Human-Centred Artificial Intelligence for Democracy

This PhD scholarship is in the context of an international collaboration funded by the Swiss National Science Foundation under the project “Large-Scale Political Participation: Issue Identification, Deliberation, and Co-creation”. The overall project will investigate how technology-supported, large-scale crowd-computing approaches can be used to strengthen the functions of the consultation and popular initiative procedures. These two procedures are arguably the most impactful participatory mechanisms of direct democracy, as they allow the population to not only strongly influence the outcome of the political process but also to set the agenda (in popular initiatives). Whilst they look different from the outside, they share significant structural similarities: Both are complex mechanisms, as they require (1) the identification of the controversial issues; (2) a deliberation to find a suitable solution as well as to assess its material accuracy, feasibility of implementation, and public acceptance; and (3) the refinement of the deliberation’s result into a submission document.

 

The aim of this PhD is to measure the effect of the contextual information provided to contributors and human annotators. This will involve performing controlled experiments varying the type and amount of contextual information provided and measuring the impact on the quality and diversity of contributed content to the annotation and deliberation process. Results will include an understanding of how to optimize for certain desired outcomes such as, for example, diversity of opinions or making decisions based on similar previous deliberations. To this end, the project will also include the investigation of task assignment strategies which will identify the right contributor from a pool of contributors given a certain deliberation task. After this, we will investigate different group composition strategies including, for example, maximizing the diversity of lines of thought with groups formed by like-minded people to optimize desired properties of the crowdsourced text.

 

Research environment

 

The University of Queensland, Australia is the world's top 50 university (QS World University Rankings 2022). Embedded in the Data Science discipline at The University of Queensland, Brisbane, Australia, you will be part of a world-leading research group in Data Science with research funding coming both from the industry sector (e.g., Facebook, Google) and the public sector (e.g., Australian Research Council, Swiss National Science Foundation).

 

Host for the 2032 Olympic Games, Brisbane is one of the fastest-growing capital cities in Australia in terms of population and employment. Brisbane residents are young and skilled, highly educated, and culturally diverse. With 12 months of sunshine-filled days and clear blue skies, Brisbane has a climate that sets the scene for year-round alfresco activities. Even in the midst of a Brisbane winter, you’ll be yearning to play in the parks and dine outdoors. As the most biologically-diverse capital in Australia, Brisbane is a green city with clean, healthy air and a clear commitment to its environment. The Brisbane City Council achieved carbon-neutral status for its operations in 2017. Brisbane’s public transport system is a clean and green network of trains, ferries (CityCats), and buses that have been integrated so commuters can travel seamlessly between each service when using a go card. Brisbane's nightlife is extensive, spread across both sides of the River, and packed with variety and options.

 

 

Eligibility

 

You're eligible if you meet the entry requirements for a higher degree by research.

 

 

How to apply

 

Before submitting an application you should:

 

• check your eligibility for a Doctor of Philosophy (PhD)
• prepare your documentation
• contact Associate Professor Gianluca Demartini (g.demartini@uq.edu.au) to discuss your suitability for this scholarship

 

 

You apply for this scholarship when you submit an application for a Doctor of Philosophy (PhD). You don't need to submit a separate scholarship application.

 

When you apply, please ensure that under the scholarships and collaborative study section you:

 

1. Select ‘My higher degree is not collaborative’
2. Select 'I am applying for, or have been awarded a scholarship or sponsorship'.
3. Select ‘Other’, then ‘Research Project Scholarship’, and type in ‘HUMAN CENTRED AI-DEMARTINI’ in the 'Name of scholarship' field.

 

 

Selection criteria

 

Your application will be assessed on a competitive basis.

 

We take into account your:

• previous academic record
• publication record
• honors and awards
• employment history

 

Working knowledge of machine learning libraries would be of benefit to someone working on this project.

 

You will demonstrate academic achievement in the field/s of information retrieval, artificial intelligence, machine learning, human-computer interaction, and/or recommender systems and the potential for scholastic success.

 

A background or knowledge of machine learning is highly desirable.

 

 

Rules

 

A domestic part-time student with carer’s responsibilities, a medical condition, or a disability, which prevents them from studying full-time may be eligible for scholarship consideration, on a case-by-case basis.

UQ Research Scholarships terms and conditions

 

 

Repayment status and permission for other scholarships are not specified. For further information, please contact the institution. Click the link for detailed information.