Zobrazeno 1 - 10
of 4 376
pro vyhledávání: '"A. Danks"'
In many causal learning problems, variables of interest are often not all measured over the same observations, but are instead distributed across multiple datasets with overlapping variables. Tillman et al. (2008) presented the first algorithm for en
Externí odkaz:
http://arxiv.org/abs/2411.04243
Autor:
Swaminathan, Nandhini, Danks, David
As quantum machine learning (QML) emerges as a promising field at the intersection of quantum computing and artificial intelligence, it becomes crucial to address the biases and challenges that arise from the unique nature of quantum systems. This re
Externí odkaz:
http://arxiv.org/abs/2409.19011
Sociotechnical requirements shape the governance of artificially intelligent (AI) systems. In an era where embodied AI technologies are rapidly reshaping various facets of contemporary society, their inherent dynamic adaptability presents a unique bl
Externí odkaz:
http://arxiv.org/abs/2409.00015
Recent years have seen increased awareness of the potential significant impacts of computing technologies, both positive and negative. This whitepaper explores how to address possible harmful consequences of computing technologies that might be diffi
Externí odkaz:
http://arxiv.org/abs/2408.06431
Autor:
Swaminathan, Nandhini, Danks, David
One strategy in response to pluralistic values in a user population is to personalize an AI system: if the AI can adapt to the specific values of each individual, then we can potentially avoid many of the challenges of pluralism. Unfortunately, this
Externí odkaz:
http://arxiv.org/abs/2404.19256
Autor:
Swaminathan, Nandhini, Danks, David
This study offers an in-depth analysis of the application and implications of the National Institute of Standards and Technology's AI Risk Management Framework (NIST AI RMF) within the domain of surveillance technologies, particularly facial recognit
Externí odkaz:
http://arxiv.org/abs/2403.15646
This report summarizes the discussions and conclusions of a 2-day multidisciplinary workshop that brought together researchers and practitioners in healthcare, computer science, and social sciences to explore what lessons were learned and what action
Externí odkaz:
http://arxiv.org/abs/2403.00096
Autor:
Trusilo, Daniel, Danks, David
This paper presents a theoretical analysis and practical approach to the moral responsibilities when developing AI systems for non-military applications that may nonetheless be used for conflict applications. We argue that AI represents a form of cro
Externí odkaz:
http://arxiv.org/abs/2402.01762
Autor:
Chien, Jennifer, Danks, David
Algorithmic harms are commonly categorized as either allocative or representational. This study specifically addresses the latter, focusing on an examination of current definitions of representational harms to discern what is included and what is not
Externí odkaz:
http://arxiv.org/abs/2402.01705
Publikováno v:
Journal of Business & Industrial Marketing, 2024, Vol. 39, Issue 12, pp. 2673-2683.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JBIM-02-2024-0076
