Presentation (individual)

2 - Oral assessment and presentation - 20

Report

1 - Written assignment (including essay) - 80

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- Science and technology studies
- Critical data studies
- Software studies
- Feminist data studies
- Critical theories on AI
- Digital data production, storage and distribution

Feedback is provided in a number of ways throughout your module. This includes feedback you receive during teaching from both peers and lecturers and that provided for formative assessment. Following an assessment, you will be given your marks and feedback in line with the assessment regulations and policy. More information on the timing and type of feedback that will be provided for each assessment will be available from the module leader. <a href='https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations'>https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations</a>

This module will support the development of all the graduate attributes. Your module leader will provide you with information about how your learning, teaching and assessment activities support your development of these attributes. The graduate attributes are: - Always learning - Engaged in the world - Technical and digital - Connected Professional - Creating Impact

In-Person - 

Self-directed - 

Big data from the South (s): Beyond data universalism 319-335.

Television & New Media

Peter Lang International Academic Publishers.

Media Distortions: Understanding the Power Behind Spam, Noise, and Other Deviant Media

Bodies of Information: Intersectional Feminism and the Digital Humanities. 

Big data, big questions| the big data divide, 8, 17.

International Journal of Communication

What is data justice? The case for connecting digital rights and freedoms globally

Big Data & Society

Data feminism

Indigenous data sovereignty: Toward an agenda

Data politics

Big data & society

The ambivalent internet: Mischief, oddity, and antagonism online

Weaving the dark web: legitimacy on freenet, Tor, and I2P

Indigenous data, indigenous methodologies and indigenous data sovereignty. 233-243.

International Journal of Social Research Methodology

Queer Data: Using Gender, Sex and Sexuality Data for Action

 Uncertain Archives: Critical Keywords for Big Data

Data citizens: How to reinvent rights (pp. 248-266). 

Data Politics 

Key academic journals:

Big Data & Society
Information, Communication & Society 
New Media & Society
International Journal of Communication 
Journal of Information Technology

SG3085 - AI, Technology and Society

SG3085-PRD1-PER-ALV1

You will be taught through a combination of in-person sessions (i.e. face to face seminars on campus) and online guided activities to complete in your own time, in preparation for your live sessions. The guided activities may include viewing recorded lectures or other online resources, reading materials, completing exercises and chatting on Moodle forums. In addition to these teaching delivery approaches, you will undertake your own independent study, which may involve wider reading, independent research, skills practice and preparation for assessment. Please see this module’s Moodle page and/or handbook for further information. It is mandatory to engage with all elements of your module content, right from the start of term. If you do not do so, you will find it very difficult to pass your module assessments.

AI, Technology and Society

Examine different data processes, cultures and practices, in terms of the four main processes discussed in the module: production, storage, distribution and design.

Knowledge

Show respect and tolerance for other people in the module.

Values and attitudes

Develop original insights into a wide variety of different contexts and textual products, such as policy documents, speeches and newspaper and journal articles.

Skills

Evaluate key debates, theories and research findings around digital data and its various strands of inquiry.

Identify concepts and principles of data politics while realising the limits and ethics of their knowledge.

Correctly reference academic work, be mindful of reference politics when it comes to gender and race.

Critically assess this knowledge in an original manner linking it to wider theories of how the digital data function on the national, regional and global scales.

Demonstrate consideration for the rules and regulations of the University in your class conduct and your coursework.

Act autonomously in planning and implementing tasks requiring synthesis of the knowledge they acquired.

Assemble ideas and concepts in your coursework and class contributions so as to develop a robust understanding of research findings and evidence, and construct grounded and coherent arguments for rival explanations.

Respect your peers, value their work and be conscious of the need to avoid plagiarism.

Critically analyse major developments and debates in various data theories and of the key concepts and paradigms of the discipline.

Demonstrate consideration for the ethical and political implications of media, communication and multi-cultural perspectives in your class conduct and your coursework.