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Beyond the Obvious

How to Think in the Age of Generative AI

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.

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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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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Career center

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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