Why AI? Overcoming Human Cognitive Biases

We have traditionally relied on human intellect and intuition for decision-making. However, these processes are often flawed due to a variety of cognitive biases, such as:

• Availability bias: Basing decisions on easily recalled information rather than considering all relevant data

• Bandwagon effect: Adopting opinions or beliefs because they are popular or endorsed by others

• Hindsight bias: Believing, after an event has occurred, that one would have predicted or expected the outcome

• Illusory superiority: Overestimating one’s abilities and underestimating the abilities of others

• Negativity bias: Giving more weight to negative information than positive information

• Sunk cost fallacy: Continuing to invest in a decision based on the amount already invested rather than evaluating the current and future value of that decision

• Overconfidence bias: Overestimating the accuracy of one’s beliefs or predictions

• Anchoring bias: Focusing too much on one piece of information while ignoring others

• Apophenia: Finding connections between unrelated events or data points

• Cognitive dissonance: Disregarding or modifying conflicting information to maintain existing beliefs

• Confirmation bias: Interpreting information in a way that confirms pre-existing beliefs.

• Logical fallacy: Allowing irrational factors to influence decision-making or conclusions.

• Truthiness: Believing in the logic of a process based on the plausibility of the outcome.

AI has the potential to overcome many of these human biases in decision-making. However, it is crucial to note that AI can also exhibit these biases if they are present in its programming. Additionally, AI has its own set of potential flaws that need to be considered and addressed.