Unlocking Smarter Decisions: How AI Can Help—and Hinder—Our Decision-Making
I recently read a fascinating study titled Do AI Chatbots Provide an Outside View? by a group of behavioral scientists, which explores how AI assists (or sometimes hinders) human decision-making. If you don’t have the time to read the entire research paper, don’t worry—I did it for you! Here’s a breakdown of the key lessons and actionable insights from the study, along with my recommendations on how to use AI effectively to improve decision-making.
The Good News: How AI Can Help Avoid Decision Traps
The study revealed that AI is particularly effective at countering certain decision-making biases that we, as humans, often struggle with. Here’s how you can leverage AI in your business to sidestep common decision-making traps:
- Base Rate Neglect: One of the major takeaways from the study is that AI tends to outperform humans when it comes to accounting for base rates. Humans often overlook this essential part of risk assessment, especially in low-probability situations. By using AI to perform base rate analysis, you can improve the accuracy of decisions in fields such as medical diagnostics, financial forecasting, and market predictions.
- Availability Bias: The study highlights that humans frequently fall prey to availability bias—relying too heavily on readily available or recent information. AI, on the other hand, can access and analyze data without the influence of recent memories or emotionally charged events. For decisions such as product launches or market expansion strategies, using AI can provide a broader, more data-driven view, helping you avoid the limitations of your own experience.
- Cognitive Reflection: The study shows that AI is also good at engaging in deeper cognitive reflection, helping to challenge impulsive or reactive decisions. In strategic planning or crisis management, AI’s ability to methodically assess options and reflect on them can be a significant asset, helping your team avoid rash decisions.
The Bad News: Decision Traps AI Itself Falls Into
However, the study didn’t shy away from discussing AI’s flaws. In fact, it highlights several cognitive biases that AI systems are still susceptible to. While AI can help with human biases, it’s not immune to its own. Here are some common traps AI can fall into:
- Conjunction Fallacy: Surprisingly, the study found that AI platforms like ChatGPT and BingAI are prone to falling for the conjunction fallacy, just as humans are. In this fallacy, AI incorrectly ranks the probability of two events happening together as higher than the probability of a single event, which defies logic. When using AI for probabilistic reasoning, it’s important to cross-check its outputs with human judgment.
- Overconfidence: One of the key findings from the research was that AI systems often exhibit overconfidence. This overconfidence can lead to highly assured responses, even in cases where the AI’s understanding is incomplete or flawed. In high-stakes areas like finance or healthcare, it’s crucial to ensure that AI’s overconfident predictions don’t lead to costly errors—human oversight is essential in these contexts.
- Confirmation Bias: Like humans, AI systems can also display confirmation bias, especially if they are trained on biased datasets. The study highlighted that AI often reinforces the patterns it has been trained on, which can include societal biases related to race, gender, or cultural assumptions. Regularly auditing and refining AI systems is necessary to avoid perpetuating these biases.
Practical Recommendations Based on the Study
After reading the study, I’ve distilled a few key recommendations to help you maximize AI’s potential while mitigating its risks:
- Increase AI Literacy: The study emphasized the importance of AI literacy. Ensure your team understands both the strengths and weaknesses of AI. Train them to identify where AI can mitigate biases and where it may introduce its own errors, so they can apply it effectively.
- Human-AI Collaboration: One of the key findings was that AI complements human decision-making best when used in tandem with human judgment. Establish systems where AI provides data-driven insights, but final decisions are made by humans who can apply contextual, ethical, and strategic considerations.
- Continuous Monitoring: The study warns that AI models can “drift” over time—meaning that their accuracy and reliability may fluctuate. Keep a close eye on AI systems, especially if they are integrated into critical decision-making processes. Regular updates and human intervention will ensure that AI outputs remain reliable and free of unintended biases.
- Prompt AI for Cognitive Reflection: Use AI not just for analysis, but also to generate alternative viewpoints. One of the highlights of the study is AI’s strength in cognitive reflection, which means it can help explore different scenarios and challenge assumptions. Prompt your AI systems to consider counterfactuals or “what if” scenarios to improve decision quality.
- Implement a Common Decision-Making Framework: One of the most effective ways to help your team avoid decision traps—whether they are using AI or not—is by implementing a common Decision-Making Framework. This framework will guide your team in evaluating risks, weighing alternatives, and recognizing biases (both human and AI-driven). By following a structured approach to decision-making, your team will be better equipped to recognize and avoid decision traps, fostering more consistent and thoughtful decisions across your organization.
Conclusion: AI is a Powerful Tool—But Not a Perfect One
Based on the insights from the study, it’s clear that AI has great potential to improve decision-making by overcoming human biases. However, it’s equally clear that AI can fall into its own traps if left unchecked. The key is to balance AI’s strengths with human oversight and strategic thinking. By doing so, you can make better, more informed decisions that drive your business forward.
Remember, I read the study so you don’t have to—but now you can apply these lessons to empower your team and strengthen your decision-making processes with the help of AI.
Want to learn more about Decision Traps? Check out this pre-recorded webinar.
Chris Seifert is the author of Enabling Empowerment: A Leadership Playbook for Ending Micromanagement and Empowering Decision-Makers. With over two decades of experience in transforming organizations through strategic leadership and decision-making frameworks, Chris has helped teams cut through bottlenecks, optimize capital project budgets, and build cultures of accountability. He is passionate about teaching leaders how to empower their teams to make smarter, faster decisions without sacrificing business value.
