Group items tagged

"What happens when speakers try to "dodge" a question they would rather not answer by answering a different question? In 4 studies, we show that listeners can fail to detect dodges when speakers answer similar-but objectively incorrect-questions (the "artful dodge"), a detection failure that goes hand-in-hand with a failure to rate dodgers more negatively. We propose that dodges go undetected because listeners' attention is not usually directed toward a goal of dodge detection (i.e., Is this person answering the question?) but rather toward a goal of social evaluation (i.e., Do I like this person?). "

AI writers like ChatGPT can often produce work that is, at least on first glance, indistinguishable from human writing. With a simple prompt like "write an expository essay on symbolism in Heart of Darkness," ChatGPT can spit out an organized, coherent, five-paragraph essay in seconds. (See results below.) And no two essays will be identical. In some cases, help from an AI may be as acceptable as using a Google search as part of the research process. But in many cases, it will be unacceptable for classroom work. So how do teachers deal with the growing ease with which AIs can complete student homework? Turnitin, which is known for its technology used for plagiarism detection, has posted a technology preview that shows its software automatically detecting work written by an AI writer, even going so far as to show which parts of an essay were written by AI versus human and indicate where AI writing transitions into human writing.

This article discusses how both verbal and body language can indicate deceit in conversation. Although there is no established method of lie detection, many psychologists are working towards creating a more accurate system to do so using a combination of technology that analyzes facial expression, speech patterns, and more.

"A small band of linguists, engineers and computer scientists, among others, are busy training computers to recognize hallmarks of what they call emotional speech - talk that reflects deception, anger, friendliness and even flirtation. ... Algorithms developed by Dr. Hirschberg and colleagues have been able to spot a liar 70 percent of the time in test situations, while people confronted with the same evidence had only 57 percent accuracy ... His lab has also found ways to use vocal cues to spot inebriation, though it hasn't yet had luck in making its computers detect humor - a hard task for the machines, he said."

text analysis tool for detecting deception

This article answers the question of why sarcasm is hard to detect in texting and email conversations. It depends on things like context of the person like the relationship you have with the person you are using sarcasm with. Also, with texting, you can't convey your emotions with facial expressions like you do in face-to-face conversation. Emojis help a little bit with that, but it isn't the same as a face-to-face interaction.

In modern society, there is sarcasm all around us. This article describes sarcasm and how we are so surrounded by it, that it is practically the "primary language". It also discusses how we detect sarcasm and how it is naturally picked up from a young age. Lastly, researchers found that some people have a difficult time detecting sarcasm so some computer scientists have actually developed a sarcasm detection device.

Launches a flash application in which you can watch muscles of the face engage to reveal certain emotions...useful in detection of lying or "fake smiles."

interactive language detective activity for PIE

"An area of the brain called the Visual Word Form Area, or VWFA, is activated whenever it sees something that looks like a word-and is so adept at packaging visual input for the brain's language centers that activation happens within a few tens of milliseconds. ... Instead of being "luminance-defined," words can be "motion-defined," distinguishable from their background not by color or contrast, but by their apparent direction of movement. Against a field of dots moving one way, words made up of dots moving in the other direction will "pop out" to most viewers, even if the word and background dots are the same shade."

Example of the motion-defined words used in the study: http://news.stanford.edu/news/2011/september/videos/973.html

has a link to a link to the original study :)

Parents teach their children to lie. The teaching process is subtle but just as effective as if they had sent their children to formal classes in deception. How many times have parents told their kids "Look me in the eye and then tell me what you did?"

Research demonstrates that liars maintain more deliberate eye contact than do truthful people.

This article by Candice Jalili on Time discusses the body language people tend to have when lying. Everyone can lie, in fact, the average American tells one to two lies each day. It explains how to detect honesty in a conversation, including where their eyes go and how their voice sounds. When someone is lying, they are likely uncomfortable, so they may fidget or have frequent voice cracks. Doctors from the healthcare community provide input on signs people display when lying. The main sections of this article are body cues, facial cues, tone of voice, and content of speech. Body cues include hand movement and itching/fidgeting. Facial cues are eye movement, mouth position, change in complexion, and sweating. The section on tone of voice consists of a high pitched voice and changes in volume while speaking. Lastly, content of speech includes phrases people use, filler words, and slip-ups.

This New York Post article discusses strategies to tell when someone is lying. It provides tips on how to detect a liar, like what details they won't be able to provide. It also discusses a study conducted by the University of Amsterdam. This study describes nine experiments where 1,445 people needed to determine whether handwritten letters, videos, and interviews, both pre-recorded and live, were discussing true or false information. It also discusses the accuracy of polygraphs and how our intuition and attention to detail can help us determine if someone is being truthful or not.

The urge to converse with animals is age-old, long predating the time when smartphones became our best friends. A new app, is the product of a growing interest in enlisting additional intelligences - machine-learning algorithms - to decode animal communication. The app detects and analyzes cat utterances in real-time, assigning each one a broadly defined "intent," such as happy, resting, hunting or "mating call." It then displays a conversational, plain English "translation" of whatever intent it detects. MeowTalk uses the sounds it collects to refine its algorithms and improve its performance, the founders said, and pet owners can provide in-the-moment feedback if the app gets it wrong. In 2021, MeowTalk researchers reported that the software could distinguish among nine intents with 90 percent accuracy overall. But the app was better at identifying some than others, not infrequently confusing "happy" and "pain," according to the results. Dogs could soon have their own day. Zoolingua, a start-up based in Arizona, is hoping to create an A.I.-powered dog translator that will analyze canine vocalizations and body language. Still, even sophisticated algorithms may miss critical real-world context and cues, said Alexandra Horowitz, an expert on dog cognition at Barnard College. For instance, much of canine behavior is driven by scent. "How is that going to be translated, when we don't know the extent of it ourselves?" Dr. Horowitz said in an email.

Teachers worried about students turning in essays written by a popular artificial intelligence chatbot now have a new tool of their own. Edward Tian, a 22-year-old senior at Princeton University, has built an app to detect whether text is written by ChatGPT, the viral chatbot that's sparked fears over its potential for unethical uses in academia. Tian, a computer science major who is minoring in journalism, spent part of his winter break creating GPTZero, which he said can "quickly and efficiently" decipher whether a human or ChatGPT authored an essay.

This article writes about the complexities of animal communication and how elephants are able to use low frequency sounds to stay in touch amongst each other. Generative artificial intelligence is able to help humans generate an algorithm that is capable of detecting animal calls, grumbles, grunts, squeaks etc and translate it into a language that humans are comfortable interpreting.

This Scientific American blog article provides a handy run-down of research findings re: music's effect on the brain, including 1. Musicians are better able to process foreign languages because of their ability to hear differences in pitch, and have incredible abilities to detect speech in noise. Even those w/ a few years of music training showed more robust neural processing of sounds. Music "tones auditory fitness", critical for perceiving speech and distinguishing, recognizing and processing conversation in noisy environments. 2. Musical training and education may confer linguistic, mathematical, and spatial benefits, and promote social development/"team player" capacities.

This article gives an overview of sarcasm and how hard/easy it is to detect it.