LAUSR

In the last two decades, human trafficking (where individuals are forcibly exploited for the profits of another) has seen increased attention from the artificial intelligence (AI) community. Clear focus on the ethical risks of this research is critical given that those risks are disproportionately born by already vulnerable populations. To understand and subsequently address these risks, we conducted a systematic literature review of computing research leveraging AI to combat human trafficking and apply a framework using principles from international human rights law to categorize ethical risks. This paper uncovers a number of ethical tensions including bias endemic in datasets, privacy risks stemming from data collection and reporting, and issues concerning potential misuse. We conclude by highlighting four suggestions for future research: broader use of participatory design; engaging with other forms of trafficking; developing best practices for harm prevention; and including transparent ethics disclosures in research. We find that there are significant gaps in what aspects of human trafficking researchers have focused on. Most research to date focuses on aiding criminal investigations in cases of sex trafficking, but more work is needed to support other anti-trafficking activities like supporting survivors, adequately address labor trafficking, and support more diverse survivor populations including transgender and nonbinary individuals.