Non sequitur is a Latin phrase that literally translates to “it does not follow.” In the context of logic, a non sequitur is a statement that does not logically follow from the previous statement. Non sequitur reasoning can be seen in everyday life, in the form of fallacious arguments. For example, a person might say, “It’s raining outside, so I’m going to buy a new umbrella.” This statement is a non sequitur because it does not logically follow that one should buy a new umbrella simply because it is raining.
Non sequitur reasoning is also common in the field of artificial intelligence (AI). AI systems rely on input data to generate outputs. However, without proper context, AI systems may draw incorrect conclusions from the data they are provided. This is known as the non sequitur problem. For example, an AI system might be given the task of predicting whether a particular person is likely to commit a crime. The AI system might draw the incorrect conclusion that this person is likely to commit a crime simply because they are from a particular ethnic group. This is a non sequitur because the data does not support the conclusion that a person from a certain ethnic group is more likely to commit a crime than any other person.
Non sequitur reasoning is also seen in the field of psychology. It is often observed in people who have difficulty with logical reasoning or are prone to cognitive biases. For example, a person might draw the conclusion that a particular political candidate is the best choice for office simply because they are from the same political party as the person making the statement. This is a non sequitur because it does not logically follow that the candidate is the best choice for office simply because they are from the same political party.
Non sequitur reasoning is a common problem in many areas of life, from everyday conversations to AI systems. It is important to recognize and address non sequitur reasoning in order to avoid drawing incorrect conclusions.
References
Forsythe, M. (2020). Non Sequitur: Definition, Examples, and Fallacies. Retrieved from https://www.verywellmind.com/what-is-a-non-sequitur-2795785
Griffiths, T. L., & Tenenbaum, J. B. (2005). Structure and strength in causal induction. Cognitive Science, 29(4), 423-467. https://doi.org/10.1207/s15516709cog0000_70
Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80(4), 237-251. https://doi.org/10.1037/h0034747