Students

PHIL8400 – Rights, Responsibilities, and AI

2023 – Session 2, In person-scheduled-weekday, North Ryde

General Information

Download as PDF
Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor
Dr Regina Fabry
regina.fabry@mq.edu.au
Lecturer
Prof Paul Formosa
paul.formosa@mq.edu.au
Lecturer
A/Prof Abhaya Nayak
abhaya.nayak@mq.edu.au
Lecturer
Prof Niloufer Selvadurai
niloufer.selvadurai@mq.edu.au
Tutor
Bhanuraj Kashyap
bhanuraj.kashyap@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
COMP6400 or COMP2400
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

With increasing entrenchment of AI in human affairs, its moral, legal and other social aspects are becoming a significant issue. For instance, there is a significant concern that the AI-powered automated vehicles will interfere with the "right to work" of many who drive as a profession. This unit, co-designed and co-taught by relevant experts in Computing, Philosophy and Law, will cover ethical, legal and other social implications of topical issues such as algorithmic decision making, self-driving vehicles, autonomous drones in the battlefield, and robots in the healthcare sector. Students will be exposed to ideas such as balancing risks and responsibilities, both in the moral and legal sense, in the context of the evolving AI technology.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Explain the fundamental principles underlying AI, and the normative constraints that it needs to satisfy.
  • ULO2: Demonstrate an understanding of the ethical, legal, and other socioeconomic implications of AI.
  • ULO3: Demonstrate an understanding of what Responsible AI means, or will mean, in our current as well future society.
  • ULO4: Effectively communicate your findings to different stakeholders including industry professionals, lawyers and Government bodies

General Assessment Information

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a mark of ‘0’ (zero) will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55pm. A 1-hour grace period is provided to students who experience a technical issue. This late penalty will apply to written reports and recordings only. Late submission of time sensitive tasks (such as tests/exams, performance assessments/presentations, scheduled practical assessments/labs will be addressed by the unit convenor in a Special consideration application.

Information about this unit's policy on the use of AI will be made available in the Assessment block in iLearn. Plase check that information and contact the convenor if you have any questions.

 

 

 

Assessment Tasks

Name Weighting Hurdle Due
Essay 40% No 05/11/2023 at 11:55pm
Participation 15% No Week 2 to Week 12
Online Quizzes 15% No 17/08/2023, 28/09/2023, and 26/10/2023 at 11:55pm
Case Study 30% No 31/08/2023 at 11:55pm

Essay

Assessment Type 1: Essay
Indicative Time on Task 2: 38 hours
Due: 05/11/2023 at 11:55pm
Weighting: 40%

 

Research essay on a topic from the unit

 
On successful completion you will be able to:
  • Explain the fundamental principles underlying AI, and the normative constraints that it needs to satisfy.
  • Demonstrate an understanding of the ethical, legal, and other socioeconomic implications of AI.
  • Demonstrate an understanding of what Responsible AI means, or will mean, in our current as well future society.

Participation

Assessment Type 1: Participatory task
Indicative Time on Task 2: 12 hours
Due: Week 2 to Week 12
Weighting: 15%

 

Active engagement in class discussions and associated activities

 
On successful completion you will be able to:
  • Explain the fundamental principles underlying AI, and the normative constraints that it needs to satisfy.
  • Demonstrate an understanding of the ethical, legal, and other socioeconomic implications of AI.
  • Demonstrate an understanding of what Responsible AI means, or will mean, in our current as well future society.

Online Quizzes

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 3 hours
Due: 17/08/2023, 28/09/2023, and 26/10/2023 at 11:55pm
Weighting: 15%

 

Online quizzes covering key topics and concepts

 
On successful completion you will be able to:
  • Explain the fundamental principles underlying AI, and the normative constraints that it needs to satisfy.
  • Demonstrate an understanding of the ethical, legal, and other socioeconomic implications of AI.
  • Demonstrate an understanding of what Responsible AI means, or will mean, in our current as well future society.

Case Study

Assessment Type 1: Case study/analysis
Indicative Time on Task 2: 30 hours
Due: 31/08/2023 at 11:55pm
Weighting: 30%

 

Case study involving application of theoretical concepts to practical context

 
On successful completion you will be able to:
  • Explain the fundamental principles underlying AI, and the normative constraints that it needs to satisfy.
  • Demonstrate an understanding of the ethical, legal, and other socioeconomic implications of AI.
  • Demonstrate an understanding of what Responsible AI means, or will mean, in our current as well future society.
  • Effectively communicate your findings to different stakeholders including industry professionals, lawyers and Government bodies

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Delivery: With the exception of one recorded lecture, all lectures are delivered live. The tutorial is held in person.

Resources: All required readings are provided in iLearn and Leganto. You must read the required readings before class.

