MBP7006M Risk & Issue Management Assignment Brief 2024-25 | YSJU

MBP7006M Assignment Description

Artificial Intelligence (AI) systems are increasingly prevalent across diverse sectors, offering potential benefits such as automation, predictive analytics, and enhanced decision-making. However, the integration of AI also introduces unique risks and issues, ranging from data governance concerns and potential biases to regulatory and ethical challenges.

AI-driven innovations could add trillions of dollars to the global economy, yet many organisations remain ill-prepared for the fast-changing landscape of AI risks. 

These risks are not purely technical; they often have profound social, ethical, and organisational dimensions. As adoption grows, project teams must account for the multifaceted risks posed by AI—both current and future—by employing robust risk and issue management practices.

MBP7006M Brief

You are required to evaluate the impact of AI-related risks and issues in a project scenario. You may choose from one of the projects below:

1. IBM Watson for Oncology
2. Amazon’s “recommendation” algorithm
3. Clearview AI. You must evaluate the impact of rising AI technologies. 

You should take into account the immediate issue management requirements as well as undertake a risk analysis going forward. This will involve screening the project environment for potential AI-related risk categories and conducting a high-level assessment of these risks.

As part of this, you should identify the top five specific risks that you feel have the potential to cause the greatest damage and critically analyse the most appropriate response strategies to address them. Consider any organisational tolerances and whether additional measures may be required.

Finally, you should critically appraise the existing risk management process and consider whether it is sufficiently robust given the rapidly evolving nature of AI. Evaluate how effectively issues and risks are identified, assessed, and managed, and recommend changes to ensure that the project remains aligned with both current best practices and potential future challenges in AI development and deployment.

MBP7006M Learning Outcomes

You must successfully achieve the following Programme-level Learning Outcomes to pass this assessment:

• Critically analyse the risk management process, including assessment of probability & impact exposure, the formation of an appropriate risk response strategy, and the use of contingency.
• Develop a critical awareness of the potential sources of risk, the influence of environmental factors and the role of individual bias on the effective management and alignment with organisational tolerances.
• Critically evaluate the issue management process to minimise the negative impact of issues on the project objectives through identification, analysis and effective resolution.

MBP7006M Advice and Guidance

Your risk evaluation should include identification, assessment and response strategies. You should provide clarification of the risk matrix used to analyse the risks to support your risk assessment.

Your work must be underpinned by reference to academic theory, and whilst the use of media reporting may be permitted, you should be circumspect when selecting sources.

• Proposed structure (for guidance only):
• Executive Summary (Not part of the word count)
• Table of Contents (Not part of the word count)
• Introduction and Context
• Issue Management
• Risk Evaluation
• Recommendations
• References
• Appendices

How Is This Assessment Marked?

Your work will be marked according to the assessment instructions provided within this document and the selected ‘Programme-level Learning Outcomes’ (PLOs) (see above). 

Furthermore, this assessment is marked based on a rubric devised from the GAD (see below). Where a rubric has been used in place of the GAD, this is to further specify and enhance your understanding of the expectations of this assessment. 

Please note that you must meet the required baseline standards (50 – 59%), which will include the PLOs and minimum expectations of the assessment. Further still, you must ensure you meet the requirements of each grade boundary to progress to the next, i.e. you should demonstrate your learning through the standards of a Pass, Merit, and Distinction to achieve a Distinction (70 – 100%). These standards are designed to scaffold and build your learning to achieve your fullest potential in each criterion being assessed.

Each criterion will be allocated a weighting for this assessment. This is to indicate our expectations of where and how you should focus your efforts, and how marks will be awarded.

Assessment Marking Criteria

Pass Grade Bands (100 – 50) (Programme Learning Outcomes must be met)
Fail Grade Bands (49 – 0) (Programme Learning Outcomes are not met)