Code 8.7: Using ICT to Find Hidden Populations
The modern anti-slavery movement began in the late 1990s and slowly achieved policy acceptance, contributing to the refinement of legal definitions and opening the door to numerous activist groups that were largely unguided by research. The unsophisticated analyses used during the growth of this movement over the past 15 years did little to achieve the goal of ending slavery.
Today, evidence-led groups are coming to the fore as the global community works towards Target 8.7. The Code 8.7 conference took up the question of what computational science and artificial intelligence can contribute to the delivery of those “effective measures”.
At the ICT hothouse, speakers Shannon Stewart from GFEMS, Sam Blazek from IST Research and Hannah Thinyane from UNU-CS introduced a range of stand-alone and interconnected methods, including network scale-up, longitudinal migration tracking, predictive modelling, dark web analysis and survivor-deployed apps. These technologies can be used to advance fast prevalence estimation, tackle slavery in apparel supply chains, disrupt trafficking networks and enhance the agency of survivors.
From left to right: Hannah Thinyane (UNU-CS), Shannon Stewart (Global Fund to End Modern Slavery), Sam Blazek (IST Research).
Across this hothouse discussion three big challenges emerged that also contained opportunities. The first was how technology can keep up with perpetrators, who tend to adapt their approaches in response to new technological innovations on the part of NGOs and law enforcement. Speakers and attendees offered the solutions of providing data directly to end users who can then help refresh and nuance the data to form a feedback loop. Ideas included staying ahead of constantly changing data patterns by designing a series of tools that allow regular updates from the outset (for example, adding or removing questions and languages); committing to the need for constant maintenance of AI tools, including in the underlying funding for projects; and engaging in a constant process of forecasting where we predict tools that traffickers may pick up in the future.
The second was how to use technology in ways that reach everyone, or at least more communities and populations than are included in the obvious social media platforms. Speakers and discussants observed that although more and more people have mobile phones, they remain in a fragmented global digital community, where not everyone is part of the same networks. Tech-based anti-slavery solutions therefore face the challenge of accessing diverse populations, and NGOs may make presumptions based on that limited reach. The discussion concluded that we need to access people in ways that reflect their networks and realities, and to achieve this we must work harder to understand the motivations and contexts of front-line responders, constantly surveying the possibilities and limitations of their approaches to technology use.
The third major challenge that emerged from the ICT hothouse was the presence of “unknown unknowns”. These trouble the tech and anti-slavery communities alike, because both communities are aware of the sheer number of known unknowns—for example how to reach women or linguistic minorities effectively with anti-slavery programmes or new technologies. Because we confront so many known unknowns, we know there is likely a daunting number of unknown unknowns. Speakers and participants pointed in response to the promising approach of collecting and indexing open data to piece together intelligence. By mining large collections of public data and indexing indicators, where anti-slavery actors would otherwise not see patterns and structure, we might at least identify more of our unknown unknowns.
Ultimately, this hothouse, like the wider Code 8.7 event itself, asked the question: can a science of anti-slavery help to achieve a better anti-slavery movement? One that can design a pathway to a slavery-free world by 2030 because it has catalysed accurate mapping and measurement and brought a deep understanding of slavery’s nature and drivers? One that knows what slavery is, where it takes place, how many people it affects, how it takes root and persists and what works to end it?
But this hothouse, like all the Code 8.7 hothouses and discussions, also recognized that at the heart of a scientific anti-slavery movement there must be a human-machine fusion: the development of new scientific, data and technological approaches for measuring, mapping and analysing slavery, but around the voices, ideas and human agency of some of the world’s most vulnerable people. Particularly during the discussion of survivor-informed apps and how vulnerable communities can use technology to support their empowerment, agency and dignity, the ICT hothouse discussion recognized that a science of anti-slavery should revolve around “rigorous morality”.
This term, formulated by Code 8.7 participant and Rights Lab Executive Director Professor Todd Landman, describes “a turn away from any notion that social scientific research has to be (or can be) value free” and an attempt, instead, to draw on “a deep tradition of empirical work that seeks to make social (and political) science matter.” Rigorous morality means championing problem-based research that remains systematic while producing outputs that are of public value. For Code 8.7 participants as they take forward the lessons of the conference into a longer-term collaboration, this means seeking a research approach that is as much about humanity as it is about technology: delivering anti-slavery “effective measures” that are designed around cutting-edge methods and the agency of survivors.
Zoe Trodd is Director of the Rights Lab at the University of Nottingham.
This article has been prepared by Zoe Trodd as a contributor to Delta 8.7. As provided for in the Terms and Conditions of Use of Delta 8.7, the opinions expressed in this article are those of the author and do not necessarily reflect those of UNU or its partners.