Learning Generative AI #9: Making Better Decisions with Generative AI
Generative AI can be a powerful tool to help you make better decisions. Don't hesitate to try it.
Tools like Claude, ChatGPT, and Perplexity are unlike anything we have had before. They differ from search engines that merely find information for you. They are not like computer programs that follow simple rules. Instead, these generative AI systems can engage in genuine conversations, comprehend complex situations, generate creative ideas, and offer advice tailored to your specific needs. When used correctly, they can significantly enhance your decision-making process while still allowing you to retain control over the final choice.
This article is an extract from my latest book: Decision Making: The Key to Success in Life and Business. It is now available from Amazon in print, Kindle, and Audible versions. https://www.amazon.com/Decision-Making-Business-Practical-Decisions-ebook/dp/B0FB9GPG97/ref=sr_1_1
This article illustrates how Generative AI can serve as a valuable partner in decision-making. We will explore how AI can assist you in gathering and organizing information, identifying options you may overlook, recognizing problems in your reasoning, and structuring your thoughts. We will also discuss the limitations of these systems and what to be cautious about. You will discover specific scenarios where AI can aid in various types of decisions, practical methods for collaborating effectively with these systems, and key considerations to keep in mind as you begin using AI in your decision-making process.
Generative AI Can Improve The Way We Make Decisions
Before we examine specific ways to utilize AI, let's consider how these new tools alter the entire decision-making process.
From too little information to just the right amount
In the past, making good decisions was difficult because we lacked sufficient information. We had limited access to knowledge, examples, and diverse viewpoints. The internet helped by providing us access to vast amounts of information, but this created a new issue: we now had too much information and no practical way to sift through it. When researching an important decision online, you often feel overwhelmed by information, encounter conflicting advice without context, and struggle to differentiate credible sources from unreliable ones.
AI helps solve this problem by acting as an innovative librarian and organizer. Instead of merely providing thousands of search results or repeating facts, systems like Claude, ChatGPT, and Perplexity can sift through vast amounts of information and deliver clear, tailored summaries specific to your situation. They can integrate different viewpoints, highlight key considerations, and reveal patterns that may not be apparent when examining individual sources.
When Alice decided whether to accept a job offer in another city, her usual research was overwhelmed by scattered information about living costs, neighborhood safety, school quality, and cultural activities. By using a Generative AI assistant, she described her specific situation, values, and concerns. She received a clear overview that connected all these factors in ways relevant to her family's unique circumstances. This personalized summary helped her identify which factors mattered most for her decision, rather than getting lost in disjointed details.
Expanding your thinking power
Even the most intelligent individuals have limitations when making complex decisions. Our brains can typically manage only about seven pieces of information at a time. We struggle to think systematically about more than a few options at once. Often, we overlook essential factors until someone points them out to us. We tend to focus on what seems most obvious while missing less apparent but potentially significant factors.
AI helps overcome these limits by effectively expanding your thinking capabilities. These systems can monitor and analyze numerous factors simultaneously, systematically explore a variety of options, and highlight aspects that human decision-makers often overlook due to mental shortcuts or a limited perspective.
When James was helping his daughter choose colleges, he initially concentrated on reputation, academic programs, and cost. His conversation with Claude prompted him to consider additional factors he had not adequately thought about: graduation rates for students with backgrounds similar to his daughter's, mental health support services, internship placement records, and the strength of the alumni network in his daughter's intended career field. This broader set of considerations did not decide for him, but it ensured he wasn’t overlooking potentially essential factors due to limited thinking capacity.
Making decision assistance more personal
Generative AI excels at personalizing frameworks for your specific situation. Rather than providing generic advice, these systems can tailor decision-making approaches to your unique circumstances, priorities, constraints, and preferences. They can assist you in developing customized methods for evaluating options, suggesting personalized strategies for gathering information, and adapting established frameworks to address your distinct decision context.
