Data is fundamental to automated decision-making, and sits at the heart of its ethical and practical challenges. These range from well-known problems with bias and privacy to complexities of data ownership and flows across devices and national borders.
Examples include:
- An algorithm used to assign school grades during COVID-19 is accused of
bias against students from poorer backgrounds. - Driverless vehicles are unable to ‘see’ and avoid kangaroos because they
were designed in Europe and trained with data about animals like moose. - Photos people posted online for social purposes have been collected by a
company that markets facial recognition technology to the police. - As more workers telecommute due to the Covid-19 pandemic, new
applications are being developed for detailed monitoring of remote
employees. The new forms of data that are collected can help remote work
become more efficient, but they can also result in wage theft and diminished
autonomy in the workplace.
Whilst there are new Centres and Institutes emerging around the world to advance ethical data-driven AI and data governance, the ADM+S Centre tackles these challenges at an unprecedented scale of cross-disciplinary and cross-institutional collaboration.
The Data research program brings together data science with social science to find responsible, ethical and inclusive ways of constructing, sharing and using data to solve problems and automate decision-making systems; and uses critical data studies approaches to critically examine the data logics, infrastructures and flows that sit behind ADM systems.
This group will deploy new digital tools and methods to improve awareness of data-related issues and involve the public in research, as well as working closely with our partners to collaboratively develop and embed responsible, inclusive and ethical data practices in industry, government and community settings, leading to more effective automated decision-making with fairer outcomes.
RESEARCH PROJECTS
This project maps a range of informal automated activities that proliferate within automated systems across various empirical domains, such as click farming, CAPTCHA hacking, phone farming, dropshipping, OTP scams, fraudulent loan apps, and free jacking.
This project investigates the extent to which automated decision-making systems impact the provision of consumer insurance via pricing algorithms which may produce unfair outcomes for particular subsets of society by engaging in proxy and price discrimination.
Examining the ways in which automated decision-making systems impact public and shared space via sensors that produce actionable digital simulations, artefacts, and interfaces.
Working with Brimbank City Council and a wider reference group, the project team will co-design a robust AI governance strategy to guide the policies and practices for the development and deployment of AI systems.
Assessing prospective harms vs prospective benefits associated with ADM as a first step to amelioration.
The project will provide non-profit CEOs, managers, practitioners and board members with feasible strategies for getting into data analytics or assessing and building their organisation’s data capability.
Examining the political economy of ‘sex tech’ in order to identify how sexual technologies are being governed at scale, how sexual data is being collected, stored, shared and monetised, and how the material benefits of sex tech may be more equitably distributed.
Indentifying how misunderstandings of harm and safety flow into flawed data logics and ineffective automated digital platform responses.
Creating a replicable framework for building capacity (expertise, literacy, data partnerships and data governance) to unlock the social value and impact of advanced data analytics, AI and ADM across the not-for-profit sector.
This project brings together expertise in digital media, platform studies, and law with data science and machine learning to study the roles and data operations of bots – pre-programmed automated agents – on social media platforms.
Recent developments in machine learning and information access communities attempt to define fairness-aware metrics to incorporate into these frameworks. This project will address a number of research questions related to quantifying and measuring bias and engagement that remain unexplored.
Considering ethical approaches in the area of automated decision-making (ADM) and civic life with a focus on civic commitments and concerns.
Operationalising new data partnerships and implementing data analysis to improve non-profit and humanitarian sector work.
Exploring the role of everyday data practices and literacies in automated decision-making.
Examining common themes with respect to the issues raised by the collection, storage, and use of data for ADM across object domains.
Considering ethical approaches in the area of automated decision-making (ADM) and civic life with a focus on civic commitments and concerns.
How might platform regulators and moderators better distinguish between education and information content, and other forms of sexual texts and imagery on social media platforms?
Creating a replicable framework for building capacity (expertise, literacy, data partnerships and data governance) to unlock the social value and impact of advanced data analytics, AI and ADM across the not-for-profit sector.
Providing strategies to address the potential harms posed by ‘dark ads’ and provide accountability and transparency mechanisms for targeted advertising.
Considering ethical approaches in the area of automated decision-making (ADM) and civic life with a focus on civic commitments and concerns.
This research aims to assess the extent to which search results are personalised, by various leading search engines and their algorithms, based on the profiles established by those search engines for their different users.