SSCC Group In-course(AI in Logistics)

Asia Pacific University of Technology and Innovation

System Software and Computing Concepts (CT123-3-1-SSCC)

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Total Marks: 40%

Group Assignment

Instructions:

This is a group assignment. You will be setup into groups (about 6 members per group).

The group is to research and investigate an area of Computing in information technology as it is used within a context.

The goal of this assignment is to engage students in critical thinking about the intersection of AI (artificial intelligence) and Logistics.

By exploring your attitudes, values and emotional responses, you will gain a deeper understanding and appreciation of the specified technology.

The total word count of the report should be within the range of 5,000 words. You may exceed this word count if your topic necessitates it however, the absolute limit for word count should be +/- 1000 words.

No marks will be awarded for the entire assignment if:

• Any part is copied directly from published materials or from another student.
• There is “careless” use of AI tools (see the associated document).
• The work does not adhere to the assignment case.

All submissions should be made on or before the due date. Any late submissions after the deadline will not be entertained. Zero (0) mark will be awarded for late submission unless extenuating circumstances are upheld.

All highlighted items in this document requires a good amount of research and as a group, you all must understand the fundamentals before proceeding with the tasks.

As a group, you will be researching the implementation of AI in Logistics. Your task is to investigate and reflect on the impact AI has had on supply chain and transportation (logistics).

1. An exploration of AI in Logistics:

Begin by researching and providing a precise definition of AI, and then Logistics (supply chain management, inventory control, route optimization, and last-mile delivery).

Explain how AI is transforming supply chain management, inventory control, route optimization, and last-mile delivery.

1. Attitude Exploration:

Reflect on your personal attitude towards AI in Logistics. Consider questions such as:

• How do you feel about AI replacing traditional logistics processes?
• What excites you about AI-driven supply chains?
• What concerns you about AI-driven supply chains?
• Are there ethical implications related to job displacement or bias in AI decision-making?
• Make sure to document the above as it will be relevant to Section E: Personal Reflections

1. Value Assessment:

Identify and discuss the values associated with AI in logistics. Consider the following:

• Efficiency: How can AI streamline logistics operations and reduce costs?
• Sustainability: Explore how AI can enhance environmental sustainability in transportation and warehousing.
• Equity: Consider fairness and inclusivity in AI algorithms.

1. Case Study Analysis:

Choose a case study from the given list attached to this assignment document.

Analyse the case study from an affective (relating to moods feelings and attitudes) perspective:

• How do stakeholders (logistics managers, workers, customers) perceive the integration of AI?
• What emotions are associated with the adoption of AI logistics solutions?

1. Personal Reflections:

• Write a reflective essay (around 800 words each student) synthesizing your attitude, values, and insights related to AI in logistics.
• Consider both positive and negative emotions, ethical considerations, and potential societal impacts.

Guidelines for the Report:

Document the results of your work in a professional and systematic manner, in the form of a computerized report, appropriately formatted.

Your completed documentation should include the following sections:

1. Cover
2. Abstract
3. Table of contents
4. Introduction
5. Chapters / Sections

The following chapters should be a combination/summary of ALL students works/findings

• An exploration of AI in Logistics
• Attitude Exploration
• Value Assessment
• Case Study Analysis
• Personal Reflections

1. Conclusion
2. References

Assessment Criteria (Marking Grid):

Marking Criteria:

Distinction

Demonstrated comprehensive research with detailed evidence. High level of analysis performed, exceptional and thorough knowledge and understanding displayed with regard to attitude, values, and insights on System Software and Computing Concepts. Documentation presented in a professional manner, without any spelling or grammar mistakes. Displayed evidence of critical appraisal.

Credit

Adequate research conducted with fair detail of evidence presented. Moderate level of understanding, analysis and knowledge displayed. Good level of documentation presented. Some level of reflection in the documentation. Moderate level of critical appraisal.

Pass

Low level research conducted. Some evidence of research displayed. Basic level of analysis, knowledge and understanding displayed. Satisfactory level of documentation. Satisfactory or low level of reflection displayed. Poor level of critical appraisal demonstrated.