Uncertainty Matrix: How To Deal With Uncertainty (And Gain From It) & What AI can teach us about human bias in decision making

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Sep 08, 2023

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Uncertainty Matrix: How To Deal With Uncertainty (And Gain From It) & What AI can teach us about human bias in decision making

Navigating Uncertainty and Overcoming Bias: Insights from AI and Human Psychology

Introduction:

Uncertainty and bias are two challenges that individuals and organizations face when making decisions. Uncertainty can cause anxiety, while bias can lead to skewed perspectives and limited understanding. In this article, we will explore strategies for managing uncertainty and overcoming bias by combining insights from the "Uncertainty Matrix" and the field of artificial intelligence (AI).

Understanding Uncertainty:

The "Uncertainty Matrix" categorizes knowledge into known knowns, unknown knowns, known unknowns, and unknown unknowns. Known knowns are things we know and are aware of, while unknown knowns refer to hidden knowledge we possess but may not be aware of. Known unknowns are risks we are aware of, and unknown unknowns are risks we don't even know exist. To navigate uncertainty effectively, it is essential to challenge what we think we know, discover our hidden knowledge through learning and reflection, and mitigate known risks while preparing for unknown risks.

Overcoming Bias:

Human bias is a prevalent problem that influences decision-making processes. Our limited knowledge and preference for familiarity can lead to biased perspectives and decisions. For example, the lack of diversity in clinical trials is a result of the long-held belief that the male perspective is the norm. To overcome bias, we must actively pursue diversity and seek out alternative perspectives. This is where AI and the ensemble method can provide valuable insights.

Harnessing Cognitive Diversity in AI:

The ensemble method in AI harnesses cognitive diversity by training multiple algorithms on small samples of data and aggregating their collective results. Each algorithm may make errors on its own, but when combined, their collective insight surpasses that of a single algorithm trained on all the data. This is because algorithms make different types of errors and learn from each other, improving their performance through co-evolution. Similarly, humans can benefit from diverse perspectives that come from different life experiences, leading to a more accurate understanding of the truth and better decision-making.

Taking Action:

  • 1. Challenge assumptions: Continuously question what you think you know and avoid over-relying on historical data. Embrace a growth mindset that values learning and adaptation.
  • 2. Seek diversity: Actively pursue diverse perspectives by engaging with individuals who have different backgrounds, experiences, and perspectives. This will help overcome bias and broaden your understanding of complex issues.
  • 3. Embrace collective wisdom: Just as AI algorithms benefit from collaboration, humans should embrace the power of collective wisdom. Engage in collaborative decision-making processes and leverage the strengths and weaknesses of diverse individuals to make better decisions for society.

Conclusion:

Uncertainty and bias are significant challenges in decision-making, but by adopting strategies from the "Uncertainty Matrix" and AI, we can navigate uncertainty more effectively and overcome bias. Challenging assumptions, seeking diversity, and embracing collective wisdom are actionable steps towards making better decisions and fostering a more inclusive and informed society. As we continue to learn from AI and understand the importance of cognitive diversity, we can build a better future based on a more accurate understanding of the truth.

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