The Cyprus Center for Algorithmic Transparency (CyCAT) and the Open University of Cyprus (OUC), as the coordinating organization of the Horizon 2020 Widespread Twinning Project “CyCAT,” are pleased to announce that the CyCAT Closing Event took place on the 1st of December at the Hilton Nicosia with great success.
The Closing Event was held under the auspices of the Deputy Ministry of Research, Innovation and Digital Policy of the Republic of Cyprus.
Prof. Stavros Stavrou, (Dean of the School of Pure and Applied Sciences, OUC) addressed the event with an opening greeting. Dr. Jahna Otterbacher, the Coordinator of CyCAT, presented the outcomes of the project, followed by... Read More
Dr. Jahna Otterbacher, the Coordinator of Cyprus Center for Algorithmic Transparency (CyCAT) appeared on the TV show Enimerosi Tora, Omega TV and talked about the Cyprus Center for Algorithmic Transparency’s work. She discussed the Artificial Intelligent applications that we use in our everyday life.
Dr. Jahna Otterbacher, the Coordinator of Cyprus Center for Algorithmic Transparency (CyCAT) appeared on the TV show Mesimeri kai Kati, Sigma TV and talked about the Cyprus Center for Algorithmic Transparency’s work. She discussed how search engines personalize the results we see according to the data they collect for each user.
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
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
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
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
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
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
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
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