General Course Information
1.1 Course details
|Course code:||LLAW6300 / JDOC6300|
|Course name:||Digitalisation: Health, Law and Policy|
|Programme offered under:||LLM Programme / JD Programme|
|Prerequisites / Co-requisites:||No|
|Credit point value:||9 credits / 6 credits|
|Cap on student numbers:||50|
1.2 Course description
This is an Elective designed in part for the LLM in Medical Ethics and Law programme, and will have three key objectives:
(1) Introduce students to the ethical and legal implications of digitalisation of health and related aspects of law, primarily from a policy (or regulatory) standpoint. Health is referred to generally as the module will study digitalisation in a variety of health-related contexts, including healthcare (e.g. electronic health records and use of sensors to monitor medical adherence), biomedical research (e.g. use of artificial intelligence (AI) in drug development), health insurance (e.g. use of Big Data analytics in claim and loss predictions) and public / global health (e.g. use of digital technologies to support realisation of the Sustainable Development Goals);
(2) Introduce students to Computational Law as applicable to digitalisation of health (as depicted in Objective (1) above). The module will focus on a number of computational models of legal reasoning (and related legal apps that have been developed), and will examine how modern legal expert systems are likely to change in response to the digitalisation of health; and
(3) Introduce students to data visualisation (in both health and law) and means of thinking critically about an increasingly data-driven world (with focus on potential sources of misinformation and disinformation).
Digitalisation refers to the added value of applying digital technologies (such as Big Data analytics, AI and robotics) to interventions directed at meeting needs or goals that relate to health, administration of justice and regulatory compliance. The course adopts a Policy approach in that different epistemic systems of ethical, legal/regulatory and governance principles (e.g. human-centricity) that guide decisions to achieve health and legal outcomes will be examined. The ethical and legal implications of digitalisation policies in both subjective and objective decision-making will be considered.
The jurisprudential basis of right to information, freedom of expression (as pertinent to health), privacy, as well as concerns with misinformation and disinformation will be studied. The course will also cover the role of national laws, international law, and instruments touching on digitalisation concerns in health and related aspects of legal practice and regulation. Of these laws and normative instruments, this course will focus on those that pertain to data security, collection, sharing and use, control (e.g. through intellectual property) as well as those that apply to data custodians and intermediaries (including cloud platforms). Additionally, the normative impact of social organisations (including business entities) on digitalisation and regulatory trends will be considered.
1.3 Course teachers
|Course convenor||Calvin Hoemail@example.com||CCT 803||By email|
2.1 Course Learning Outcomes (CLOs) for this course
CLO 1 Students will be able to describe and explain basic ethical and legal concepts pertaining to digitalisation and data science more generally, including right to information, freedom of speech (and associated limitations), data sovereignty, privacy, cybersecurity, misinformation and disinformation, as well as a range of principles that apply to data science and related applications, particularly in artificial intelligence/machine learning and Big Data analytics.
CLO 2 Students will be able to describe and explain the role of international law instruments and policies touching on digitalisation in the context of health and related developments in regulatory governance and legal practice, how international law operates, and how it is different from national laws on digitalisation in health and related legal processes.
CLO 3 Students will be able to explain the key features of computational law as applicable to the health(care) context(s), outline legal reasoning that underscores some legal apps and describe likely future applications of data analytics in legal practice.
CLO 4 Students will be able to identify different epistemic systems of ethical, legal/regulatory and governance principles in digitalisation policies relating to health and related legal processes, and to apply them in both subjective and objective decision-making.
CLO 5 Students will be able to apply their knowledge of data visualisation in order to communicate quantitative data more effectively, as well as to interpret data accurately and to identify potential misinformation and disinformation.
2.2 LLM Programme Learning Outcomes (PLOs)
Please refer to the following link: https://course.law.hku.hk/llm-plo/
2.3 Programme Learning Outcomes to be achieved in this course
|PLO A||PLO B||PLO C||PLO D||PLO E||PLO F|
3.1 Assessment Summary
|Assessment task||Due date||Weighting||Feedback method*||Course learning outcomes|
|Class participation (including reflection papers and presentations)||TBA||30%||1||1, 2, 3, 4, 5|
|Take home exam||3 May 2022||70%||1||1, 2, 3, 4, 5|
|*Feedback method (to be determined by course teacher)|
|1||A general course report to be disseminated through Moodle|
|2||Individual feedback to be disseminated by email / through Moodle|
|3||Individual review meeting upon appointment|
|4||Group review meeting|
|5||In-class verbal feedback|
3.2 Assessment Detail
To be advised by course convenor(s).
3.3 Grading Criteria
4.1 Learning Activity Plan
|Seminar:||3 hours / week for 12 teaching weeks|
|Private study time:||9.5 hours / week for 12 teaching weeks|
4.2 Details of Learning Activities
To be advised by course convenor(s).
|Reading materials:||Reading materials are posted on Moodle|
|Core reading list:||TBA|
|Recommended reading list:||TBA|
Please refer to the following link: http://www.law.hku.hk/course/learning-resources/