- Info
Tony Veale
An associate professor at UCD, University College Dublin, where his principal research interest is Computational Creativity (CC), specifically focusing on irony, humour, metaphor, simile, blending and analogy.
He has been a visiting professor at Fudan University, Shanghai for 13 years, as part of the international BSc. in Software Engineering which he helped establish in 2002, and at KAIST, the Korean Advanced Institute of Science & Technology, as a visiting professor in Web Science. Veale led the European coordination action on Computational Creativity, PROSECCO (Promoting the Scientific Exploration of Computational Creativity) which worked to develop the field of CC into a mature discipline. He is the author of the 2012 book Exploding the Creativity Myth: The Computational Foundations of Linguistic Creativity from Bloomsbury, co-author of the 2016 textbook Metaphor: A Computational Perspective from Morgan Claypool, co-author of the 2018 book Twitterbots: Making Machines That Make Meaning from MIT Press, and co-editor of several collected volumes of research. He is chair of the international Association for Computational Creativity (ACC), and launched the site RobotComix.com to make CC more accessible to the public. Afflatus.UCD.ie
Computer Says D’Oh! Bridging the Gap Between “Funny Peculiar” and “Funny Ha-Ha”
1 July 2022
Sala del Teatro
There are, broadly speaking, two ways of using the word “funny” in English. The first, which relates to situations that puzzle but do not amuse, is “funny peculiar,” as when we find our car keys in the fridge or questionable charges on our phone bill. This is the sense to which Isaac Asimov alludes in his observation that “The most important words in science are not ‘Eureka’ but ‘that’s funny.’” The second relates to the sense of humour, to amusing situations that make us laugh, often because they have been deliberately engineered by others to do precisely that.
It turns out that computers excel at the first sense of “funny,” both at fostering a puzzling sense of the peculiar in their users and at recognizing user behaviours that are statistically out of the ordinary, but stumble rather badly on the second. The fact that we use “funny” to describe these very different kinds of experience suggests that both share a common grounding in the incongruous, but a formal and/or algorithmic means of converting “funny peculiar” into “funny ha-ha” has proven stubbornly elusive to humour theorists and computationalists alike. The gulf between the two is most easily bridged in the case of the pun – the form of humour on which machines have shown the most success to date – since pun-words themselves serve as a shallow bridge between multiple words and senses. But machines still find it acutely difficult to look beyond the pun, to see intention in the peculiarities of others or to imbue their own creations with comical intent. However, just as one person’s funny peculiar is another’s funny ha-ha, machines can mine the large grey area between the two in ways that make their efforts at humour more than accidental if still less than entirely knowing and deliberate.
This talk will explore some of the ways in which a machine can leverage its sense of the “funny peculiar” to foster a sense of “funny ha-ha” in human audiences. I will look at different formal strategies for framing the peculiar as the funny, as in the automated generation of stories, and outline a data-driven, social application of these ideas to show how an imperfect machine sense of humour might achieve useful results at scale while still struggling to tell the amusing from the unusual.
