Responsible Decision Making
| Code | School | Level | Credits | Semesters |
| DATA2004 | Computer Science | 2 | N/A | Full Year UK |
- Code
- DATA2004
- School
- Computer Science
- Level
- 2
- Credits
- N/A
- Semesters
- Full Year UK
Summary
This module will introduce the principles of ethical data-driven development of decision-making tools. It will enable apprentices to understand real-world implications and consequences of developing AI techniques and appreciate the range of data science techniques that can be used to analyse and manage biased data. Learners will need to investigate and understand specific legal and governance issues relevant to their role (pulling from, working with and enhancing their on-the-job knowledge and experience)
Indicative Content
Data security and governance
Privacy and Data Protection
Ethics of AI (Accountability and transparency in AI)
Creating trustworthy algorithms
Algorithmic fairness and diversity
Legal frameworks, codes of ethics and professional responsibility.
Target Students
Only available to those studying towards the Data Scientist Degree apprenticeship programme
Classes
12 hours of distance learning video content and independent lap sheets supported by ad hoc remote drop in sessions
Assessment
- 100% coursework: Completion of the teaching block
Assessed by end of designated period
Educational Aims
To introduce the principles of ethics, bias and responsible decision making in the context of artificial intelligence and data science.To introduce case studies in responsible decision making, including cases in which lack of oversight had real-world consequences.To enable the apprentices to understand and be able to put in to practice responsible decision-making techniques.Learning Outcomes
Understand the role of ethical, privacy, bias and legal concerns and to embed this into practice.
Understand how data science operates within the context of data governance, data security, and communications.
Identify a suitable data science problem, questions and corresponding software which relate to organisational goals.