LLAW6300 & JDOC6300

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
Semester: Second
Prerequisites / Co-requisites: No
Credit point value: 9 credits / 6 credits

1.2 Course description

This course 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

Name E-mail address Office Consultation
Course convenor Peter Cashin peter@cashinhk.com N/A By email

Learning Outcomes

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
CLO 1
CLO 2
CLO 3
CLO 4
CLO 5

Assessment(s)

3.1 Assessment Summary

Assessment task Due date Weighting Feedback method* Course learning outcomes
Class participation (including reflection papers and presentations) TBC 30% 1 1, 2, 3, 4, 5
Take home exam TBC 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

Use of Artificial intelligence (“AI”):

This is an important aspect to the subject being taught.  Understanding how it operates is important to understanding how it is and will be used and regulated in the future.

The use of AI is permitted in students’ research as an enhanced learning and research tool only. It is not a substitute for appropriate references and its use must be proportionate and supervised.  AI must not be over-used (as explained in the University guidelines) and must not offend the usual academic responsibilities of a student.

3.3 Grading Criteria

Please refer to the following link: https://www.law.hku.hk/_files/law_programme_grade_descriptors.pdf

Learning Activities

4.1 Learning Activity Plan

Seminar: 3 hours / week for 11 teaching weeks
Private study time: 9.5 hours / week for 11 teaching weeks

Remarks: the normative student study load per credit unit is 25 ± 5 hours (ie. 150 ± 30 hours for a 6-credit course), which includes all learning activities and experiences within and outside of classroom, and any assessment task and examinations and associated preparations.

4.2 Details of Learning Activities

To be advised by course convenor(s).

Learning Resources

5.1 Resources

Reading materials: Reading materials are posted on Moodle
Core reading list: TBA
Recommended reading list: TBA

5.2 Links

Please refer to the following link: http://www.law.hku.hk/course/learning-resources/