Unit Schedule

W1 – Introduction (Prof Paul Formosa) – 28 July 2023

  • No readings
  • No tutorial

W2 – Ethics and Robotics (A/Prof Abhaya Nayak) – 4 August 2023

  • Reading 1: Birhane, A., & van Dijk, J. (2020). Robot rights? Let’s talk about human welfare instead. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 207–213. https://doi.org/10.1145/3375627.3375855
  • Reading 2: Vanderelst, D., & Winfield, A. (2018). An architecture for ethical robots inspired by the simulation theory of cognition. Cognitive Architectures for Artificial Minds, 48, 56–66. https://doi.org/10.1016/j.cogsys.2017.04.002 
  • Tutorial 1

W3 – Algorithmic Decision Making (A/Prof Abhaya Nayak) – 11 August 2023

  • Reading 1: Gorwa, R., Binns, R., & Katzenbach, C. (2020). Algorithmic content moderation: Technical and political challenges in the automation of platform governance. Big Data & Society, 7(1), 2053951719897945. https://doi.org/10.1177/2053951719897945
  • Reading 2: Lim, H. S., & Taeihagh, A. (2019). Algorithmic decision-making in AVs: Understanding ethical and technical concerns for smart cities. Sustainability, 11(20). https://doi.org/10.3390/su11205791
  • Tutorial 2
  • Quiz 1

W4 – AI and Safety (A/Prof Abhaya Nayak) – 18 August 2023

  • Reading 1: Dobbe, R., Krendl Gilbert, T., & Mintz, Y. (2021). Hard choices in artificial intelligence. Artificial Intelligence, 300, 103555. https://doi.org/10.1016/j.artint.2021.103555
  • Reading 2: Burton, S., Habli, I., Lawton, T., McDermid, J., Morgan, P., & Porter, Z. (2020). Mind the gaps: Assuring the safety of autonomous systems from an engineering, ethical, and legal perspective. Artificial Intelligence, 279, 103201. https://doi.org/10.1016/j.artint.2019.103201
  • Tutorial 3

W5 – Moral Responsibility of AI Researchers (A/Prof Abhaya Nayak) – 25 August 2023

  • Reading 1: Freedman, R., Borg, J. S., Sinnott-Armstrong, W., Dickerson, J. P., & Conitzer, V. (2020). Adapting a kidney exchange algorithm to align with human values. Artificial Intelligence, 283, 103261. https://doi.org/10.1016/j.artint.2020.103261
  • Reading 2: Schaich Borg, J. (2022). The AI field needs translational Ethical AI research. AI Magazine, 43(3), 294–307. https://doi.org/10.1002/aaai.12062
  • Tutorial 4
  • Case study

W6 – Ethical/Social AI Frameworks (Prof Paul Formosa) – 1 September 2023

  • Reading 1: Hagendorff, T. (2020). The ethics of AI ethics: An evaluation of guidelines. Minds and Machines, 30(1), 99–120. https://doi.org/10.1007/s11023-020-09517-8
  • Reading 2: Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5
  • Tutorial 5

W7 – The Regulation of AI (Prof Niloufer Selvadurai) – 9 September 2023

  • Reading 1: Gacutan, J., & Selvadurai, N. (2020). A statutory right to explanation for decisions generated using artificial intelligence. International Journal of Law and Information Technology, 28(3), 193–216. https://doi.org/10.1093/ijlit/eaaa016
  • Reading 2: Smuha, N. A. (2021). From a ‘race to AI’ to a ‘race to AI regulation’: Regulatory competition for artificial intelligence. Law, Innovation and Technology, 13(1), 57–84. https://doi.org/10.1080/17579961.2021.1898300
  • Tutorial 6
  • Quiz 2

W8 – Power, Politics, and AI (Dr Regina Fabry) – 29 September 2023

  • Reading 1: Lazar, S. (2022). Power and AI: Nature and justification. In J. B. Bullock, Y.-C. Chen, J. Himmelreich, V. M. Hudson, A. Korinek, M. M. Young, & B. Zhang (Eds.), The Oxford Handbook of AI Governance (p. 0). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780197579329.013.12
  • Reading 2: Campolo, A., & Crawford, K. (2020). Enchanted determinism: Power without responsibility in artificial intelligence. Engaging Science, Technology, and Society, 6, 1–19. https://doi.org/10.17351/ests2020.277
  • Tutorial 7

W9 – What Is AI After All? The Turing Test Revisited (Dr Regina Fabry) – 6 October 2023

W10 – Explainable AI (Dr Regina Fabry) – 13 October 2023

W11 – Equitable AI (Dr Regina Fabry) – 20 October 2023

  • Reading 1: Cossette-Lefebvre, H., & Maclure, J. (2022). AI’s fairness problem: Understanding wrongful discrimination in the context of automated decision-making. AI and Ethics. https://doi.org/10.1007/s43681-022-00233-w
  • Reading 2: Kasirzadeh, A. (2022). Algorithmic fairness and structural injustice: Insights from feminist political philosophy. Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 349–356. https://doi.org/10.1145/3514094.3534188
  • Tutorial 10
  • Quiz 3

W12 – Sustainable AI (Dr Regina Fabry) – 27 October 2023

  • Reading 1: van Wynsberghe, A. (2021). Sustainable AI: AI for sustainability and the sustainability of AI. AI and Ethics, 1(3), 213–218. https://doi.org/10.1007/s43681-021-00043-6
  • Reading 2: Cowls, J., Tsamados, A., Taddeo, M., & Floridi, L. (2023). The AI gambit: Leveraging artificial intelligence to combat climate change—Opportunities, challenges, and recommendations. AI & SOCIETY, 38(1), 283–307. https://doi.org/10.1007/s00146-021-01294-x
  • Tutorial 11

W13 – Writing and Review

  • No Readings
  • No Lecture
  • No Tutorial
  • Essay

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via AskMQ, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Unit information based on version 2023.02 of the Handbook