Decentering ADM: A Review of Automated Decision-Making in the Global South

PROJECT SUMMARY

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Decentering ADM: A Review of Automated Decision-Making in the Global South

Focus Areas: News and Media, Transport and Mobility, Health, and Social Services
Research Program: People
Status: Active

The Decentering Automated Decision-Making report offers a framework for studying automated decision-making technologies and their social effects that challenges and subverts this framing of ADM as spreading from the West. This is the centre that we aim to destabilize and displace by offering accounts of how ADM is being done otherwise. Here we do not limit ourselves to redemptive stories of emancipatory projects involving ADM, although readers may find elements of this. Rather we aim both to challenge dominant narratives of unidirectional flows of algorithmic power while also demonstrating what accounts that do not presume such dynamics might look like.

To do this we focus on parts of the world that are often left out of global narratives of ADM by bringing together academic and grey literature, online resources and interviews with key stakeholders in underrepresented regions (Africa, Caribbean, China, Latin America, Pacific Islands, South and Southeast Asia). We frame this as contributing to the Centre of Excellence as contributing to this broader project of decentering who, where, and how engagement with automated decision-making takes place. prioritise places and contexts in the world that were less visible in the field to demonstrate the diversity of ways in which ADM was being imagined, anticipated or practiced in different parts of the world.

PUBLICATIONS

5G and the digital imagination: Pacific Islands perspectives from Fiji and Papua New Guinea, 2023

Horst, H., Foster, R.

Journal article

Framing Fashion: Human-machine learning and the Amazon Echo Look, 2022

Horst, H., Mohammid, S.

Book chapter

Looking professional: How women decide what to wear with and through automated technologies. 2021

Horst, H., et al.

Journal article

RESEARCHERS

ADM+S Chief Investigator Heather Horst

Prof Heather Horst

Lead Investigator

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PARTNERS

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Australian Red Cross

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The Australian Search Experience

PROJECT SUMMARY

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The Australian Search Experience

Focus Area: News and Media
Research Program: Data
Status: Active

There is a lot of speculation about the impact that search engines have on the information we encounter. Search engine personalisation may be influencing individuals’ search results, and thereby shape what they know of the world. This may affect their personal decisions, and our collective decisions as a society – from how we spend our money or who we vote for to our attitudes on critical issues such as the safety of COVID-19 vaccines.

This research examines 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. It compiles and analyses the search recommendations encountered by a wide range of genuine users across prominent digital media platforms, for a variety of generic and specific topics, and over time.

The project launched in late July 2021 and over 12 months collected over 350 million search results from more than 1,000 participants. The project took a citizen science approach, relying on data donations from the general public made through a unique desktop browser plugin. ADM+S researchers have been analysing the data to understand the personalisation of search results for critical news and information, across key platforms including Google and YouTube, based on the profiles these platforms establish for their different users.

CASE STUDIES

Case Study: Google News
This project is examining Google News results to understand how recommender systems and search personalisation intersect with news distribution. Preliminary findings show limited evidence of personalisation, with news and information sources recommended for particular searches mainly influenced by the search topic. The team is now exploring the diversity of news outlets in the dataset, with the goal of finding out how much local and national news is featured in Google News results. The project will also reveal whether particular news outlets appear more often than others.

Case Study: Comparing search results across Google platforms/services
This project examines search results across Google News, Google Search, Google videos, and YouTube to understand how different Google services and platforms operationalise ‘authoritativeness’ across socio-cultural issues and over time. The project focuses on the sources that are ranked at the top on each service/platforms and reflects on issues of media diversity in relation to these results.

PUBLIC RESOURCES

Person typing on laptop keyboard with search bar in foreground

Open Source Software: The Australian Search Experience: Background Paper

Target audience: Researchers, Software Developers
Content type: HTML

View on Github

PUBLICATIONS

The Australian Search Experience: Background Paper

15 Jan 2022

Read on APO

RESEARCHERS

Axel Bruns, Chief Investigator with the ADM+S Centre

Prof Axel Bruns

Lead Investigator, QUT

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Mark Andrejevic

Prof Mark Andrejevic

Chief Investigator, Monash University

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator, QUT

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ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator, QUT

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Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator, University of Sydney

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Daniel Angus

Prof Daniel Angus

Associate Investigator, QUT

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ADM+S Investigator Timothy Graham

Dr Timothy Graham

Associate Investigator, QUT

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Dr Ariadna Matamoros-Fernández

Associate Investigator, QUT

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James Meese

Assoc Prof James Meese

Associate Investigator, RMIT University

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ADM+S Chief Investigator Falk Scholer

Prof Falk Scholer

Associate Investigator, RMIT University

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ADM+S Investigator Damiano Spina

Dr Damiano Spina

Associate Investigator, RMIT University

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Louisa Bartolo

PhD Student,
QUT

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Ehsan Dehghan

Dr Ehsan Dehghan

Affiliate,
QUT

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PARTNERS

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AlgorithmWatch
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University of Twente

University of Twente

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