News


Latest developments at CyCAT, including research findings and administrative changes.
Sometimes we also include external world news in our topic.



CyCAT offers a free online course entitled “Artificial Intelligence in Everyday Life”


The CyCAT research project through the Open University of Cyprus aspires to make knowledge about Artificial Intelligence accessible to all. So it takes the initiative to offer a free online course that teaches basic knowledge about Artificial Intelligence (A.I.). The course is addressed to the general public and specifically to those who are interested in learning and understanding the basics of A.I. and its applications/systems that they use daily. The course aims to acquire basic knowledge and to understand basic applications and systems of A.I. that we use - even unconsciously - every day. The course is offered in Greek and is consisted of 8 synchronous online lectures. The course... Read More



“I agree with the decision, but they didn’t deserve this”: Future Developers’ Perception of Fairness – FAccT 2021- Kasinidou, Kleanthous, Barlas, Otterbacher


While professionals are increasingly relying on algorithmic systems for making a decision, on some occasions, algorithmic decisions may be perceived as biased or not just. Prior work has looked into the perception of algorithmic decision-making from the user’s point of view. In this work, we investigate how students in fields adjacent to algorithm development perceive algorithmic decisionmaking. Participants (N=99) were asked to rate their agreement with statements regarding six constructs that are related to facets of fairness and justice in algorithmic decision-making in three separate scenarios. Two of the three scenarios were independent of each other, while the... Read More


It’s About Time: A View of Crowdsourced Data Before and During the Pandemic – CHI 2021 – Christoforou, Barlas, Otterbacher


Data attained through crowdsourcing have an essential role in the development of computer vision algorithms. Crowdsourced data might include reporting biases, since crowdworkers usually describe what is "worth saying" in addition to images’ content. We explore how the unprecedented events of 2020, including the unrest surrounding racial discrimination, and the COVID-19 pandemic, might be reflected in responses to an open-ended annotation task on people images, originally executed in 2018 and replicated in 2020. Analyzing themes of Identity and Health conveyed in workers' tags, we find evidence that supports the potential for temporal sensitivity in crowdsourced data. The... Read More


OpenTag Demo Presentation – HCOMP 2020 – Kyriakou, Barlas, Kleanthous, Otterbacher


Image Tagging Algorithms (ITAs) are extensively used in our information ecosystem, from facilitating the retrieval of images in social platforms to learning about users and their preferences. However, audits performed on ITAs have demonstrated that their behaviors often exhibit social biases, especially when analyzing images depicting people. We present OpenTag, a platform that fuses the auditing process with a crowdsourcing approach. Users can upload an image, which is then analyzed by various ITAs, resulting in multiple sets of descriptive tags. With OpenTag, the user can observe and compare the output of multiple ITAs simultaneously, while researchers can study the manner in which... Read More


“To See is to Stereotype” – CSCW 2020 – Barlas, Kyriakou, Guest, Kleanthous, Otterbacher


Machine-learned computer vision algorithms for tagging images are increasingly used by developers and researchers, having become popularized as easy-to-use “cognitive services.” Yet these tools struggle with gender recognition, particularly when processing images of women, people of color and non-binary individuals.Socio-technical researchers have cited data bias as a key problem; training datasets often over-representimages of people and contexts that convey social stereotypes. The social psychology literature explains that people learn social stereotypes, in part, by observing others in particular roles and contexts, and can inadvertently learn to associate gender with... Read More


DESCANT project Kick off meeting


The kick off meeting of the DESCANT project took place last week. DESCANT shall contribute to the smart growth of R&D in Cyprus, as its objectives are in line with the Smart Specialization Strategy, which designates ICT as a horizontal priority, as well as Cyprus’ Digital Strategy Goals and specifically, Digital Entrepreneurship. Jahna Otterbacher is the coordinator of this project. Also, she is the PI of the Transparency in Algorithms Group (TAG), within the Research Centre on Interactive Media, Smart Systems and Emerging Technologies (RISE - HO), and Assistant Professor at the Open University of Cyprus (OUC – PA1), where she leads the Cyprus Center for Algorithmic Transparency... Read More


HCOMP 2019 The seventh AAAI Conference on Human Computation and Crowdsourcing


Dr. Jahna Otterbacher is invited to present the paper "How Do We Talk About Other People? Group (Un)Fairness in Natural Language Image Descriptions" at HCOMP 2019 The seventh AAAI Conference on Human Computation and Crowdsourcing that will take place on 28-30 of October. The abstract of the paper: Crowdsourcing plays a key role in developing algorithms for image recognition or captioning. Major datasets, such as MS COCO or Flickr30K, have been built by eliciting natural language descriptions of images from workers. Yet such elicitation tasks are susceptible to human biases, including stereotyping people depicted in images. Given the growing concerns surrounding discrimination in... Read More


Fairness in Algorithmic and Crowd-Generated Descriptions of People Images


Dr. Jahna Otterbacher is invited to give a keynote talk at FAT/MM: Fairness Accountability and Transparency in Multimedia on 25th October. The abstract for the talk: Image analysis algorithms have become indispensable in the modern information ecosystem. Beyond their early use in restricted domains (e.g., military, medical), they are now widely used in consumer applications and social media. With the rise of the Algorithm Economy, image analysis algorithms are increasingly being commercialized as Cognitive Services. This practice is proving to be a boon to the development of applications where user modeling, personalization, and adaptation are required. From e-stores,... Read More


Dr. Styliani Kleanthous, CyCAT gave a talk at the Information School, University of Sheffield


The abstract for the talk: Image analysis algorithms have become indispensable in the modern information ecosystem. Beyond their early use in restricted domains (e.g., military, medical), they are now widely used in consumer applications and social media enabling functionality that users take for granted. Recently image analysis algorithms, have become widely available as Cognitive Services. This practice is proving to be a boon to the development of applications where user modeling, personalization, and adaptation are required. But while tagging APIs offer developers an inexpensive and convenient means to add functionality to their creations, most are opaque and proprietary and there are... Read More


Dr. Styliani Kleanthous gave a talk at the BHCC 2019 First symposium on Biases in Human Computation and Crowdsourcing


Dr. Styliani Kleanthous from Cyprus Center for algorithmic transparency presented, Fairness in Algorithmic and Crowd-Generated Descriptions of People Images at the First symposium on Biases in Human Computation and Crowdsourcing. The abstract for the talk: Crowdsourcing plays a key role in developing algorithms for image recognition or captioning. Image analysis algorithms have become indispensable in the modern information ecosystem. Beyond their early use in restricted domains (e.g., military, medical), they are now widely used in consumer applications and social media, with the consumers taking the output of these applications for granted.With the rise of the “Algorithm... Read More