharpening their critical appraisal of financial models and market narratives. Understanding how "Patterns That Fool Us" can lead to spurious correlations in market data or how "Misleading Aggregates and Base Rates" can distort financial performance metrics is invaluable. The course helps learners to detect hidden assumptions and flawed comparisons in financial reports, leading to more accurate valuations and risk assessments. Evaluating arguments using logic and evidence is crucial for discerning sound investment opportunities from speculative claims. Using Generative AI to test claims can also provide a novel approach to validating financial forecasts or market intelligence, enhancing due diligence.
Strategist
A Strategist develops long-term plans and initiatives for organizations, which demands foresight, robust analysis, and the ability to challenge conventional wisdom. This course may be useful for a Strategist in cultivating a powerful framework for critical thinking when assessing market dynamics, competitive intelligence, and internal capabilities. The ability to spot false patterns, challenge biased evidence, and uncover logical flaws in data-driven claims is paramount for building resilient strategies. Learning to recognize classic reasoning traps helps a Strategist avoid pitfalls in forecasting and decision-making. The "Using Generative AI to Think More Critically" module offers valuable methods for leveraging AI to test strategic assumptions, simulate diverse future scenarios, and surface alternative perspectives, ultimately leading to more robust and innovative strategic development.
Educator
An Educator, particularly at higher education levels, guides students in critical thinking, research, and subject-specific knowledge, often requiring an advanced degree. This course helps an Educator to model and teach essential critical thinking skills directly. The content, including recognizing "Patterns That Fool Us" and understanding "Misleading Aggregates and Base Rates," provides concrete examples and frameworks for instruction. Learning to evaluate arguments using logic and evidence, and to detect hidden assumptions, can be directly integrated into curriculum development and classroom discussions. Moreover, the module on "Using Generative AI to Think More Critically" is incredibly relevant for an Educator who wishes to prepare students to navigate the information landscape of today by leveraging AI tools responsibly to sharpen their own reasoning and challenge claims effectively within their academic pursuits and beyond.
Product Manager
A Product Manager leads the development of products, making crucial decisions based on market data, user feedback, and business goals. This course may be useful for a Product Manager in developing a keen sense of critical analysis when interpreting diverse data sources. Recognizing how "Patterns That Fool Us" can lead to incorrect assumptions about user behavior or market trends is invaluable for making informed product choices. Similarly, understanding "Bad Samples Bad Stories" helps in scrutinizing user research and A/B test results to ensure genuine insights. The course's emphasis on detecting hidden assumptions and flawed comparisons directly supports the Product Manager in evaluating competitive landscapes or feature prioritization. The integration of Generative AI tools for testing claims can further refine a Product Manager's strategic thinking and decision-making.
Risk Manager
A Risk Manager identifies, assesses, and mitigates potential threats and uncertainties for an organization, requiring a meticulous and analytical approach. This course may be useful for a Risk Manager in strengthening their capacity for critical evaluation of potential risks and their likelihood. Understanding how "Patterns That Fool Us" can create illusions of causality or how "Misleading Aggregates and Base Rates" can distort risk assessments is invaluable. The course helps learners to critically examine not just the source of data, but also how it is framed and used, which is essential for accurate risk modeling and reporting. By detecting hidden assumptions and logical flaws in risk reports, a Risk Manager can ensure more comprehensive and proactive risk management strategies. Leveraging Generative AI tools to test claims can further enhance their analytical toolkit.
Auditor
An Auditor systematically examines financial records, operational processes, and compliance frameworks to ensure accuracy, integrity, and adherence to regulations. This role demands a highly critical and skeptical mindset. This course may be useful for an Auditor in enhancing their ability to detect subtle discrepancies and challenge information presented. The course's focus on uncovering logical flaws in data-driven claims and detecting hidden assumptions is directly applicable to scrutinizing financial statements and internal controls. Understanding how "Bad Samples Bad Stories" can lead to misrepresented data or "Misleading Aggregates and Base Rates" can distort financial performance is crucial for robust audit findings. Leveraging Generative AI tools to test claims and simulate alternative perspectives can assist an Auditor in identifying potential fraud indicators or inconsistencies more effectively, thereby reinforcing the integrity of their assessments.
