A chatbot is perceived as more humanlike and likeable if it includes some jokes in its output. But most existing joke generators were not designed to be integrated into chatbots. This paper presents Witscript, a novel joke generation system that can improvise original, contextually relevant jokes, such as humorous responses during a conversation. The system is based on joke writing algorithms created by an expert comedy writer. Witscript employs well-known tools of natural language processing to extract keywords from a topic sentence and, using wordplay, to link those keywords and related words to create a punch line. Then a pretrained neural network language model that has been fine-tuned on a dataset of TV show monologue jokes is used to complete the joke response by filling the gap between the topic sentence and the punch line. A method of internal scoring filters out jokes that don't meet a preset standard of quality. Human evaluators judged Witscript's responses to input sentences to be jokes more than 40% of the time. This is evidence that Witscript represents an important next step toward giving a chatbot a humanlike sense of humor.

A previous paper presented Witscript, a system for generating conversational jokes that rely on wordplay. This paper extends that work by presenting Witscript 2, which uses a large language model to generate conversational jokes that rely on common sense instead of wordplay. Like Witscript, Witscript 2 is based on joke-writing algorithms created by an expert comedy writer. Human evaluators judged Witscript 2's responses to input sentences to be jokes 46% of the time, compared to 70% of the time for human-written responses. This is evidence that Witscript 2 represents another step toward giving a chatbot a humanlike sense of humor.

Previous papers presented Witscript and Witscript 2, AI systems for improvising jokes in a conversation. Witscript generates jokes that rely on wordplay, whereas the jokes generated by Witscript 2 rely on common sense. This paper extends that earlier work by presenting Witscript 3, which generates joke candidates using three joke production mechanisms and then selects the best candidate to output. Like Witscript and Witscript 2, Witscript 3 is based on humor algorithms created by an expert comedy writer. Human evaluators judged Witscript 3's responses to input sentences to be jokes 44% of the time. This is evidence that Witscript 3 represents another step toward giving a chatbot a humanlike sense of humor.

Read here how my Formal Theory of Fun uses the concept of compression progress to explain not only science but also art, music, and humor.[AC06][AC09][AC10] Consider the following statement: Biological organisms are driven by the "Four Big F's": Feeding, Fighting, Fleeing, Mating. Some subjective observers who read this for the first time think it is funny. As the eyes are sequentially scanning the text the brain receives a complex visual input stream. The latter is subjectively partially compressible as it relates to the observer's previous knowledge about letters and words.

Creating noodling piano tunes and endless configurations of cat drawings with AI may not sound like an obvious project for Google, but it makes a lot of sense to Douglas Eck. Eck has spent about 15 years studying AI and music, and these days he's a research scientist on the Google Brain team, leading Magenta--Google's open-source research project that's aimed at making art and music with machine learning. He spoke to MIT Technology Review about how Google is producing new sounds with deep neural networks, where Magenta is taking AI music, and why computers suck at telling jokes. Below is an edited excerpt of the interview. Premium MIT Technology Review subscribers can listen to the full interview. Using AI to make art isn't new, so what's unique about Google's approach?