Programme Information

Elective Courses (Not all elective courses listed below will be offered each year)

PHIL7004  AI Safety and Security 

This course aims to provide students with an overview of current issues in AI safety and security. Questions include: How can we ensure that AI is interpretable? That is, how can we ensure that the behaviour and choices of sufficiently sophisticated AI systems are rationally transparent – able to be understood as supported by reasons – by human agents? How can we align AI with human values, objectives, desires, goals, and aims so that potentially quite powerful AI systems will not behave in objectionable ways? How can we ensure control of (potentially power-seeking) AI? How can we ensure that potentially dispersed AI systems are subject to human oversight and control? By the end of this course, students will be able to articulate the major safety and security challenges facing modern AI system design and the various extant approaches designed to solve these challenges. No previous background in machine learning or computer science is expected in this course.

PHIL 7005 AI Regulation and Governance 

The prevalence of AI and algorithmic decision making raises a host of governance issues and questions, including: How should privacy be protected in the use of large data sets? Are artificial agents subject to the same laws as humans? How can software be effectively regulated? Who is responsible for the potential lawbreaking behaviour of AI systems: (i) their designers, (ii) the individuals who own the hardware on which the AI is running at the time, (iii) someone else? How should AI be expected to behave when it is programmed to perform an action that is illegal? Should AI have a way to weigh illegal actions against one another? Must the capabilities of AI be published in the public domain? How do several and joint liability work in cases where different AI contribute to a single legally actionable outcome? Are there distinctive regulatory challenges faced by the introduction of AI systems? In this course, students will be exposed to a variety of theoretical frameworks designed to think carefully about these issues, and by the end of the course they will be expected to be able to analyse these and other regulatory and governance questions that arise in a variety of fields, including business, law, finance, criminal justice, etc. While focus will be on the identification and analysis of such issues, students will be exposed to examples of existing regulatory and governance frameworks as models and in order to engage critically with them.

PHIL7006  Minds and Machines 

This course compares the nature of the human mind to the minds, or proxies thereof, of complex machines. Students will explore theories of the nature of the mind and mental phenomena, including consciousness and mental representation, the relationship between the mind and the brain, and the relationship between the mind and external tools (e.g., smartphones) we exploit to extend the capacities of our minds. After establishing a firm foundation in these topics, the course will cover the theoretical foundations of research programmes in computational cognitive science and artificial intelligence research, in order to address what these philosophical and scientific theories tell us about the nature and capacities of (potential) minds, or proxies thereof, of complex machines. The course may also explore ethical issues such as the normative aspects of mental representation, manipulation by machines, the extended mind, mind uploading, and the moral status of robots.

PHIL7007  Philosophy and Ethics of Virtual Reality 

This course provides an introduction to the current and foreseeable capabilities of virtual reality technology, the philosophy and ethics of virtual reality and more generally to technophilosophy, and to the social and political implications of virtual reality technology. Central questions include: What is augmented reality? What is a virtual reality and how is it related to augmented reality? How can we know that we’re not living in a simulated reality? Are virtual objects real and if so, in what sense? Can we live a good life in a simulated reality? What is the connection between mind and body in virtual reality? What do words mean in virtual reality? Are there special social, political, economic, moral and legal issues associated with (wide uptake of) virtual reality, or within virtual reality itself? What are the implications of VR on social, political, and economic organisation? How could and should such an organisation manifest within virtual reality itself? What principles of design and design challenges arise for those creating virtual reality technologies? By the end of this course, students will be able to articulate the major ethical, philosophical and practical issues and challenges posed by virtual reality technology, and the existing approaches to addressing these.

PHIL7008  Philosophy and Ethics of Information 

In this course, students will explore topics and issues in the philosophy and ethics of information. Information and communication technologies have transformed diverse aspects of our lives, including the nature of entertainment, work, privacy, social relationships, communication, elections, and warfare, to name just a few. The course will address the question of how information and communication technology has fundamentally changed the nature of and our concepts of work, privacy, communication, etc. The course will also explore the important and distinctive ethical challenges that arise with the advent of information and communication technologies, such as online pornography, the digital divide, free speech and censorship, mis- and dis-information, and fake news. The social and political epistemology of information will also be covered by exploring how it relates to search engines and the digital public sphere. In addition to explicitly normative issues such as those listed, the course will cover foundational topics and issues in information theory, including: the nature of information, the dynamics of information, information networks, the basic principles of information, applications of information theory, and measures and applications of the quality of information. Students completing this course will be able to articulate and analyse both practical and theoretical issues concerning information.

 PHIL7009  Technology and Human Values 

This course will address questions pertinent to the more general topic of the philosophy of technology, value-sensitive design and critical design theory: What is technology? What is the relationship between technology and humanity? What are the appropriate methods and metrics for evaluating technologies and their role in society? How does disruptive technology affect our values, beliefs, concepts and social norms? How and when should humanity innovate? What is responsible innovation? What values should designers of technology possess in creating technology? Who is responsible for the harms of technology? How is technology regulated, and how should it be regulated? Can technology govern? Case studies will be of a more general nature and may include, but are not limited to: genetic selection, enhancement and eugenics, sex robots, chatbots and virtual assistants, automated weaponry, wearable or implantable technology, facial recognition, driverless vehicles, and digital or smart cities.

PHIL7010  Formal Methods for AI, Ethics and Society 

The course will allow students to build on their understanding of the technical fundamentals learnt in the core course Fundamentals of AI, Data and Algorithms. In addition to the topics covered in Fundamentals of AI, Data and Algorithms, topics may be chosen from among a selection of theoretically fundamental issues in AI, Ethics and Society, with an emphasis on the cross-disciplinary analysis of these issues. Like Fundamentals of AI, Data and Algorithms, the core competency targeted is a conceptual understanding of the way modern artificial intelligence systems operate, and on developing tools for understanding their import.

PHIL7011  AI, Ethics and Society Seminar 

The course will consist of both seminars and special learning activities. The latter might include tutorials and workshops, coding or design projects, field trips, company visits, community outreach, or other forms of experiential learning. Multiple forms of assessment will be used. The total output of written assignments should not exceed 8,000 words.

PHIL7012  AI, Ethics and Society Workshop 

In this course students will attend an academic or professional workshop whose topic is relevant to AI, Ethics, and Society. Preparation for the workshop will include (i) reading the relevant research to be discussed at the workshop, (ii) discussion of the material in advance of the workshop to prepare for the discussion (including collaborating with peers to develop questions and issues to address with the other participants of the workshop). At the workshop students will take notes and participate in a discussion of the workshop presentations. After the workshop students will prepare research reports on the issues discussed at the workshop, including outlines of plans for future work on the topics. Students enrolled in this course will be supervised by the seminar teacher throughout their preparation, attendance, and after-workshop activities. Seminar sessions will be conducted by the seminar teacher to facilitate planning, student coordination and sharing, peer-feedback, and joint discussion of relevant research, experiences, and culminating reports.

PHIL7013  AI in Business and Economics

This course focuses on the applications of artificial intelligence (AI) in business and economics. Students will learn how various AI techniques can be applied to solve real-world problems in business and economics, such as market analysis, customer relationship management, human resources management, robo-advisors, algorithmic trading, risk management, and economic predictions. Case studies and the ethical challenges raised by the use of AI in business and economics, such as algorithmic bias, data bias, security risks, privacy violations, and lack of transparency, will be discussed.