Empirical Analysis of Ethical Principles Applied to Different AI Uses Cases

Rivero, Alfonso José López; Beato, M. Encarnación; Martínez, César Muñoz; Vázquez, Pedro Gonzalo Cortiñas

doi:10.9781/ijimai.2022.11.006

Cited by 2 publications

(2 citation statements)

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“…Future work would benefit from the examination of how new technology can impact user work and how job roles may shift and change when technologies are introduced. In the general population there are hesitations around the potential harm that Artificial Intelligence tools could have on human work [54]. Having a better understanding of information passing in the current intelligence ecosystem, can help serve as a marker to contrast later work, and could consider techniques and factors that can ameliorate concerns regarding future technology use cases.…”

Section: Discussionmentioning

confidence: 99%

Preliminary Perspectives on Information Passing in the Intelligence Community

Block,

Bookner,

Chu

et al. 2023

Analytics

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Analyst sensemaking research typically focuses on individual or small groups conducting intelligence tasks. This has helped understand information retrieval tasks and how people communicate information. As a part of the grand challenge of the Summer Conference on Applied Data Science (SCADS) to build a system that can generate tailored daily reports (TLDR) for intelligence analysts, we conducted a qualitative interview study with analysts to increase understanding of information passing in the intelligence community. While our results are preliminary, we expect that this work will contribute to a better understanding of the information ecosystem of the intelligence community, how institutional dynamics affect information passing, and what implications this has for a TLDR system. This work describes our involvement in and work completed during SCADS. Although preliminary, we identify that information passing is both a formal and informal process and often follows professional networks due especially to the small population and specialization of work. We call attention to the need for future analysis of information ecosystems to better support tailored information retrieval features.

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Section: Discussionmentioning

confidence: 99%

Preliminary Perspectives on Information Passing in the Intelligence Community

Block,

Bookner,

Chu

et al. 2023

Analytics

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“…In learning analytics, the main ethical issues are related to data ownership and student privacy [46], with the protection of privacy being one of the fundamental values and rights on which ethical artificial intelligence is based [47]. In this study, all human participants' data were fully anonymized before we accessed them.…”

Section: Research Ethicsmentioning

confidence: 99%

Clustering of LMS Use Strategies with Autoencoders

et al. 2023

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Learning Management Systems provide teachers with many functionalities to offer materials to students, interact with them and manage their courses. Recognizing teachers’ instructing styles from their course designs would allow recommendations and best practices to be made. We propose a method that determines teaching style in an unsupervised way from the course structure and use patterns. We define a course classification approach based on deep learning and clustering. We first use an autoencoder to reduce the dimensionality of the input data, while extracting the most important characteristics; thus, we obtain a latent representation of the courses. We then apply clustering techniques to the latent data to group courses based on their use patterns. The results show that this technique improves the clustering performance while avoiding the manual data pre-processing work. Furthermore, the obtained model defines seven course typologies that are clearly related to different use patterns of Learning Management Systems.

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Empirical Analysis of Ethical Principles Applied to Different AI Uses Cases

Cited by 2 publications

References 0 publications

Preliminary Perspectives on Information Passing in the Intelligence Community

Preliminary Perspectives on Information Passing in the Intelligence Community

Clustering of LMS Use Strategies with Autoencoders

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