Analyzing Demographic Bias in Artificially Generated Facial Pictures<\/a>. ACM CHI Conference on Human Factors in Computing Systems (CHI’20) (Extended Abstract), Honolulu, HI, USA. 25\u201330 April, 1-8.<\/p>\n","protected":false},"excerpt":{"rendered":"Artificial generation of facial images is increasingly popular, with machine learning achieving photo-realistic results. Yet, there is a concern that the generated images might not fairly represent all demographic groups. We use a state-of-the-art method to generate 10,000 facial images and find that the generated images are skewed towards young people, especially white women. We … Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":["post-42","post","type-post","status-publish","format-standard","hentry","category-user-study"],"jetpack_featured_media_url":"","jetpack-related-posts":[{"id":12,"url":"https:\/\/metric.qcri.org\/blog\/2022\/07\/28\/using-artificially-generated-pictures-in-customer-facing-systems-an-evaluation-study-with-data-driven-personas\/","url_meta":{"origin":42,"position":0},"title":"Using Artificially Generated Pictures in Customer-facing Systems: An Evaluation Study with Data-Driven Personas","date":"July 28, 2022","format":false,"excerpt":"We conduct two studies to evaluate the suitability of artificially generated facial pictures for use in a customer-facing system using data-driven personas. STUDY 1 investigates the quality of a sample of 1,000 artificially generated facial pictures. Obtaining 6,812 crowd judgments, we find that 90% of the images are rated medium\u2026","rel":"","context":"In "user study"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":264,"url":"https:\/\/metric.qcri.org\/blog\/2024\/06\/27\/picturing-the-fictitious-person-user-perceptions-of-ai-generated-personas\/","url_meta":{"origin":42,"position":1},"title":"Picturing the Fictitious Person: User Perceptions of AI-generated Personas","date":"June 27, 2024","format":false,"excerpt":"Artificial intelligence has increasingly been leveraged to create personas in recent years, with tools like DALL-E and Midjourney generating detailed textual and visual representations. However, a recent study, Picturing the Fictitious Person: An Exploratory Study on the Effect of Images on User Perceptions of AI-generated Personas, has provided intriguing insights\u2026","rel":"","context":"In \"user experience\"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/metric.qcri.org\/blog\/wp-content\/uploads\/2024\/06\/openart-image_gEhS-NrC_1719486122347_raw-e1719487751729.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":60,"url":"https:\/\/metric.qcri.org\/blog\/2022\/07\/28\/findings-of-a-user-study-of-automatically-generated-personas\/","url_meta":{"origin":42,"position":2},"title":"Findings of a User Study of Automatically Generated Personas","date":"July 28, 2022","format":false,"excerpt":"We report findings and implications from a seminaturalistic user study of a system for Automatic Persona Generation (APG) using large-scale audience data of an organization\u2019s social media channels conducted at the workplace of a major international corporation. Thirteen participants from a range of positions within the company engaged with the\u2026","rel":"","context":"In "user study"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":66,"url":"https:\/\/metric.qcri.org\/blog\/2022\/07\/28\/generating-cultural-personas-from-social-data-a-perspective-of-middle-eastern-users\/","url_meta":{"origin":42,"position":3},"title":"Generating Cultural Personas From Social Data: A Perspective of Middle Eastern Users","date":"July 28, 2022","format":false,"excerpt":"We conduct a mixed-method study to better understand the content consumption patterns of Middle Eastern social media users and to explore new ways to present online data by using automatic persona generation. First, we analyze millions of content interactions on YouTube to dynamically generate personas describing behavioral patterns of different\u2026","rel":"","context":"In "user study"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":1,"url":"https:\/\/metric.qcri.org\/blog\/2022\/07\/28\/hello-world\/","url_meta":{"origin":42,"position":4},"title":"Can Unhappy Pictures Enhance the Effect of Personas? A User Experiment","date":"July 28, 2022","format":false,"excerpt":"There has been little research into whether a persona\u2019s picture should portray a happy or unhappy individual. We report a user experiment with 235 participants, testing the effects of happy and unhappy image styles on user perceptions, engagement, and personality traits attributed to personas using a mixed-methods analysis. Results indicate\u2026","rel":"","context":"In "user study"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":54,"url":"https:\/\/metric.qcri.org\/blog\/2022\/07\/28\/is-more-better-impact-of-multiple-photos-on-perception-of-persona-profiles\/","url_meta":{"origin":42,"position":5},"title":"Is More Better?: Impact of Multiple Photos on Perception of Persona Profiles","date":"July 28, 2022","format":false,"excerpt":"In this research, we investigate if and how more photos than a single headshot can heighten the level of information provided by persona profiles. 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