| Unit name | Business Analytics and Responsible Innovation |
|---|---|
| Unit code | EFIMM0140 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Lythreatis |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Management - Business School |
| Faculty | Faculty of Social Sciences and Law |
Why is this unit important?
This unit is important because it gives students sound knowledge and deep understanding of the implications of business analytics within the frameworks of ethics, sustainability, social responsibility, and responsible innovation. It focuses on both the risks and benefits of the adoption of business analytics for organisations, consumers, society, and the environment. The unit will equip students with the necessary skills and thinking to identify and solve ethical issues in business analytics. The topics covered in the unit offer the knowledge needed to build a more sustainable, ethical, and inclusive future. The unit engages students in in-class discussions of practical and thought-provoking case studies from the academic literature and the news.
How does this unit fit into your programme of study?
This unit fulfils the purpose of familiarising students with the ethical, organisational, societal, and environmental implications of the adoption of business analytics. Students will learn about the complexity of balancing between the increasing demand for data to competitively innovate and the legal and social obligation to ensure safe and ethical treatment of data. It also complements other projects within the programme such as the final Applied Research Project.
An overview of content
The content of the unit includes identifying ethical dilemmas in business analytics, datafication of the workplace and the marketplace, quantification of the self, fairness in algorithmic decision making, national and international legal frameworks related to data analytics, big data for sustainable development and social and digital responsibility, the responsible innovation framework, surveillance capitalism, and the identification of solutions to ethical implications in business analytics.
How will students, personally, be different as a result of the unit?
Upon completion of the unit, students will have formed a deep understanding of the ethical and societal risks of integrating business analytics in business processes and the delivery of products and services to consumers. They will have acquired knowledge of how to use business analytics for sustainable development and to build better and inclusive futures. Students will have developed the skills to recognise ethical issues in business analytics adoption and provide effective solutions to such issues.
Learning Outcomes
At the end of this unit, students will be able to:
ILO 1 – Recognise the implications of business analytics for productivity, responsible innovation, sustainable development, and environmental and social responsibility.
ILO 2 – Evaluate the ethical and legal issues in the use of personal data in product/service innovation.
ILO 3 – Apply appropriate theoretical frameworks to critically analyse the organisational, ethical, and societal implications of business analytics in the workplace and for the delivery of services to consumers.
ILO 4 – Propose solutions to mitigate risk and safeguard public trust from the adoption and use of business analytics, and to create more sustainable futures.
Teaching will be conducted through ten lectorial sessions of 3 hours (total 10*3 = 30 hours) across TB2. These comprise a combination of one-hour lecture talks and two-hour tutorial-style discussions that focus on the aspects taught in the lecture. The latter will involve deep academic conversations, case studies, debates, tasks, as well as interesting talks from people in the industry. Optional advice and feedback hour sessions for additional support are available. Students will be required to do some preparation reading and activities before the sessions. All learning material will be available on the unit’s Blackboard page. Additional readings will also be provided on Blackboard to support students who wish to acquire a deeper learning about responsible innovation of business analytics. The discussion board on Blackboard will also be used to complete tasks and strengthen peer interaction. It is also a place for students to ask any questions about the unit.
Tasks which help you learn and prepare you for summative tasks (formative):
There will be one main formative assessment. This will take place in the middle of the teaching term and will comprise in-class group presentations based on a set of problems to which students need to propose sustainable solutions using systems of data acquisition and analytics (ILOs 1&4). Both instructor and written peer feedback will be given.
Other forms of formative assessment will include readings and task preparation before each session (ILOs 1, 2, 3 & 4).
Tasks which count towards your unit mark (summative):
3,000-word individual assignment (100%): Students will work individually and independently to choose a real-life example where AI has been adopted and discuss the positive impacts and opportunities of the innovation (ILO1). Students are also required to identify and discuss potential issues and implications, such as the ethical, societal, legal, political, and environmental challenges, from the adoption of this technology, drawing on appropriate theories and frameworks learned in the unit (ILOs2&3). Students should also propose solutions to these implications and discuss corrective action to ensure the safety and security of this innovation. Using theoretical and legal concepts learned throughout the unit, students will also have to propose policy recommendations that mitigate risk and safeguard public trust from the adoption and use of the chosen technology in the chosen industry (ILO4).
When assessment does not go to plan
When a student fails the unit and is eligible to resubmit, they will be reassessed with a single 3,000-word individual assignment weighted at 100%, covering all intended learning outcomes (ILOs 1-4) for the unit. The resit will consist of an individual essay covering the various topics of the unit.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. EFIMM0140).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
