Is it feasible to build a computer with a sense of taste? In response to this question, IBM Research scientists developed HyperTaste, a chemical taste sensing tool. It performs analyses and detects the chemical composition of liquids using its "electronic tongue" status. "HyperTaste was inspired by advances in AI and machine learning to mimic human senses like sight and hearing for recognizing images and interpreting speech. We wanted to present a new lens for chemical sensing," explained Patrick Ruch from IBM Research, the coauthor of the study.

AI that can generate new flavor combinations from scratch is nothing novel, but what about models that can taste those flavors like a human? In a recently published paper ("A portable potentiometric electronic tongue leveraging smartphone and cloud platforms") and an accompanying blog post, researchers at IBM's Zurich-based R&D division detailed Hypertaste, an artificial tongue designed to fingerprint beverages and other liquids "less fit for ingestion." Such a system could be used to guarantee supply chain safety for food and drinks, proposed IBM research staff member Patrick Ruch, who noted that there's currently little to verify that packages contain what's on the label apart from conducting costly experiments. Suppliers acting in bad faith could insert lower-quality products into the supply chain, while counterfeiters could fake a real product by adding the few chemical compounds which are most likely to be tested for in a lab. "There are many substances out there that we would like to'taste' without actually putting them in our mouth. Consider a government agency interested in an on-the-fly water quality check of a lake or river at a remote location, a manufacturer wanting to verify the origin of raw materials, or a food producer trying to identify counterfeit wines or whiskeys," wrote Ruch.

In this article some formal, content-related and procedural considerations towards the sense of humor are articulated and the analysis of both everyday humor behavior and of comic styles leads to the initial proposal of a four factor-model of humor (4FMH). This model is tested in a new dataset and it is also examined whether two forms of comic styles (benevolent humor and moral mockery) do fit in. The model seems to be robust but further studies on the structure of the sense of humor as a personality trait are required.

Based on recent experiences between a laughing virtual agent and a human user at the intersection AI and humor and laughter, this paper aims to highlight some of the psychological considerations, when conducting AI and humor experiments. The systematic and standardized approach outlined in this paper will demonstrate how to reduce error variance that may be caused by confound variables such as having poor experimental controls. From the necessity of cover stories, protocols and procedures, the differences to the pros and cons of measuring subjectively and objectively and what is required so that both give valid and reliable results are offered as solutions to achieving this goal. Furthermore, the psychological individual differences that need consideration, such as the appreciation of different types of humor, mood, personality variables, for example, trait and state cheerfulness, and gelotophobia- the fear of being laughed at are discussed.