When April was deciding whether to start her own business after twenty years in corporate management, general entrepreneurship resources felt too generic for her needs. Through conversations with an AI assistant, she developed a personalized decision framework that incorporated her specific industry expertise, financial circumstances, comfort with risk, family considerations, and timeline for retirement. This tailored approach allowed her to evaluate the opportunity through a lens that reflected her unique circumstances rather than adhering to generic business advice designed for very different situations.
Specific Ways AI Can Help Throughout
Your Decision Process
AI can improve virtually every stage of decision-making. Let's examine specific ways it can assist you throughout your decision-making journey.
Getting clarity on what you are really deciding
Before gathering information or evaluating options, it is essential to clarify what you are truly deciding and why. AI can act as an effective thinking partner in this crucial first stage.
Through thoughtful questions, these tools can help you distinguish between surface-level decisions and the deeper purposes they serve. They can help you identify assumptions you haven’t stated, clarify your fundamental goals, and properly define the decision to ensure you are addressing the right question rather than just treating the symptoms of bigger issues.
Robert initially thought, "Should I renovate my current home or buy a new one?" Through conversations with an AI assistant, he realized that this surface question concealed deeper considerations about his changing lifestyle needs as his children left for college, his desire for stronger community connections, and his evolving priorities regarding commute time versus living space. This clarification helped him understand that his fundamental decision was about his overall lifestyle priorities for the next phase of life, rather than merely a housing transaction decision.
Gathering and organizing information completely
Once you have clarified your decision-making purpose, AI excels at helping you gather and organize relevant information without getting bogged down in details.
Generative AI can identify categories of information you may not have considered, suggest targeted questions for investigation, highlight potential gaps in information, and transform complex data into easy-to-understand summaries centered on the key aspects of your decision. Most importantly, they can help organize this information based on what is relevant to your specific situation, rather than merely collecting facts.
When Marcus considered a career change from marketing to data science, he initially focused too narrowly on salary comparisons and certification requirements. His AI assistant helped him develop a comprehensive strategy for gathering information that included interviewing professionals who had made similar transitions, investigating typical day-to-day work experiences rather than just credentials, researching age bias in entry-level positions, understanding opportunity costs during the transition period, and analyzing how his existing marketing expertise might offer unique advantages in data roles. This thorough approach ensured that his decision was based on a complete understanding rather than just a few easily accessible data points.
Coming up with creative options
One of AI's most significant contributions is its ability to expand the range of options beyond your initial considerations. Many poor decisions arise not from faulty evaluations but from the failure to consider better alternatives that never entered your mind.
With their broad knowledge base and ability to forge new connections, Generative AI can suggest alternatives you might not have considered, merge elements from various options into hybrid solutions, uncover non-obvious answers that others in similar situations have found, and generally broaden your thinking beyond conventional choices.
When Lisa struggled with work-life balance as a consulting partner and a parent of young children, she initially saw her options as either continuing her demanding role or leaving the firm entirely. Through dialogue with her AI assistant, she discovered additional possibilities: proposing a specialized role that focused exclusively on her highest-value client activities, creating a job-sharing arrangement with another partner seeking flexibility, developing a remote working approach that reduced travel while maintaining client relationships, and establishing a consulting specialization that required less reactive availability. This expanded set of options enabled her to create a solution that balanced both career fulfillment and family priorities, rather than sacrificing either.
Structured ways to evaluate and compare options
Once you have generated a good set of alternatives, generative AI tools can help structure your evaluation process to ensure you conduct a thorough and balanced assessment.
They excel at creating tailored evaluation frameworks, identifying relevant criteria you may overlook, organizing complex trade-offs, conducting sensitivity analyses to examine how different priority schemes influence outcomes, and generally introducing systematic rigor to your comparison process.
When James evaluated three job offers, his initial comparison focused mainly on salary and title. His AI assistant helped him create a comprehensive evaluation framework that included fourteen additional factors: growth potential, mentorship quality, work culture alignment, commute impact, benefits details, company stability, team composition, decision authority, travel requirements, flexibility policies, industry trajectory, skills development, ethical alignment, and potential exit opportunities. More importantly, the system helped him clarify which factors truly mattered most, based on his specific values and life circumstances, rather than defaulting to conventional priorities.