User Experience Researcher
A User Experience Researcher studies how users interact with products to inform design and development, often involving qualitative and quantitative data collection. This course may be useful for a User Experience Researcher to critically evaluate research methodologies and findings. The "Bad Samples Bad Stories" module is particularly relevant, preparing learners to scrutinize participant recruitment and data collection processes for biases, ensuring that user insights are truly representative. Understanding "Patterns That Fool Us" helps in correctly interpreting user behaviors and avoiding drawing incorrect causal links from observational data. The course's emphasis on detecting hidden assumptions and flawed comparisons directly supports the User Experience Researcher in synthesizing findings and making evidence-based recommendations, ensuring user-centric design approaches are robust and well-founded.
Content Strategist
A Content Strategist plans and oversees the creation and distribution of valuable content, often relying on data to inform decisions and ensure message effectiveness. This course may be useful for a Content Strategist in developing a more rigorous approach to evaluating information and constructing persuasive, yet factually sound, narratives. Understanding how "Patterns That Fool Us" and "Misleading Aggregates and Base Rates" can distort audience insights or market trends helps in crafting more targeted and impactful content strategies. The ability to evaluate arguments using logic and evidence, and to detect hidden assumptions, ensures that content is not only engaging but also credible and free from unintentional biases. Using Generative AI to test claims and surface alternative perspectives can also enrich topic generation and argument development, leading to richer and more nuanced content.

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Beyond the Obvious: How to Think in the Age of Generative AI.
This encyclopedia provides a comprehensive overview of philosophy, including logical reasoning. It covers a wide range of topics, including the history of logical reasoning, the different types of logical reasoning, and the applications of logical reasoning to ethics and law.
This comprehensive handbook provides a detailed overview of the field of formal logic. It covers a wide range of topics, including propositional logic, predicate logic, modal logic, and non-classical logics.
Decisive provides a four-step process (WRAP) for making better decisions: Widen your options, Reality-test your assumptions, Attain distance before deciding, and Prepare to be wrong. offers practical strategies and is highly applicable for students and professionals seeking to improve their decision-making skills in various contexts. It's a practical guide that complements the theoretical understanding of decision making.
This comprehensive textbook provides a broad overview of the field of artificial intelligence, covering fundamental concepts, algorithms, and applications. It is an essential resource for anyone interested in understanding the basics of AI.
Ariely explores the many ways in which our decisions are not rational, revealing the systematic and predictable errors we make. is highly relevant to understanding the biases discussed in several of the online courses. It serves as valuable additional reading to complement theoretical knowledge with real-world examples of irrationality.
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This recent book delves into the concept of noise – the unwanted variability in judgments that should ideally be identical. It builds upon Kahneman's previous work and is highly relevant to contemporary discussions on improving decision making in professional settings, such as medicine, law, and forecasting. It provides a deeper understanding of errors in judgment beyond just biases.
Directly addresses the challenges of identifying and combating fake news and misinformation. It provides practical strategies and theoretical context for understanding the current information disorder. Highly relevant for all audiences, particularly undergraduate students and professionals in communication and information fields.
Provides a comprehensive overview of the psychological processes that influence managerial judgment and decision making. It is often used as a textbook in business schools and is highly relevant for understanding how cognitive biases affect decisions in organizational settings. It's a valuable resource for both students and professionals.
Equips readers with the tools to identify and challenge misinformation, particularly in the context of data and statistics. It's a timely and practical guide for developing critical thinking skills relevant to the digital age and navigating misleading information. Highly recommended for all audiences.
Focused on effective communication of data insights, this book teaches readers how to create compelling data visualizations and narratives. It is highly relevant for undergraduate students, graduate students, and working professionals who need to present data findings persuasively. It emphasizes the practical aspects of data interpretation and communication in a business context.
