AI Tools Offer Promise in Combating Modern Slavery in Global Supply Chains

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New research suggests AI-powered language models could transform modern slavery reporting from a perfunctory exercise into a meaningful assessment tool, potentially revolutionizing how companies detect and report forced labor in their supply chains.

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The Endemic Nature of Modern Slavery in Global Supply Chains

Modern slavery remains a pervasive issue in global supply chains, with an estimated 50 million victims worldwide. Of these, 17.3 million are forced to work by private businesses, while nearly 4 million are in forced labor imposed by state authorities 1. The complexity of global supply chains means that businesses and consumers in all sectors face a real risk of unknowingly supporting modern slavery practices.

Current Reporting Challenges

Despite the scale of the problem, the detection and reporting of modern slavery in supply chains by large firms remain low. For instance, a recent analysis by investment company CCLA found that only 30 companies admitted to detecting modern slavery practices in their supply chains 1. This discrepancy between the prevalence of modern slavery and low detection rates raises serious doubts about the effectiveness of current reporting mechanisms.

The Tomato Puree Case Study

A recent BBC analysis of tomato purees sold by UK supermarkets illustrates the complexity of the issue. While several UK supermarkets advertise own-brand tomato puree as "Italian," the report concluded that most UK own-brands likely contain tomatoes grown in China, where picking has been linked to forced labor of Uyghur and other Muslim minorities 2.

The Problem with Current Reporting Practices

Many jurisdictions require companies to report on modern slavery risks in their business and supply chains. In the UK, for example, the Modern Slavery Act requires large companies to publish annual statements on modern slavery and human trafficking 1. However, the quality of reporting often falls short, with companies adopting an "all's fine - nothing to see here" approach due to reputational risks.

Shifting the Paradigm: From Shame to Praise

Experts argue that the reporting focus and responsibility need to be flipped. Instead of shaming companies that detect modern slavery in their supply chains, such disclosures should be seen as evidence of well-functioning due-diligence processes 2. Conversely, "nothing to see here" disclosures should attract more skepticism and scrutiny, especially when the reporting organization's suppliers operate in high-risk sectors and regions.

AI as a Solution: Transforming Reporting Practices

New research using large language models (LLMs) demonstrates how artificial intelligence can help transform modern slavery reporting from a box-ticking exercise into a meaningful assessment tool 1. These AI models can analyze company statements with accuracy resembling human expert evaluation, providing constructive feedback aligned with best practices.

The Path Forward

The combination of better incentives and AI-powered tools could finally make supply chain reporting work as intended. This approach requires a fundamental shift in how corporate behavior is judged, with the detection of modern slavery becoming the norm rather than the exception 2. Companies operating in high-risk sectors must be required to demonstrate concrete detection efforts or provide detailed explanations for finding nothing, ultimately leading to more transparent and ethical global supply chains.

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