What Are Companies Doing? Using Data to Analyse Corporate Statements on Child Labour in Supply Chains

4 March 2022
Research Innovation

Adriana Eufrosina Bora  | PhD Candidate at the Centre for Data Science, School of Mathematical Sciences at Queensland University of Technology (QUT)

It is estimated that almost one in ten children worldwide, a total of over 160 million children, are in child labour globally. Over half of them are younger than 11 years old and working in hazardous conditions. Due to the COVID-19 pandemic, the United Nations predicts another 9 million children to be in this situation by the end of this year.

These shocking statistics and the recent crisis highlight the responsibility of both governments and companies to apply laws, implement due diligence and create transparency on the measures they are taking to eliminate and prevent child labour from supply chains.

For companies, addressing the issue of child labour in supply chains is not only an obligation but also an opportunity, as it can strengthen their response to the COVID-19 crisis as well as their business sustainability more broadly. To do so, companies should complement their immediate response to the short-term incidents with “longer-term, systemic responses that make global supply chains more resilient, ethical and sustainable, and, concomitantly, more impervious to child labour and other human rights violations in future crises.”

External actors such as governments, investors, consumers and even competitors in the same industry have been pressuring companies to track and report their progress. As a result, there has been a rise in mandatory requirements and voluntary disclosure concerning human rights and supply chain due diligence in recent years.

Globally, legislations are being passed requiring companies to respond to human rights abuses in their supply chains. Some legislations include transparency clauses asking companies to publish statements highlighting the steps they are taking in this regard.

For example, the introduction of the first national legal framework for combatting modern slavery, the 2015 Modern Slavery Act (MSA) in the UK, has been a helpful step toward supply chain transparency. It requires companies making over £36 million per annum to report on the actions they are taking to eradicate modern slavery from their operations and supply chains. As a result, businesses publish an estimated 16,000 modern slavery statements each year under the UK Act alone.Other countries and jurisdictions are quickly following suit with their own modern slavery-targeted legislation, causing a drastic increase in the number of corporate statements published each year.

Documenting the impact of new legislative acts is an indispensable tool for improving the effectiveness of these legislations and advancing business practice. As transparency in supply chains is gaining momentum, in recent years there has been a push for more third-party sustainability and due diligence indices and benchmarks that seek to analyse what companies are reporting and measure their performance vis-à-vis their supply chains due diligence obligation.

While indices have traditionally been focused on corporate social responsibility, there has been a shift towards human rights due diligence benchmarks, such as KnowTheChain, Fashion Revolution, the Corporate Human Rights Benchmark and the UK Modern Slavery Act Research Project.

While the publication of corporate statements has provided external parties a greater capacity to hold businesses accountable, it has presented a new challenge: external parties cannot comprehensively assess the large and increasing volume of statements.

The current analysis of the statements, done manually, is resource-intensive. It takes approximately one hour per statement, and even the most comprehensive benchmark, the UK Modern Slavery Act Research Project run by Walk Free and WikiRate, has been able to analyse only approximately 2,400 statements to date. This process leaves thousands of statements unanalysed and governments unable to assess actual levels of compliance. Thus, automating the process is the only way to achieve accountability at scale.

Project AIMS (AI against Modern Slavery) is a first attempt to answer this question. Project AIMS is an open-source solution that strives to build towards achieving accountability at scale by using data science and Artificial Intelligence (AI) methods such as Natural Language Processing (NLP) to analyse all the available statements. It builds initial explorations of machine-learning solutions designed to benchmark the UK MSA statements. All the data and the code developed so far are publicly available on the GitHub repository.

Yet, as presented in Table 1,out of the hundreds of legislations, initiatives and reference materials listed on the latest “Compendium of relevant reference materials and resources on ethical sourcing and prevention of trafficking in human beings for labour exploitation in supply chains,” only a handful are asking companies to particularly address the issue of child labour in their supply chains.

The leading model, however, is the Dutch Child Labour Due Diligence Law. This legislation requires Dutch companies or companies that sell products on the Dutch market to exercise due diligence, examine whether child labour occurs in their supply chain and develop and publish their action plan. The companies’ statements will be recorded in a public register yet-to-be designated. Nevertheless, a new legislation was recently proposed to replace the Child Labour Due Diligence Act that was adopted by the Dutch Parliament in 2019 but has not entered into force yet, the Dutch Bill for Responsible and Sustainable International Business Conduct. Regardless of which legislation will come into effect, and companies start publishing their statements on the publicly available registry, similar data science and AI methods as those explored in Project AIMS can be outlined and adopted to systematically monitor companies progress towards eradicating child labour in the supply chains.

Yet, considering the urgent need to address child labour, until then, solutions can be re-designed to extract the most information possible what companies are already doing against child labour, from existing data sources, such as the UK and Australian statements as illustrated in the case study on Project AIMS’s GitHub, accessible here

Given the increased vulnerability and the expected rise in cases of child labour, new tools are needed to increase the impact and effectiveness of legislations and end child labour in all its forms by 2025. Collaborations between the legislators and the technology providers are key to accelerate progress and build accountability at scale.

This article has been prepared by Adriana Bora as a contribution to Delta 8.7. As provided for in the Terms and Conditions of Use of Delta 8.7, the opinions expressed in this article are those of the author and do not necessarily reflect those of UNU or its partners.

This piece has been prepared as part of the Code 8.7 Virtual Symposium: Using Tech-Assisted Data to Identify and Address Child Labour symposium. Read all the responses below:

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