Force labor, as defined by the Department of Homeland Security, "occurs when individuals are compelled against their will to provide work or service through the use of force, fraud, or coercion.” 

It's a global problem that involves 27 million people who are in this situation. 

And it's a business problem in that annual profits from forced labor are $236 billion globally. This is according to a recent survey, The Emergence of Artificial Intelligence to Address Forced Labor in Global Supply Chains, produced by The Dynamic Sustainability Lab at Syracuse University in Partnership With Thomson Reuters.

The top five at-risk imports to be produced with forced labor are:

• Electronics
• Garments
• Palm oil
• Solar panels
• Textiles

There is movement to address this issue from businesses that are adopting measures to increase supply chain visibility. Governments are doing the same and consumers, in the form of Gen Z, are adding pressure. This generation of consumers "care deeply about the life cycle of products and are willing to pay more for cleaner products," according to the report. 

AI Can Help Mitigate Forced Labor

While companies have made progress in identifying suppliers using forced labor, there are still blind spots when companies move beyond Tier 1 suppliers. 

Companies are currently using three basic approaches for identification:

Social Audits – Third-party factory inspections checking conditions, wages, and worker treatment.
Codes of Conduct – Labor standards written into supplier contracts before any business is done.
Traceability Programs – Systems that track materials and products through the supply chain. 

However, the survey found that manual surveys reach only about 10% of suppliers beyond Tier 1. And it's below that level that forced labor risks lives.

Using AI can help get past Tier 1. The report notes two examples:

Web Scraping with Natural Language Processing (NLP) can extract supply chain maps from online sources.

Graph Neural Networks (GNNs) can predict supplier relationships with areas of high risk.

The report also discusses the advantages that blockchain technology has for traceability.

Key Capabilities:
• Creates an immutable ledger of all events throughout supply chains.
• Enables tracking and verification from raw materials to final product.

Significant Challenges
• Immutability creates risks if initial information entered is inaccurate or fraudulent.

• Verification and proper technological access and skill needed for all participants in a supply chain.

While AI has potential, not many supply chains are using it to detect forced labor. A study included in the survey found that just 1% of those using AI for supply chain management used it for that purpose. 

In an article discussing the report, Thomson Reuters noted that the research points to a clear set of actions, including:

• A global data partnership against forced labor must be formed in which organizations compete not on proprietary data, but on their ability to intervene.
• Multistakeholder working groups should establish common standards for AI training data and transparency requirements.
• Human oversight must be embedded at every level of AI implementation; no algorithm should make consequential decisions about labor risk without human judgment in the loop.
• Investment in AI training for corporate workforces, supplier networks, and government agencies alike cannot wait.