Drawing on her background as a professional poker player, Duke provides a framework for making better decisions in situations involving uncertainty and incomplete information. is particularly useful for understanding probabilistic thinking and managing risk, relevant to courses on decision making under uncertainty and financial analysis. It offers practical strategies for real-world decision making.
Schwartz argues that an overload of choices can lead to increased anxiety, indecision, and dissatisfaction. is highly relevant to understanding the psychological impact of decision making in modern society, a theme that resonates with courses on consumer psychology and behavioral economics. It provides a deeper understanding of the challenges individuals face when making choices.
Focuses on combining data, narrative, and visuals to create compelling data stories that can influence decisions. It is highly relevant for professionals and graduate students who need to communicate data insights effectively to a non-technical audience. It builds upon data visualization by adding the crucial element of storytelling.
Considered a classic practical guide, this book outlines a structured approach to decision making focusing on identifying objectives, creating alternatives, and understanding consequences and tradeoffs. It's a valuable reference tool for anyone who needs a systematic method for tackling complex decisions. The methods presented are time-tested and widely applicable.
Comprehensive guide to deep learning, a powerful AI technique that has revolutionized fields such as computer vision, natural language processing, and speech recognition. It covers the theoretical foundations of deep learning as well as practical implementation details.
A follow-up to 'Thinking in Bets,' this book offers practical tools and frameworks for making better decisions in everyday life. It focuses on developing a robust process for decision making, even when faced with uncertainty. is well-suited for a broad audience looking for actionable strategies.
Aligned with the ACRL Framework for Information Literacy for Higher Education, this book provides practical exercises for implementing the framework's concepts. It's a crucial resource for academic librarians and instructors working with undergraduate and graduate students. It helps translate theoretical concepts into actionable teaching strategies.
Carl Sagan's बुक powerful defense of science and reason against pseudoscience and irrationality. It introduces the 'Baloney Detection Kit,' a set of tools for skeptical thinking and evaluating claims. This is an inspiring read for all audiences, particularly relevant for navigating misinformation in the contemporary world.
A seminal work in data visualization, this book provides timeless principles for creating effective and accurate graphical displays of quantitative data. It is essential for anyone serious about presenting data clearly and honestly, making it valuable for undergraduate students through working professionals. critical reference for understanding best practices in visual data interpretation.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Collection of papers by two of the most influential researchers in the field of cognitive biases. It provides a comprehensive overview of the psychology of intuitive judgment and is essential reading for anyone who wants to learn more about cognitive biases.
This guide provides a comprehensive overview of philosophical logic. It covers a wide range of topics, including the history of philosophical logic, the relationship between logic and metaphysics, and the applications of logical reasoning to ethics and law.
Julia Galef introduces the concepts of 'soldier mindset' (defending your beliefs) and 'scout mindset' (seeing the world as it is). This framework is excellent for understanding the psychological barriers to objective critical thinking and offers strategies for adopting a more open and accurate perspective. Highly relevant for all levels.
Provides a non-technical introduction to statistical thinking and how to interpret data in the context of real-world problems. It is suitable for all audiences and is particularly good for building statistical literacy and a critical approach to data presented in the media and elsewhere. It emphasizes understanding the story behind the data.
Examines the traits and techniques of 'superforecasters' – individuals who are exceptionally good at predicting future events. It provides insights into probabilistic thinking, updating beliefs based on new information, and working in teams to improve forecasts, all of which are relevant to data-driven decision making and strategic planning.
Dalio shares the principles he developed and used to achieve success in life and at Bridgewater Associates. The book outlines a systematic approach to decision making based on clearly articulated principles and radical transparency. It provides insights into strategic decision making in a professional context.
Authored by prominent figures in the critical thinking movement, this book provides a framework and tools for applying critical thinking concepts to various aspects of life. It's a practical guide for developing critical thinking as a habit and is suitable for a wide audience, including professionals.
