Artificial Intelligence (AI) is increasingly featured in all areas of working with digital information, whether it is creation, interpretation, communication, and/or use. This places it at the centre of the social and cultural impact of the digital revolution. This course goes beyond philosophy and ethics to help you gain the practical skills valuable for a deeper understanding of the basic mechanics of AI and their applications. The course intends to empower a broader audience, with a focus in the arts and humanities, to engage in a deeper discussion about current debates regarding AI, across technical, social and cultural dimensions. It prepares students with the foundation to undertake the course AI for the Arts and Humanities (B) where they will explore how AI can augment human creative processes.

This will be a blended course. 1x1hr per week lecture and 1x1hr per week computer lab over 10 weeks as scheduled on MyCampus. Lecture will be delivered online either live and/or pre-recorded. Supervised computer labs will be in-person by default.

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The standard assessments for this course are: 

■ The portfolio (2500 words) will comprise presented code contextualised with written text, image, and/or sound. - 50% 

■ The report (1500 words) will consist of a review of a selected area/aspects of AI. - 50% 

If required, for instance where a disability prevents a student from undertaking a specific method of assessment, the following alternatives are available: 

■ There are no alternatives to the assessments, but flexible deadlines can be offered as reasonable adjustment (Students should follow the usual process for extensions). 

Further reasonable adjustments may be provided where necessary. Students are encouraged to consult with the course convenor.  

The course aims to:

■ Engage students with a range of current developments in AI and associated applications.

■ Enhance students' practical skills in writing and presenting code (e.g. for handling data, experimenting with machine learning, and rendering content) to engage with the broader coding community in the arts and humanities.

■ Help students critically examine social concerns (e.g. ethical, archival, philosophical) specific to AI-applications.

By the end of this course student will be able to:

■ Formulate a overview of key developments in AI history and their disciplinary significance.

■ Distinguish the general principles of machine learning and its relationship to data.

■ Contrast a selection of AI models relevant to current state-of-the-art approaches (e.g. different types of neural networks).

■ Illustrate skills relevant to the steps of machine learning in a portfolio of presented code (computer code accompanied by written text, comments and relevant images and/or audio to engage a broader audience).

■ Review critically the social implications of AI in a focused application area.