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Aims/Description: This foundational module underpins our approach to teaching future data scientists. It develops students' essential skills and awareness of the ethics and practicalities of real-world data science contexts. These contexts will include big business, academic research, cause-related charities as well as policy and public sectors. This module addresses two key questions: firstly, 'What makes data science a science?', through material on the origins and traditions of data uses; and secondly, 'How does thinking about data science as a social and information science help us imagine and realise more ethical and sustainable futures?' Core content includes: - the importance of useful data science, with critical understanding of how data science is used - in different contexts - for good and bad; - foundational professional skills and literacies (data, information, ethical and academic); - how data work in different contexts: in the workplace, personal data and different geographies, domains and industries; - how contextual data can improve understanding as well as ways that data are acquired, deployed, monitored and evaluated; - different origins and traditions of data science including its history, perspectives and disciplines; - the impact of data science and ethical innovations including critical data science, fairness, accountability, transparency, ethics and social justice (FATES), ethical data and Artificial Intelligence (AI), data and AI futures, data politics and activism, and using data for good causes; - cross-cutting themes such as sustainability (and the Sustainable Development Goals [SDGs]), decolonisation, and intersectionality; - the benefits, challenges and threats of AI and data-driven approaches to decision-making, as well as human computer interaction across multi-cultural contexts; - the core legislation, standards and codes of conduct related to data.
Information on the department responsible for this unit (Information School):
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