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Full-Text Articles in Physical Sciences and Mathematics
Enhancing Early-Stage Xai Projects Through Designer-Led Visual Ideation Of Ai Concepts, Helen Sheridan, Emma Murphy, Dympna O'Sullivan
Enhancing Early-Stage Xai Projects Through Designer-Led Visual Ideation Of Ai Concepts, Helen Sheridan, Emma Murphy, Dympna O'Sullivan
Academic Posters Collection
The pervasive use of artificial intelligence (AI) in processing users’ data is well documented with the use of AI believed to profoundly change users’ way of life in the near future. However, there still exists a sense of mistrust among users who engage with AI systems some of this stemming from lack of transparency, including users failing to understand what AI is, what it can do and its impact on society. From this, the emerging discipline of explainable artificial intelligence (XAI) has emerged, a method of designing and developing AI where a systems decisions, processes and outputs are explained and …
Unlocking The Black Box: Evaluating Xai Through A Mixed Methods Approach Combining Quantitative Standardised Scales And Qualitative Techniques, Helen Sheridan, Dympna O'Sullivan, Emma Murphy
Unlocking The Black Box: Evaluating Xai Through A Mixed Methods Approach Combining Quantitative Standardised Scales And Qualitative Techniques, Helen Sheridan, Dympna O'Sullivan, Emma Murphy
Academic Posters Collection
In 1950 when Alan Turing first published his groundbreaking paper, computing machinery and intelligence and asked “Can machines think?” a new era of research exploring the intelligence of digital computers and their ability to deceive and/or imitate a human was ignited. From these first explorations of AI to modern day artificial intelligence and machine learning systems many advances, breakthroughs and improved algorithms have been developed usually advancing at an exponential pace. This has resulted in the pervasive use of AI systems in the processing of data. Concerns have been expressed related to biased decisions by AI systems around the processing …
Data: The Good, The Bad And The Ethical, John D. Kelleher, Filipe Cabral Pinto, Luis M. Cortesao
Data: The Good, The Bad And The Ethical, John D. Kelleher, Filipe Cabral Pinto, Luis M. Cortesao
Articles
It is often the case with new technologies that it is very hard to predict their long-term impacts and as a result, although new technology may be beneficial in the short term, it can still cause problems in the longer term. This is what happened with oil by-products in different areas: the use of plastic as a disposable material did not take into account the hundreds of years necessary for its decomposition and its related long-term environmental damage. Data is said to be the new oil. The message to be conveyed is associated with its intrinsic value. But as in …
Mind The Gap: Situated Spatial Language A Case-Study In Connecting Perception And Language, John D. Kelleher
Mind The Gap: Situated Spatial Language A Case-Study In Connecting Perception And Language, John D. Kelleher
Other
This abstract reviews the literature on computational models of spatial semantics and the potential of deep learning models as an useful approach to this challenge.
An Investigation Into The Effects Of Multiple Kernel Combinations On Solutions Spaces In Support Vector Machines, Paul Kelly, Luca Longo
An Investigation Into The Effects Of Multiple Kernel Combinations On Solutions Spaces In Support Vector Machines, Paul Kelly, Luca Longo
Conference papers
The use of Multiple Kernel Learning (MKL) for Support Vector Machines (SVM) in Machine Learning tasks is a growing field of study. MKL kernels expand on traditional base kernels that are used to improve performance on non-linearly separable datasets. Multiple kernels use combinations of those base kernels to develop novel kernel shapes that allow for more diversity in the generated solution spaces. Customising these kernels to the dataset is still mostly a process of trial and error. Guidelines around what combinations to implement are lacking and usually they requires domain specific knowledge and understanding of the data. Through a brute …
Proceedings Of The 18th Irish Conference On Artificial Intelligence And Cognitive Science, Sarah Jane Delany, Michael Madden
Proceedings Of The 18th Irish Conference On Artificial Intelligence And Cognitive Science, Sarah Jane Delany, Michael Madden
Books/Book Chapters
These proceedings contain the papers that were accepted for publication at AICS-2007, the 18th Annual Conference on Artificial Intelligence and Cognitive Science, which was held in the Technological University Dublin; Dublin, Ireland; on the 29th to the 31st August 2007. AICS is the annual conference of the Artificial Intelligence Association of Ireland (AIAI).
A Context-Dependent Model Of Proximity In Physically Situated Environments, John D. Kelleher, Geert-Jan M. Kruijff
A Context-Dependent Model Of Proximity In Physically Situated Environments, John D. Kelleher, Geert-Jan M. Kruijff
Conference papers
The paper presents a computational model for a context-dependent analysis of a physical environment in terms of spatial proximity. The model provides a basis for grounding linguistic analyses of spatial expressions in visual perception. The model uses potential fields to model spatial proximity. It has been implemented, and when combined with a handcrafted grammar, is used to enable a conversational robot to carry out a situated dialogue with a human. The key concept in our approach is defining the region that is proximal to a landmark based on the spatial configuration of other objects in the scene. The model extends …