Sustainability systems are positioned to advance human rights protections in specific geographies and commodities through verification and remediation of human rights violations, such as forced and bonded labor. However to ensure impact, detecting those violations is central and often elusive. This report captures project learnings and shares general recommendations for those working to improve FBL detection in different sectors.

A compilation of the lessons learned from four pilot projects in remote auditing from Responsible Jewellery Council, LEAF Marque, Beter Cotton Initiative, and Fairtrade USA. LEAF Marque and the Responsible Jewellery Council looked at the extent to which remote auditing could provide an alternative to in-person on-site visits, while the two other pilot projects used a remote phone survey based on worker voice technology to carry out interviews with workers in factory settings (in the case of Fair Trade USA) and in an agricultural setting on cotton farms (Better Cotton Initiative – BCI).

Report produced for the ISEAL Alliance Innovations Fund project “Integrating new data to improve risk assessments and detection of forced labour vulnerability in agricultural supply chains”.

A Report produced for the ISEAL Alliance Innovations Fund project “Integrating new data to improve risk assessments and detection of forced labour vulnerability in agricultural supply chains”.

The ISEAL-funded research project Integrating new data to improve risk assessments and detection of forced labour in agricultural supply chains (2017 – 18) is an attempt to build the evidence base around monitoring and remediating forced labour in agricultural supply chains.

This case study forms part of the Rainforest Alliance project Use of Risk Maps for Child and Forced Labour in Risk-Based Assurance Processes, supported by the ISEAL Innovations Fund. The project sought to test the prototypes of sectoral risk maps for child labor and forced labor in Kenya, Côte d’Ivoire, and Honduras.

A working paper for the project “New data to detect forced labour in agriculture”.