Looking for blind spots and mental traps
Even with excellent information and structured evaluation, human decision-makers remain susceptible to mental shortcuts and blind spots. Generative AI can act as an effective bias checker and blind spot detector.
These tools can help identify potential biases that affect your thinking, suggest alternative perspectives you might not have considered, argue against your preferred option to test its validity, highlight the viewpoints of people impacted by your decision that you may have overlooked, and generally assess your thinking for strength from multiple angles.
When Sophia was deciding whether to accept a significant promotion that required relocation, she felt confident in her analysis, which favored acceptance. Her AI assistant helped her identify several potential blind spots in her thinking: giving too much weight to immediate career advancement relative to long-term family preferences, underestimating the psychological impact of moving away from her support network, focusing on best-case scenarios rather than likely outcomes based on others' experiences, and failing to consider how the role might change during economic downturns. This bias checking did not alter her decision, but it ensured that it was made with a clearer understanding of potential risks and trade-offs.
Planning how to carry out your decision
After reaching a tentative decision, generative AI can help develop robust implementation strategies and contingency plans to enhance your chances of success.
These tools excel at identifying potential implementation challenges, developing strategies to mitigate key risks, creating structured timelines with appropriate milestones, suggesting methods to monitor progress, and formulating backup plans for various potential scenarios.
When Thomas decided to pursue an executive MBA while continuing his full-time job, his AI assistant helped him develop a comprehensive implementation plan to address potential challenges: creating a realistic study schedule that accounts for work surges and family commitments, developing strategies for managing energy as well as time, establishing communication methods with key people affected by his reduced availability, identifying specific work responsibilities that require delegation, creating early warning signs for unsustainable overcommitment, and developing backup plans for academic emergencies that coincide with work crises. This detailed implementation plan significantly increased his confidence in the feasibility of the decision.
Practical Ways to Use AI for
Better Decision Making
Consider these practical strategies to maximize the benefits of AI assistance while minimizing potential problems.
Keep clear ownership of your decisions.
The most important principle when using AI for decision support is to maintain clear ownership of your decisions. These systems should serve as thinking partners and information processors, not as replacements for decision-making.
Effective AI collaboration involves using these tools to enhance your decision-making process while accepting full responsibility for the final choice and its consequences. This mindset prevents both over-reliance on AI recommendations and the dismissal of valuable insights these systems may provide.
Use different ways of interacting.
Different decision phases benefit from distinct AI interaction approaches. Tailoring your interaction style to your current decision stage greatly enhances effectiveness.
For open-ended exploration and initial problem framing, conversational dialogue helps uncover considerations you might not have anticipated. For systematic evaluation, clearly structured formats, such as decision matrices or weighted criteria analysis, provide a more disciplined assessment. For bias checking, challenging questions help test your thinking more rigorously than cooperative dialogue.
Use the best of both human and AI Thinking.
The most powerful decision-making processes utilize the complementary strengths of human intuition and AI analytical capabilities, rather than relying exclusively on either.
Human decision makers generally excel at understanding context, articulating values, recognizing intuitive patterns, making creative leaps, and considering emotional and social factors. AI systems, on the other hand, typically excel at processing comprehensive information, generating systematic options, comparing details across multiple dimensions, detecting biases, and checking for logical consistency.
Learn to ask good questions.
The quality of AI assistance depends significantly on how you frame your requests. Learning to create effective prompts substantially improves the quality of decision support.
Effective decision prompts typically include: specific context about your situation, a clear explanation of the decision you are facing, relevant constraints and considerations, your current thinking, and an explicit description of what type of assistance you are seeking. This structured information helps the AI system provide relevant, personalized guidance rather than generic advice.
Real Examples of AI-Enhanced Decisions
To illustrate these principles in action, let's examine several real-world examples of AI enhancing various types of decisions.
Career changes and professional growth
Miguel, a mid-career financial analyst, felt increasingly drawn to data science but was uncertain whether a career transition made sense given his age, family responsibilities, and established expertise. His initial research left him feeling overwhelmed by the disconnected information regarding various certification programs, salary potential, and job prospects.
