Prof Scott E Fahlman
“The Birth, Evolution and Spread of the Emoticon”
The :-) ‘smiley’ and :-( ‘frowny’ emoticons are now very familiar to users of the Internet, Email, and social media. I first suggested that we use these character-based symbols for online communication in a message that I posted on a Carnegie Mellon University online ‘bulletin board’ on September 19, 1982. At the time I was a young faculty member in CMU’s Department of Computer Science, doing research on AI.
The posting of this message is considered by many, including the Guinness Book of World Records, to be the birth of ‘the digital emoticon’, though the term ‘emoticon’ was coined years later — I don’t know by whom. My silly idea of using text characters to make little faces ‘went viral’ on the primordial computer networks of the day, long before ‘going viral’ was a thing. The Internet was created in the U.S. that very year, and whenever a new site was added to the network, the emoticons soon took root there.
This led to the development of many more text-based emoticons. And then in the 1990s (when the technology was ready to support it) the emoticon idea gave rise to the thousands of graphical emoji that are used today by people in every country of the world, as part of their daily lives. By most estimates, emoticons and emojis are now used several billion times every day.
In this talk I will describe why and how the idea of text-based emoticons popped up, how they spread all around the world, and how they mutated as they spread. I’ll also say a bit about what the future might hold for these symbols, and whether they might ultimately evolve into a complete graphical language, replacing text in at least some instances.
Biography
Scott E. Fahlman, Professor Emeritus at Carnegie Mellon University, earned his PhD in Artificial Intelligence from MIT in 1977 and is a fellow of the AAAI. With broad interests in AI, Fahlman has contributed to various domains including planning, reasoning, and natural language processing, among others. He is currently authoring a book advocating a symbolic, knowledge-based approach to commonsense AI, positioning it as a more reliable and efficient alternative to the popular but criticized Large Language Models.
