Published By: MIT Technology Review, 10/13/2016
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Researchers at the Indian Institute of Technology are focusing on a new strategy for recognizing sarcasm automatically. This development represents a step forward in helping computers to derive meaning from words.
Extended Discussion Questions
- The article observes that humor is, to some degree, formulaic, and suggests the potential for algorithms to create sarcastic sentences. Do you think computed humor can be as effective as humor produced by an individual human? Why or why not?
- The Turing test is a test of a machine’s capacity to exhibit behavior that is indistinguishable from a human. Would a machine that could produce sarcastic humor have a better chance at passing this test?
Published By: Encyclopaedia Britannica, Last Modified 3/14/2016 || View the Article
Explains the basics of the Turing Test.
Relating This Story to the CSP Curriculum Framework
Global Impact Learning Objectives:
- LO 7.1.1 Explain how computing innovations affect communication, interaction, and cognition.
Global Impact Essential Knowledge:
- EK 7.2.1A Machine learning and data mining have enabled innovation in medicine, business, and science.
Other CSP Big Ideas:
- Idea 3 Data and Information
- Idea 4 Algorithms
Banner Image: “Network Visualization – Violet – Crop 9”, derivative work by ICSI. New license: CC BY-SA 4.0. Based on “Social Network Analysis Visualization” by Martin Grandjean. Original license: CC BY-SA 3.0
Home › Forums › How Vector Space Mathematics Helps Machines Spot Sarcasm
Tagged: 3 Data & Info, 4 Algorithms, 7.1.1 Interaction and cognition, 7.2.1A Data impact