Computational Humor: Promises and Pitfalls

Creating an AI device that is both easy to control and comfortable to interact with will likely require algorithms for accurately interpreting conversational speech. Homonyms and homophones represent a particular challenge in this regard, thus the study of puns and other forms of humorous wordplay can be informative. Moving beyond the simple resolution of word uncertainty to an understanding of humor is, however, problematic. The Mutual Vulnerability Theory of Laughter identifies numerous variables involved in our differentiating humorous and nonhumorous stimuli. These include available information, type and degree of relationship with others, personal history, culture, and even mood. It also suggests there will be potential liabilities for AI users, retailers, and developers resulting from even successful attempts to identify, respond to, and create humor, as all require the highlighting of vulnerabilities.