Science Daily November 1, 2019 Researchers at Dartmouth College present a detection model that captures a speaker’s intent by measuring his patterns of reasoning. Through empirical studies, these intent-driven reasoning patterns can identify as well as explain deceptive communications. They developed a unique approach and resulting algorithm that can tell deception apart from all benign communications by retrieving the universal features of deceptive reasoning. However, the framework is currently limited by the amount of data needed to measure a speaker’s deviation from their past arguments. The model which could be developed to extract opinion from “fake news,” among other uses, […]
Tag Archives: Biometrics
Emotion-detection applications built on outdated science, report warns
Science Daily July 18, 2019 The general public and some scientists believe that there are unique facial expressions that reliably indicate six emotion categories: anger, sadness, happiness, disgust, fear, and surprise. But in reviewing more than 1,000 published findings about facial movements and emotions, a team of researchers in the US (Northeastern University, Mass General Hospital, Caltech, the Ohio State University, University of Wisconsin) found that typical study designs don’t capture the real-life differences in the way people convey and interpret emotions on faces. They propose a new model for studying emotion-related responses in all their complexity and variations. This […]
Emotion-reading tech fails the racial bias test
Phys.org January 3, 2019 Researchers at Wake Forest University compared the emotional analysis from two different facial recognition services, Face and Microsoft’s Face API. Both services interpreted black players as having more negative emotions than white players. According to the researchers there are two different mechanisms. Face consistently interprets black players as angrier than white players, even controlling for their degree of smiling. Microsoft registers contempt instead of anger, and it interprets black players as more contemptuous when their facial expressions are ambiguous. As the players’ smile widens, the disparity disappears. The finding has implications for individuals, organizations, and society, […]
Artificial intelligence can predict your personality … simply by tracking your eyes
Eurekalert July 27, 2018 An international team of researchers (Germany, Australia) used state-of-the-art machine-learning algorithms to demonstrate a link between people’s eye movements and their personality. It reveals whether they are sociable, conscientious or curious, with the algorithm software reliably recognising four of the Big Five personality traits: neuroticism, extroversion, agreeableness, and conscientiousness. The study provides new links between previously under-investigated eye movements and personality traits and delivers important insights for emerging fields of social signal processing and social robotics… read more. Open Access TECHNICAL ARTICLE
IBM to release world’s largest facial analytics dataset
Phys.org June 27, 2018 One of the biggest issues causing bias in facial analysis is the lack of diverse data to train systems on. IBM is releasing a facial attribute and identity training dataset of over 1 million images to improve facial analysis. It is annotated with attributes and identity, leveraging geo-tags from Flickr images to balance data from multiple countries and active learning tools to reduce sample selection bias. Unlike the current datasets the IBM dataset has a single capability to match attributes (hair color, facial hair, etc.) and identify multiple images of the same person. A dataset which […]