Understanding the Logic Behind 'Yes' and 'No'

by Monica Joshi

Do you like chocolate? Yes. Will you ever give up eating it? No. It's relatively easy to understand the difference between 'yes' and 'no'. However, according to new research, understanding the behaviour and interpretation of the words 'yes' and 'no' is surprisingly much more difficult to pin down.

In a paper published in the scholarly journal Language, two linguists have examined the workings of the words 'yes' and 'no'. The linguists contend that understanding these words has led them to new insights concerning the understanding of questions, as well as statements more generally.

Floris Roelofsen, from the University of Amsterdam, and Donka F. Farkas, from UC – Santa Cruz, have provided a comprehensive account of polarity particles. Polarity particles refer to the intricate pattern of the distribution of words across languages.

'Yes, it is' and 'No, it isn't', for instance, are acceptable answers to the question 'Is the door open or not?', but they are not acceptable answers to the question 'Is the door open or is it closed?'. In the former case, the question is asking you whether 'A' or 'Not A' is the case, whereas in the second case, the question is asking whether 'A' or 'B' is the case. This slight difference in the language makes the acceptable answers vary slightly.

The distribution of these particles, as it turns out, is also affected by the polarity of the question that they answer. For example, 'No, he hasn't' and 'Yes, he hasn't' are acceptable responses to 'Ben has not called today?'. Specifically, given that the question is a negative sentence, it is acceptable to affirm a negative (as in 'Yes, he hasn't'). However, in response to the question 'Ben has called today?', 'Yes he has' is acceptable, but 'No, he has' is not.

Farkas and Roelofsen are building on previous insights from semantics and discourse models. They are also building on quantitative surveys of how speakers judge various responses to such questions. The framework they create not only explains the distribution and interpretation of these particles in English, but also predicts what patterns one expects to find across languages. These predictions are then checked and verified against data from French, German, Romanian, and Hungarian.

Understanding the semantics and logic behind these 'Yes' or 'No' questions and responses to them will be helpful in the possible building of AI's brain. Nuances like these can make or break the ways in which we develop future AI to resemble the human brain.

Furthermore, Professor Steven Pinker illustrates how the study of linguistics can give us a rare window into the conscious mind.