By Sabrina Ouyang
Recent developments in machine learning (ML) and artificial intelligence (AI), including in particular the launch of the AI-driven chatbot ChatGPT in November 2022, have spurred discussions on the potential advantages and threats of AI. AI, described succinctly by IBM as “a field, which combines computer science and robust datasets, to enable problem-solving”, offers newfound solutions to persistent legal problems. As AI becomes increasingly nuanced and sophisticated, disputes regarding its application in the human rights field, and in particular for the eradication of modern slavery, have surfaced. Most notably, advocates propose that the combination of AI and big data creates a new window through which we can view exploitative practices that permeate global supply chains. While present accounts on the use of AI in the human rights field often present divided views, this post focuses on the upsides: the potential and demonstrated applications of AI in combatting modern slavery.
Modern slavery is a global crisis, threatening the liberty and wellbeing of victims while jeopardizing the sustainability of the supply chains in which it is embedded. According to the International Labour Organization (ILO), an estimated 50 million people live in modern slavery as of 2022. Despite its pervasive nature, modern slavery is critically underdetected. Businesses and governments alike have the responsibility to understand the identifiers of modern slavery and implement the necessary mechanisms to eliminate forced labour practices and support the rehabilitation of survivors. In response to this ongoing humanitarian crisis, the Canadian government has taken steps towards the elimination of modern slavery, including the proposal of Bill S-211, “An Act to enact the Fighting Against Forced Labour in Supply Chains Act and to amend the Customs Tariff”, the merits of which have been covered previously by Letty Condon on this blog. In spite of the legislation’s aim to increase corporate accountability, the limited capacity of companies to properly identify modern slavery in their supply chains will nonetheless lead to unfulfilled promises on Canada’s part to effectively combat modern slavery. In this regard, tech resources such as AI can helpfully assist Canada in meeting the Sustainable Development Goal target to eradicate forced labour and end modern slavery by 2025.
This photo by Steven Depolo is licensed under CC BY 2.0.
Present discussions surrounding the integration of AI into the battle against modern slavery focus heavily on its function in improving due diligence processes in corporate supply chains. Specifically, the use of machine learning and natural language processing, in conjunction with extensive data analysis, has been identified as crucial for enhancing the audits of global supply chains. For example, Project AIMS (Artificial Intelligence Against Modern Slavery) embraces the use of ML and AI to tackle reporting issues and improve accountability. The project uses natural language processing (NLP) and computational linguistics to analyze reports made by companies detailing their actions to eradicate modern slavery. Furthermore, proposals for the use of blockchain technology in employee onboarding offer methods that conceivably preserve the autonomy of vulnerable workers and prevent the use of child labour. For example, using a blockchain-based digital identity, companies are able to authenticate the identities of employees and utilize image analytics to prohibit the onboarding of children.
Likewise, in 2021, FRDM (Forced Labour Risk Determination and Mitigation), an American supply chain risk management software, announced a partnership with the Canadian Border Services Agency (CBSA). The collaboration aims to bolster the CBSA’s ability to identify and intercept the importation of products of forced labour, using AI and ML-powered big data analytics tools to comb through online information and measure sourcing probabilities. The potential of FRDM technology in identifying and quantifying risks of human trafficking in supply chains has also been acknowledged in strategic discussions held by the UN Working Group on Trafficking in Persons.
Modern slavery is often perpetuated through inconspicuous means. Identification of victims, often at state borders, is a key piece in the campaign against human trafficking and modern slavery. AI has the potential to assist in not only the identification of victims but also in the process of recovery and reintegration of survivors into their communities. Current applications in this area include leveraging ML and NLP to map the recovery journeys of survivors and identify key points where particular services could have the greatest impact. While the complex nature of AI technology necessitates caution in its application, human rights advocates should strive to harness the power of AI technology for a better world void of forced labour.
About the author: Sabrina Ouyang is a second-year student at the Peter A. Allard School of Law and is working with the IJHR Clinic as part of the All-Party Parliamentary Group to End Modern Slavery team.