Working with an AI assistant, Miguel developed a systematic approach to this complex decision. The system helped him identify critical questions he had not considered: How transferable were his existing financial modeling skills to data science roles? What specific industries would value his hybrid finance and data background? What was the actual day-to-day experience of data scientists compared to his current work? Which specific technical skills would provide maximum leverage given his background?
Most importantly, the AI assistant helped Miguel break down this seemingly binary decision (switch careers or stay put) into a spectrum of options with varying levels of commitment and risk: integrating more data science into his current role, pursuing a hybrid position that utilized both skill sets, exploring freelance projects before full commitment, or structuring a phased transition while maintaining financial stability.
The AI system did not make Miguel's decision; however, it transformed a vague, anxiety-producing dilemma into a structured exploration with concrete options, relevant information, and a personalized evaluation framework that reflected his specific circumstances. His ultimate choice to pursue a specialized hybrid role focusing on algorithmic trading models emerged from this enhanced decision-making process rather than from directly following AI recommendations.
Major purchases and financial commitments
Elena and Thomas were considering purchasing their first home after relocating to a new city for job opportunities. As first-time homebuyers unfamiliar with the local market, they felt overwhelmed by the complexities of evaluating neighborhoods, determining their actual budget, and assessing whether buying made more sense than continuing to rent.
Through conversations with a generative AI assistant, they developed a comprehensive decision-making approach that went beyond simplistic rent-versus-buy calculators. The system helped them create a personalized evaluation framework that included factors they had not adequately considered: commute patterns at their specific work hours (not just distance), school quality trajectories rather than just current ratings, neighborhood age diversity beyond typical demographic statistics, walkability to amenities that matched their specific preferences, and future development plans that might affect property values.
Most importantly, the generative AI assistant helped them recognize a timing element they had overlooked. Their uncertainty about whether they would stay in this city beyond 5 to 7 years significantly altered the financial equation compared to standard 30-year mortgage assumptions. This insight led them to develop a hybrid approach: purchasing a modestly priced condominium in an appreciating area with strong rental potential rather than stretching for their "forever home" in the most established neighborhood.
Health and medical decisions
Robert faced a tough decision after being diagnosed with early-stage prostate cancer. His doctor presented several treatment options: surgery, radiation therapy, or active surveillance. Each option had different implications for survival rates, quality of life, and side effect profiles. The medical statistics and conflicting recommendations from friends left him uncertain about how to proceed.
Working with a generative AI assistant, Robert established a structured approach to this crucial decision. The system helped him translate complex medical statistics into personalized risk assessments tailored to his specific age, health profile, and cancer characteristics. It pinpointed key questions to discuss with his doctor that he had not previously considered, including how treatment success rates varied by physician experience and hospital volume for his specific condition.
Most importantly, the AI assistant helped Robert clarify his personal values and priorities concerning different potential outcomes. Through carefully structured reflection questions, he gained insight into his specific concerns regarding longevity, possible side effects, recovery time, and the invasiveness of treatment. This values clarification was crucial for evaluating the medical options from his personal perspective rather than through generic statistical comparisons.
The AI system did not recommend which treatment Robert should choose, nor did it provide medical advice beyond what was already established in research. Instead, it helped him organize complex information, identify key questions for his healthcare providers, and clarify his values as they related to the medical options. His ultimate decision to opt for active surveillance, with a clearly defined monitoring protocol and specific triggers for intervention, reflected both the medical realities and his priorities.
Relationship and family decisions
Hope and Charles faced a challenging parenting decision concerning their talented 16-year-old daughter. She had been offered an opportunity to train with an elite athletic program, which would require her to live away from home during her final two years of high school. While this opportunity could be transformative for her athletic development, it raised concerns about her academic progress, social development, and family dynamics.
Using a generative AI assistant, they created a more comprehensive framework for this complex decision. The system assisted them in identifying considerations they had not fully explored, including research on psychological outcomes for adolescents in similar high-performance environments, the educational impacts beyond just academic measures, the importance of their daughter's voice in the decision-making process, and potential middle-ground alternatives they had not considered.
