AIN7301 Applied Artificial Intelligence Assessment 1 Brief 2025 | UoB

AIN7301 Learning Outcomes

Module Learning Outcomes

• LO1: Critically evaluate the capabilities of applied AI, considering ethics and sustainability.

AIN7301 Assessment Brief:

In recent years, the integration of Artificial Intelligence (AI) into various sectors has dramatically transformed industries, driving unparalleled efficiency, fostering innovation, and propelling progress. However, the swift advancement and widespread adoption of AI technologies raise significant concerns regarding their ethical implications and sustainability. The objective of this assignment is to critically assess the capabilities of applied AI within the frameworks of ethics and sustainability.

Students are expected to conduct an in-depth analysis of the ethical implications and sustainability considerations associated with the development and deployment of AI technologies across diverse sectors. This comprehensive evaluation will enable students to understand the broader impact of AI and contribute to the development of responsible and sustainable AI solutions.

Activity Instructions (Essential Content/Deliverables):

You are required to submit a report with emphasis on your understanding of AI, its ethical considerations and its application in a sustainable future. Your report should be based on critical thinking, analysis and reflection aligned with the learning outcomes. The project report should consist of an indicative 3000 words.

A. Understanding Applied AI (20%):

1. Define and discuss the scope and boundaries of applied AI.
2. Identify key applications and industries where applied AI is extensively utilised, such as healthcare, finance, and transportation.

B. Ethical Considerations in Applied AI (40%):

1. Discuss the fundamental principles of AI ethics, including transparency, accountability, fairness, and robustness.
2. Analyse the challenges related to bias and fairness in data-driven AI systems, highlighting potential societal impacts.
3. Evaluate the implications of privacy and data protection in the context of AI technologies, considering legal and ethical perspectives.
4. Examine ethical dilemmas surrounding autonomous decision-making systems, focusing on real-world examples and potential consequences.

C. Sustainability in Applied AI (40%):

1. Explore the social and economic sustainability implications of AI, particularly concerning employment, inequality, and long-term viability.
2. Investigate examples of sustainable AI applications in sectors such as renewable energy, agriculture, and urban planning, showcasing their potential benefits.

GAI Declaration Information:

• Declaration: At the end of the assessment, you should also include a declaration of any software tools, including Generative AI (GAI) applications, that you used in developing and completing the assessment.

Guidelines for the Preparation and Submission of Written Assessments:

a. Written assessments should be word-processed in Arial or Calibri Light font size 12. There should be double-spacing, and each page should be numbered.

b. There should be a title page identifying the programme name, module title, assessment title, student number, your marking tutor and date of submission.

c. You should include a word count at the end of the assessment (excluding references, figures, tables and appendices). Where a word limit is specified, the following penalty systems apply:

• Up to 10% over the specified word length = no penalty
• 10-20% over the specified indicative word length = 5 marks subtracted (but if the assessment would normally gain a pass mark, then the final mark to be no lower than the pass mark for the assessment).
• More than 20% over the indicative word length = if the assessment would normally gain a pass mark or more, then the final mark will be capped at the pass mark for the assessment.

d. All written work should be referenced using the standard University of Bolton referencing style

e. Unless otherwise notified by your Module Tutor, electronic copies of assignments should be saved as Word documents and uploaded into Turnitin via the Moodle class area. If you experience problems in uploading your work, then you must send an electronic copy of your assessment to your Module Tutor via email BEFORE the due date/time.

f. Please note that when you submit your work to Moodle, it will automatically be checked for matches against other electronic information. The individual percentage text matches may be used as evidence in an academic misconduct investigation (see Section 13).

g. Late work will be subject to the penalties:

• Up to 7 calendar days late = 10 marks subtracted, but if the assignment would normally gain a pass mark, then the final mark is no lower than the pass mark for the assignment.
• More than 7 calendar days late = This will be counted as non-submission, and no marks will be recorded.

Late submission of assessments on refer and those that are graded Pass/Fail only. Students may request an extension to the original published deadline date as described below.

h. In the case of exceptional and unforeseen circumstances, an extension of up to 14 days after the assessment deadline may be granted. This must be agreed by your Programme Leader, following a discussion with the Module Tutor. You should complete an Extension Request Form available from your Tutor and attach documentary evidence of your circumstances before the published submission deadline.

Extensions over 14 calendar days should be requested using the Mitigating Circumstances procedure, except for extensions for individual projects and artefacts, which, at the discretion of the Programme Leader, maybe longer than 14 days.
Requests for extensions that take a submission date past the end of the module (normally week 15) must be made using the Mitigating Circumstances procedures.

Some students with registered disabilities will be eligible for revised submission deadlines. Revised submission deadlines do not require the completion of extension request paperwork.

Please note that the failure of data storage systems is not considered to be a valid reason for an extension. Therefore, you must keep multiple copies of your work on different storage devices before submitting it.

Important and helpful information:

• Please refer to the Module Guide for information regarding indicative reading, guidelines for the preparation and submission of assignments, and the module learning outcomes

Specific Assessment Criteria:

This assessment will be graded against the University of Bolton's "General Assessment Criteria for Written Assessments Level HE7". This is provided in the module guide.

Your Report must be in PDF and should be uploaded to Moodle with the filename "XXXXX_NNNN_AIN7301_A1.pdf" where XXXXX stands for your student ID number and NNNN stands for your Name.

Ensure clarity, coherence and critical analysis throughout the assignment as the below-mentioned criteria will also be taken into consideration while grading the submitted work:

• Depth of analysis and critical evaluation: 40%
• Clarity and coherence of arguments: 20%
• Integration of relevant literature and examples: 20%
• Compliance with submission guidelines and academic writing standards: 10%
• Originality and creativity in presenting ideas: 10%

Minimum Secondary Research Source Requirements: 

• Level HE7 - It is expected that the Reference List will contain between fifteen to twenty sources. As a MINIMUM, the Reference List should include four refereed academic journals and five academic books.

 Academic Misconduct

• Academic misconduct may be defined as any attempt by a student to gain an unfair advantage in any assessment.
• This includes plagiarism, collusion, and commissioning (contract cheating) amongst other offences. To avoid these types of academic misconduct, you should ensure that all your work is your own and that sources are attributed using the correct referencing techniques. You can also check originality through Turnitin.

General Assessment Guidelines for Written Assessments Level HE7