Course Catalogue

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The world is becoming augmented by artificial intelligence (AI). Generative AI (GenAI) is now a part of our everyday lives. When prompted, large language models and AI image generators can rapidly generate specific responses and images, respectively. This course will introduce students to the use of LLMs and AI image generators in scientific communications and how to use these technologies appropriately, responsibly and ethically.

This course will consist of lectures and workshops delivered over 5 weeks in semester 1.

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1. Write an editorial on an LLM and AI image generator prompt and write a critical evaluation of the accompanying response and an AI generated image (75%) (2250-2500 words) (ILO 1-4)

2. Group debate on a relevant topic (25%). An element of the debate mark (10% of 25%) will be subject to staff assessment based on individual contribution. (ILO 2-4)  

Reassessments are normally available for all courses, except those which contribute to the Honours classification. Where, exceptionally, reassessment on Honours courses is required to satisfy professional/accreditation requirements, only the overall course grade achieved at the first attempt will contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items such as the group debate, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

Group element is not re-assessable.

This course aims to provide students with skills and knowledge to effectively use GenAI for generating scientific information and imagery. Students will learn how to effectively engineer prompts to generate responses and images and consider the scientific integrity and reliability of responses.

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

1. Critically evaluate the use of effective prompt engineering for generating scientific responses and images by LLMs and AI image generators, respectively, for intended audiences.

2. Critically appraise the scientific integrity and reliability of responses generated by LLMs and how this relates to published, peer reviewed scientific literature.

3. Critically assess the presence of bias in LLM responses and AI generated images and why these biases occur.

4. Critically evaluate the necessity for regulation of the use of GenAI technology in scientific research.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.