This recent book offers practical strategies for improving decision-making and avoiding common mental traps. It translates complex ideas into accessible advice, making it valuable for a broad audience, including professionals seeking to enhance their practical critical thinking skills in daily life and work.
This academic text provides a thorough exploration of the theoretical and empirical research on thinking and decision making. It covers various models of decision making and biases, making it a valuable resource for graduate students and researchers seeking a deep understanding of the subject. It's more suitable as a core textbook for advanced study.
Applies game theory principles to a wide range of strategic interactions, providing a framework for thinking strategically and making decisions when the outcome depends on the choices of others. It's highly relevant for understanding strategic decision making in business and other competitive environments.
Focuses on the statistical concepts and methods that are most relevant to data scientists. It provides a practical approach to understanding and applying statistics for data interpretation in a data science context. It is valuable for undergraduate students, graduate students, and professionals entering or working in data science.
Exposes the gender data gap and its impact on women, highlighting how data collection and interpretation can be skewed by inherent biases. It is crucial for all audiences to understand the societal implications of biased data and the importance of inclusive data practices for accurate interpretation. It sheds light on a critical contemporary issue in data.
Klein explores decision making in naturalistic settings, focusing on how experienced professionals make high-stakes decisions under pressure and with limited information. is valuable for gaining a broader understanding of decision processes beyond purely rational models and is particularly relevant for those interested in leadership and applied decision making.
Covers the principles and techniques for creating effective data visualizations, focusing on how to represent data accurately and clearly. It's valuable for students and professionals who want to deepen their understanding of visualization best practices for data interpretation. It provides a solid foundation in the theory and practice of data visualization.
Taleb discusses the impact of rare and unpredictable events (black swans) and our tendency to rationalize them in hindsight. is relevant for understanding the limitations of traditional forecasting and decision-making models in the face of extreme uncertainty. It offers a critical perspective on how we think about and prepare for the unexpected.
This collection examines the intersection of information literacy and social justice, exploring how information professionals can address inequality and advocate for equitable access to information. It's a vital read for graduate students and professionals interested in the ethical and social responsibilities of the field. It challenges readers to consider the broader impact of their work.
While not solely focused on personal decision making, Cialdini's book explores the principles of persuasion and how they influence our decisions and compliance. Understanding these principles is valuable for recognizing external factors that can impact decision processes, relevant to courses on consumer psychology and negotiation. It provides insight into how others can influence our choices.
This guide focuses specifically on strategic decision making within a business context, offering practical steps and frameworks for developing effective business plans. It useful resource for professionals and students interested in the application of decision-making principles to business strategy. It serves as a practical guide for a specific domain of decision making.
This widely used textbook in critical thinking courses at the college level. It provides a comprehensive introduction to the subject, covering topics such as argument analysis, deductive and inductive reasoning, and fallacies. It includes numerous exercises to practice critical thinking skills and solid reference tool for students and instructors.
A classic introduction to how statistics can be manipulated and misinterpreted. is essential for anyone who needs to critically evaluate statistical information, a common element in many fields and everyday life. While older, its lessons remain highly relevant for developing a skeptical eye towards data presented in various contexts.
Provides a practical guide to creating informative data visualizations using R and ggplot2. It is suitable for undergraduate and graduate students, as well as professionals, who want to develop hands-on data visualization skills for interpreting and presenting data. It serves as a useful reference for applying visualization principles.
Explores the challenges of making predictions in a data-rich world and emphasizes the importance of probability and uncertainty in data interpretation. It's a thought-provoking read for all audiences interested in understanding the limitations and nuances of data analysis in forecasting. It provides valuable context for interpreting probabilistic data.
Offers a visually engaging collection of 50 models and frameworks for better decision making and strategic thinking. It's a practical and accessible resource that can be used as a quick reference tool for approaching different types of decisions. It provides breadth in terms of the variety of decision-making approaches.
Provides a practical, step-by-step guide to academic research for students. It covers essential strategies for navigating the information landscape, evaluating sources, and organizing research. It's particularly useful for high school and undergraduate students as a foundational text and reference.

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