Language reflects and supports the ability to reason about the likelihood or goodness of unrealized possibilities–a critical capacity underlying practical decisions, scientific explanations, moral judgments, legal agreements, and attitudes like regret and relief. Conditional and modal expressions are ways to talk about what is, will be or would have been likely or preferable, and to flag contingencies and degrees of confidence. In English, such expressions (examples are ‘if-then’ sentences and auxiliaries like ‘must’ and ‘might’) have been extensively studied. However, languages other than English employ radically different ways to express similar notions, and much remains unknown about the cross-linguistic picture with regard to both the variety of expressive means and the uniformity of the underlying concepts. This project works towards filling that gap. Its linguistic goal is to elucidate how general concepts and cognitive abilities interact with the grammatical idiosyncrasies of different languages. Its wider applications include language teaching and artificial intelligence, where the ability to use and understand modals and conditionals correctly helps improve the quality of machine translation systems and human-computer interfaces.

This project is funded by:

• National Science Foundation: #2116972, "Research on conditional and modal language" (M. Kaufmann, PI; S. Kaufmann, Co-PI), 2021-23.
• UConn College of Arts and Sciences Research in Academic Themes grant, "Conditional Thought and Talk" (Mitch Green, Magda Kaufmann, Stefan Kaufmann), 2022-23.