Code 8.7 Symposium: Using Tech-Driven Data to Address Child Labour
The United Nations declared 2021 the International Year for the Elimination of Child Labour, a year that was to be critical to the achievement of SDG Target 8.7 and the goal of ending child labour by 2025. As a member of the Organizing Committee for Code 8.7, Delta 8.7 convenes this Symposium to explore how the employment of AI, machine learning, computational science and other frontier technologies can address child labour. Researchers from three Code 8.7 member organizations — HACE: Data Changing Child Labour; the Ministry of Labour and Social Security of Brazil; and the Centre for Data Science, School of Mathematical Sciences at Queensland University of Technology (QUT) — explored the challenges and opportunities available through data and novel technologies to increase knowledge of prevalence and analyse efficacy of measures taken to end child labour.
Representing HACE, Elizabeth Burroughs, Anahad Kaur Khangura and Eleanor Harry examine the complexities of the data itself: to create accurate modelling and analyses of child labour, frontier technologies require accurate and standardized data. Using data collected in Bangladesh as an example, they illustrate the first challenge faced by researchers: of creating comparable data from different sources for accurate and consistent analysis. Disconnects in data within and between national sources and international measurements and standards can be found in how age categories are grouped, how activities were defined over time and variations in regional grouping. These inconsistencies present a challenge for developing rigorous analysis of how the prevalence and nature of child labour is changing over time, as (for example) during the COVID-19 pandemic.
In the leadup to 2021, stakeholders were invited to make a pledge as part of the International Year for the Elimination of Child Labour. In response, the Labour Inspection Subsecretariat of Brazil (SIT) entered a pledge titled “Aprimorar e fortalecer a Inspeção do Trabalho Brasileira no Combate ao Trabalho Infantil” (“Enhancing and Strengthening the Brazilian Labour Inspection to Combat Child Labour”). Luiza Carvalho Fachin and Roberto Padilha Guimarães from the Brazilian Ministry of Labour and Social Security discuss how action was taken in 2021 to achieve this goal, specifically focusing on the development of an innovative online platform to analyse, classify and manage reports of child labour.
Prior to becoming a PhD Candidate at the Centre for Data Science, School of Mathematical Sciences at Queensland University of Technology (QUT), Adriana Bora worked with The Future Society and Walk Free to develop Project AIMS (Artificial Intelligence Against Modern Slavery). In her contribution to the Symposium, she considers the challenge of analysing and learning from the thousands of modern slavery statements emerging from companies subject to reporting under the United Kingdom and Australian Modern Slavery Acts. Project AIMS uses technologies including natural language processing to read and analyse modern slavery statements. The project demonstrates the capacity for frontier technology to sort through and assess public information at the rate necessary to inform policy and consumer decisions. As Bora’s article proposes, such insights can also support the private sector by offering the opportunity to strengthen response to child labour within supply chains and increase their business sustainability as a result.
Emerging from the International Year for the Elimination of Child Labour, it is clear there are significant challenges to achieving SGD Target 8.7 goal of ending child labour by 2025. The rate of child labour was already increasing prior to the pandemic and is projected to rise further as a result of economic and social shocks. The articles contributed to this Symposium clearly demonstrate how the use of innovative technology can support stakeholders across sectors to take meaningful and effective action to accelerate progress in this critical period.
All of the contributions to the Symposium can be found below:
The Importance of Standardized Child Labour Data to Machine Learning and AI
Elizabeth Burroughs, Anahad Kaur Khangura, and Eleanor Harry, HACE
2 March 2022
Ipê Trabalho Infantil (Ipê Child Labour) System
Luiza Carvalho Fachin, Roberto Padilha Guimarães, Ministry of Labour and Social Security of Brazil
3 March 2022
What Are Companies Doing? Using Data to Analyse Corporate Statements on Child Labour in Supply Chains
Adriana Bora, Centre for Data Science, School of Mathematical Sciences at Queensland University of Technology (QUT)
4 March 2022
All these contributions culminated in a virtual panel held on 7 March 2022. The full recording of this event can be found below:
Delta 8.7 symposia offer experts the opportunity to discuss technical details of their research and receive commentary from the wider research and anti-slavery community. Researchers are then able to give a response to the previous commentaries received. We hope these symposia will spark further conversations and build the dialogue around research and data in the fight to eradicate forced labour, modern slavery, human trafficking and child labour.
Previous symposia can be found below: