Knowledge Model for Responsible AI

Design of a Sustainable Knowledge Model Towards Responsible AI

Degree type


Closing date

29 October 2021



Citizenship requirement

Domestic/International Onshore

About the research project

As the development of AI, it has increasing impacts on society. In most cases, the AI model is treated as a Blackbox to its users. However, outcomes of the AI model may not be trusted by the end users. Building and maintaining public trust in AI has been identified as the key to successful and sustainable of innovation. Responsible AI is aiming to increase the trust of human on AI models (Zhu, 2021).

Currently, governments/social organisations propose multiple principles and regulations to guide the ethics of AI models/products/services. Technology companies also have their policies to make alignment with these principles and regulations. This project aims to enhance the realisation of these ethical values in the workflow of AI models. The regulation documents written by human will be processed and transferred to a machine-readable knowledge model. On the other hand, all the factors of AI model, such as source data, algorithm, prediction outcomes will be recorded. These records will also be transferred to a machine-readable knowledge model. The comparison of these two knowledge models will indicate whether the targeted AI model satisfies the corresponding ethical requirements. By doing this, the ethical alignment will be realised directly in AI model level, rather than the policy level. It will increase the trusts on the products/services based on the AI model. Moreover, it is sustainable as regulation evolving. There is a trend that different regulations converge to some common values. The knowledge model generated from regulation documents can be self-updated. Eventually, it can be extended to a framework covering the whole processes of the AI products/services.

Primary Supervisor

Meet A/Prof Quan Bai


Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

  • a living allowance stipend of $28,597 per annum (2021 rate, indexed annually) for 3.5 years
  • a relocation allowance of up to $2,000
  • a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.


The project is open to domestic (Australian and New Zealand) and international applicants who are already in Australia (onshore) at the time of submitting their application.

Due to current Australian COVID-19 travel restrictions the University cannot accept applications from international applicants who are currently overseas.

Applicants should review the Higher Degree by Research minimum entry requirements.

Selection Criteria

The project is competitively assessed and awarded.  Selection is based on academic merit and suitability to the project as determined by the College.

Additional essential selection criteria specific to this project:

  • Research PG qualification in ICT

Additional desirable selection criteria specific to this project:

  • Good research publication track record
  • Good knowledge background in AI

Application process

There is a three-step application process:

  1. Select the project, and check you meet the eligibility and selection criteria;
  2. Contact the Primary Supervisor, A/Prof Quan Bai, if you have any questions about the project; and
  3. Click here to submit an application by the closing date listed above.
    • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
    • As part of your application you will be required to submit a covering letter, a CV including 2 x referees and your project research proposal.

Following the application closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email.

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