Most helpfully, the AI assistant provided a structured framework for family discussions, ensuring that all perspectives, including their daughter's, were thoroughly explored rather than allowing the loudest voices or strongest initial opinions to dominate the conversation. This guided approach helped the family move beyond simplistic pro and con lists to a deeper exploration of underlying values, fears, and aspirations related to the opportunity.
Understanding the Risks of Using Generative AI
While generative AI offers powerful decision support capabilities, it is essential to acknowledge its fundamental limitations and potential risks for responsible use.
1. Information problems and made-up facts
Current generative AI systems have significant limitations in their information processing capabilities. Their training data has specific cutoff dates, which means they lack awareness of recent developments that could be crucial for your decision-making. They sometimes generate false information, presenting statements that sound plausible but are factually incorrect with the same confidence as accurate information. Additionally, they may possess biases or blind spots in their training data that influence their responses.
2. Problems with values and what matters
While generative AI systems strive to present balanced perspectives, they inevitably reflect particular values and assumptions that may not align with your personal beliefs. These systems cannot determine what should matter most to you in your specific circumstances. That remains fundamentally human work.
3. Problems with nuance and context
Current generative AI systems sometimes struggle with nuanced cultural, social, or interpersonal dynamics that are critical to your specific decision context. They might overlook subtle emotional considerations, cultural factors, or relationship dynamics that would be clear to humans familiar with your situation.
4. The risk of feeling less responsible
Perhaps the most significant risk in AI-assisted decision-making is the phenomenon of responsibility diffusion, a subtle psychological tendency to feel less personally accountable for decisions made with the aid of generative AI. This can result in diminished ownership, reduced critical evaluation, and a potential abdication of moral responsibility for outcomes.
Conclusion:
AI as Decision Partner, Not Decision Maker
Generative AI offers unprecedented capabilities to enhance human decision-making. It can expand our thinking capacity, help us process complex information, generate creative alternatives, identify potential blind spots, and structure our evaluation processes. When used thoughtfully, these systems can significantly improve decision quality across virtually every area of life.
The most successful approaches leverage the complementary strengths of human and artificial intelligence: human values clarity, contextual understanding, creativity, and moral responsibility, while AI offers information processing capacity, systematic comparison abilities, and bias checking capabilities.
As these technologies continue to evolve rapidly, they will likely offer increasingly sophisticated decision support capabilities. Future systems may provide more personalized assistance based on your decision history, offer more nuanced understanding of complex social and emotional factors, and facilitate collaborative decision processes involving multiple people with different perspectives and priorities.
Despite these advancing capabilities, the fundamental principle remains constant: decisions that matter deserve human ownership. The wisdom to make informed decisions does not come from giving choices to algorithms, but from thoughtfully incorporating AI assistance into decision-making processes that remain fundamentally human. The ultimate goal is not AI-directed decisions but AI-enhanced human judgment. We want decisions that reflect your deepest values and priorities while benefiting from unprecedented analytical support.
As you navigate life's countless decision points, think about how these powerful new tools could enhance your decision-making process. How might they assist you in organizing complex information? How could they expand your consideration of alternatives? How might they help uncover blind spots in your thinking?
This is the eleventh article in my series on Generative AI, each covering different ways to use it. If you want to read the others, here is the list and links.
Learning Generative AI #7: The Transformative Power of Generative AI in Education
Learning Generative AI #6: Apple Intelligence
Learning Generative AI #5: An Invaluable Investing Tool
Learning Generative AI #4: Planning Your Travel
Learning Generative AI: #3 Getting Useful Medical Information
Learning Generative AI: #2 Satisfying Your Curiosity
Learning to Use Generative AI: #1 Writing and Editing
Explanation and Access to Leading Generative AI Systems
If you want to read my articles on generative AI and emerging technologies, as well as all the articles in this series, click this link to access an extensive and interesting library.
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Nice article.. enjoyed it.