PhD in Human-Inspired Artificial Intelligence

This exciting PhD in Human-Inspired Artificial Intelligence will train the next generation of AI researchers, technologists, and leaders in the development of human-centred, human-compatible, responsible and socially and globally beneficial AI technologies. The course offers research training in areas such as fundamental human-level AI, social and interactive AI, cognitive AI, creative AI, health and global AI, and responsible AI. Students will be educated in an interdisciplinary environment where they can get access to expertise not only in the technical but also human, ethical, applied and industrial aspects of AI.

This programme is distinct from other PhD programmes in that it takes a strongly interdisciplinary and cross-disciplinary approach to technical AI. It will be based at the Centre for Human-Inspired Artificial Intelligence (CHIA) within the Institute for Technology and Humanity (ITH) where PhD students will have access to both a large community of scholars and students tackling similar questions and to the active research events programme that constitutes a key part of CHIA’s work. The course addresses the broader need for experts equipped to develop more responsible and human-centred AI as academia, industry, government and non-profit sectors increasingly recruit AI specialists and is a logical next step for students moving through AI-related master’s programmes and wishing to specialise in human-inspired AI. The interdisciplinary nature of human-inspired AI means that the programme will involve working closely also with other units of the University, including co-supervision arrangements, access to research seminars, and access to facilities.

The PhD in Human-Inspired AI aims to equip students with the skills and knowledge to contribute critically and constructively to research in human-inspired AI. It introduces students from diverse backgrounds to research skills and specialist knowledge from a range of academic disciplines and provides them with the opportunity to carry out focused research under close supervision by domain experts at the University.

The programme will train the next generation of researchers and leaders in AI by

• providing them with educational infrastructure and interdisciplinary research environment and world-leading training in human-inspired AI,
• providing them with the critical tools to engage with the forefront of academic knowledge, methods and applications in this area,
• developing the advanced skills and abilities to identify, approach and address practical interdisciplinary research challenges,
• supporting students to develop a broad and deep understanding of the technical, ethical, applied and human aspects of AI,
• developing the ability and initiative to identify, address and approach relevant and complex challenges across sectors and society.

The course will benefit

• students wanting to engage with human-inspired AI by enabling them to hone critical, methodological and technical skills, develop new approaches and test them out, and specialise,
• students locating themselves in other home disciplines who wish to develop advanced projects including CHIAs approaches and orientations,
• students entering into or returning to careers in academia, tech industry, and other sectors by giving them the advanced skills, critical perspectives, and methodological insights to pursue these pathways.

Learning Outcomes

Knowledge and Understanding

By the end of the PhD programme our graduates will demonstrate:

• The ability to create and interpret new knowledge, through original research or other advanced scholarship of a quality to satisfy peer review, extend the forefront of the discipline, and merit publication.
• The general ability to conceptualise, design and implement a project for the generation of new knowledge, applications or understanding at the forefront of human-inspired AI, and to adjust the project design in the light of unforeseen problems.
• A detailed understanding of applicable techniques for cross-disciplinary research and advanced academic enquiry in the field of human-inspired AI
• The ability to make informed judgements on complex issues in human inspired AI, often in the absence of complete data.
• A critical perspective on the governance and ethical challenges that arise from applications of human-inspired AI and how these sit within and interact with wider society.
• A systematic acquisition and understanding of a substantial body of knowledge in relation to the history, methods, and applications of human-inspired AI.

Skills and other attributes

Graduates of the course will be able to:

• Continue to undertake pure and/or applied research and development at an advanced level, contributing substantially to the development of new techniques, ideas or approaches.
• Communicate their ideas and conclusions clearly and effectively to specialist and non-specialist audiences.
• Contribute constructively within national, international and cross-disciplinary environments.
• Transfer skills and qualities acquired during the programme to successfully engage in employment requiring the exercise of personal responsibility and largely autonomous initiative in complex and unpredictable situations, in professional or equivalent environments.

Employability

Students of the programme will graduate with a formal qualification in the rapidly expanding area of AI. The emphasis is on human-inspired AI. The combination of specialist, technical expertise in AI and cross-disciplinary approaches involving a wide range of human-centric disciplines means that our doctoral graduates will be uniquely qualified in the sector. The PhD will, therefore, put them in a strong position to pursue careers in a variety of academic and non-academic settings, for example organisations and consultancies in diverse sectors such as tech, health, environment, education, journalism, civil service among others.

For those intending to continue into an academic career, the course will equip them with the skills, experience and qualification for applying for a postdoctoral research position.

Continuing

For Cambridge students applying to continue from the MPhil to a PhD, students must achieve a pass in the MPhil by Thesis or an overall distinction in the MPhil by Advanced Study.

All applications are judged on their own merits, and students must demonstrate their suitability to undertake doctoral-level research.

Open Days

The Centre for Human-Inspired Artificial Intelligence (CHIA) will hold an online webinar 9:00-9:45am on 4 November 2024. Please see the CHIA website for information on how to register for this event.

The Cambridge University Postgraduate Virtual Open Day usually takes place at the beginning of November. It's a great opportunity to ask questions to admissions staff and academics, explore the Colleges virtually, and to find out more about courses, the application process and funding opportunities. Visit the Postgraduate Open Day page for more details.

See further the Postgraduate Admissions Events pages for other events relating to Postgraduate study, including study fairs, visits and international events.

Applicants for this course should have achieved a UK Masters (Pass). If your degree is not from the UK, please check International Qualifications to find the equivalent in your country. Distinction or equivalent in a master’s level degree is normally required but in certain cases CHIA may consider other postgraduate work or qualifications alongside a strong honours degree in a relevant field. If you wish to apply to undertake a PhD on a part-time basis please refer to the admissions advice for potential part-time students. We accept students from a wide range of academic backgrounds, but applicants should be aware of and prepared for the computational, mathematical, and programming aspects of their research. We advise students with limited experience in these areas to join the open day to assess course fit for their need. University Minimum Academic Requirements Language Requirement

Listening: 7.0, Writing: 7.0, Reading: 7.0, Speaking: 7.0, Total: 7.5, Listening: 25, Writing: 25, Reading: 25, Speaking: 25, Total: 110