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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Crisis Communication And Executive Leadership: Ethical Shortcomings In Government, Daniel Davidoff
Crisis Communication And Executive Leadership: Ethical Shortcomings In Government, Daniel Davidoff
School of Professional Studies
This research thesis project is an analysis of how and why governments fail in their attempts at crisis communication. The hypotheses tested are: there exists a negative correlation between unethical leadership and successful crisis communication practices. And governments are more likely to experience these failures due to ethical disconnects in modern politics. Research includes a review of relevant academic literature regarding crisis communication theory, as well as the ethical framework that can be applied to that theory. Cases considered are Hurricane Katrina, the choking death of Eric Garner, and the COVID-19 global pandemic. The research project concludes with a recommendation …
Expectations Of Artificial Intelligence And The Performativity Of Ethics: Implications For Communication Governance, Aphra Kerr, Marguerite Barry, John D. Kelleher
Expectations Of Artificial Intelligence And The Performativity Of Ethics: Implications For Communication Governance, Aphra Kerr, Marguerite Barry, John D. Kelleher
Articles
This article draws on the sociology of expectations to examine the construction of expectations of ‘ethical AI’ and considers the implications of these expectations for communication governance. We first analyse a range of public documents to identify the key actors, mechanisms and issues which structure societal expectations around artificial intelligence (AI) and an emerging discourse on ethics. We then explore expectations of AI and ethics through a survey of members of the public. Finally, we discuss the implications of our findings for the role of AI in communication gover- nance. We find that, despite societal expectations that we can design …
Implementation Considerations For Mitigating Bias In Supervised Machine Learning, Bardia Bijani Aval
Implementation Considerations For Mitigating Bias In Supervised Machine Learning, Bardia Bijani Aval
CSB and SJU Distinguished Thesis
Machine Learning (ML) is an important component of computer science and a mainstream way of making sense of large amounts of data. Although the technology is establishing new possibilities in different fields, there are also problems to consider, one of which is bias. Due to the inductive reasoning of ML algorithms in creating mathematical models, the predictions and trends found by the models will never necessarily be true – just more or less probable. Knowing this, it is unreasonable for us to expect the applied deductive reasoning of these models to ever be fully unbiased. Therefore, it is important that …