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| 1.
| Explain the different dimensions of privacy and their tensions with societal, technological and business developments. |
| 2.
| Explain different data protection and privacy regimes. Analyse privacy/data protection risks and compliance using appropriate management tools. |
| 3.
| Identify privacy related impacts in the use of information technologies and techniques including those related to data science and AI developments, and propose appropriate steps to alleviate those impacts. |
| 4.
| Discuss the challenges of AI developments to existing data protection regimes, and how ethics come to play in filling the gap. Demonstrate the ability to codify ethics to actionable measures to create conditions for trusts with stakeholders. |
Mapping from Course Learning Outcomes to Programme Learning Outcomes
| | PLO a | PLO b | PLO c | PLO d | PLO e | PLO f | PLO g | PLO h | PLO i | PLO j |
| CLO 1 | | | | | | | | | | |
| CLO 2 | | | | | | | | | | |
| CLO 3 | | | | | | | | | | |
| CLO 4 | | | | | | | | | | |
T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to
here.
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| Syllabus |
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Calendar Entry:
Using a case-based approach, students will analyse contemporary controversies from a techno-legal and ethical perspectives. The focuses are data privacy and the regulation of using data in specific areas of law. Topics include basic privacy protection techniques, such as encryption and data anonymization data privacy laws, open data policy, data protection process and technology, issues in the usage of sensitive personal data and public data.
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Detailed Description:
| COMP3312 Law and Ethics in Data Science |
Mapped to CLOs
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| Theories and legal bases of privacy and data protection. | 1 |
| Requirements and interpretations of data protection laws and regulations, including Hong Kong’s Personal Data (Privacy) Ordinance and other major legislations around the world that have impacts to Hong Kong. | 2 |
| Management tools to help compliance of data protection laws and regulations. | 2 |
| Challenges of information, communications and data science technologies on data protection, and how they may be addressed. | 2, 3 |
| The emergency of ethics as a measure to alleviate the data protection challenges arisen from data science applications. | 2, 3, 4 |
| Management tools to help codify ethics considerations in the building of data science applications. | 2, 3, 4 |
| Outlook and trends for future developments such as AI regulations. | 2, 3, 4 |
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Assessment:
Continuous Assessment:
100%
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| Teaching Plan |
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Please refer to the corresponding Moodle course.
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| Moodle Course(s) |
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