Fighting Human Trafficking (#4) – Traffik Analysis Hub (TA Hub)

Overview

The Traffik Analysis Hub (TA Hub) provides empirical information to a wide variety of stakeholders involved in combatting human trafficking. Instead of relying on estimates, those stakeholders can then use data-driven intelligence to perform their respective functions more effectively. The TA Hub has been reviewed by a diverse group of members across the Kalinga Fellowship, with extensive support from John McGrath from the TA Hub team.

According to its website, the TA Hub is “a partnership across industries and sectors including financial institutions, NGOs, law enforcement and government agencies; all unified by the common goal of sharing data to stop human trafficking”.

In the context of the findings listed in the full report (available from Jambuzi on request), the Fellowship deems the solution to be a valid and powerful tool, which delivers the core capabilities required. No other solution has been identified which compares to the strengths of the TA Hub in this respect.

Phased approach

To address the challenges highlighted, it is recommended that the approach be divided into three clear phases. There are technical dependencies between the phases, but some of the preparation could happen concurrently.

• Phase 1: Open system – Traffik Analysis Hub (TA Hub)

• Phase 2: Closed system – Workbench

• Phase 3: Predictive analytics and forecasting

Outcomes

Phase 1

The first phase will deliver powerful analytics via the TA Hub, shared across all stakeholders. It will:

• Provide NGOs and police with visibility of emerging trends within their local areas, together with clear indicators for patterns connecting neighbouring areas and beyond, so that collaborative initiatives can be planned and executed effectively.

• Present rich content to central government and state governments to support a cycle of evidence-based business cases for legislation and policy, and the measurement of results.

• Provide financial services institutions with a means to identify and eliminate money laundering associated to human trafficking.

• Provide corporations with analytics to identify and eliminate the inadvertent funding of exploitative trafficking within their workforce and supply chains.

This first phase is suited to cloud-based hosting and data sharing through collaborative partnerships across industries and sectors. This phase focusses on the TA Hub.

Phase 2

The second phase will:

• Allow interested organisations to augment the data with their own datasets.

• Provide their users with a deeper analysis of the augmented data to support more advanced capabilities. For example, it will help identify individual people, to whom they’re connected, in which organisations they’re involved, and how the money is flowing from one organisation to another.

Due to the likely inclusion of personally identifiable information, this second phase is not suited to collaborative data sharing or public cloud-hosting. Instead, this phase will see the TA Hub technology platform move to being hosted within interested partners’ own IT environment on their own premises. This second phase will also involve the TA Hub team training the partners in using the vast analytical capabilities of the platform in conjunction with their own datasets. It will unleash a much more advanced use of the AI and will be incredibly powerful. This second phase is referred to as the ‘Workbench’.

Phase 3

A third phase will encompass longer-term objectives to:

• Provide reliable time series projections and predictive analytics to accurately show stakeholders the likely future patterns and trends.

• Increase analytical automation to free-up human resources from performing low level analytical processes, so that they can focus on other aspects of the operation.

This third phase requires the community to be in place and collaborating, the data to be scaled, and the analytical development to have advanced. Eventually, using machine learning, the AI will be able to perform the task of forecasting and predicting human trafficking activity more quickly, more accurately, and in a more scalable and reliable way than manual techniques.

Open system (TA Hub) versus closed system (Workbench)

Open system (TA Hub): overcoming data privacy concerns (phase 1)

Where a primary objective is to provide shared visibility on so many fronts, a key challenge is that such a data sharing platform should never receive, store or process any personally identifiable information. Firstly, it doesn’t need to. Secondly, if it did receive, store or process personally identifiable information, it could impede the implementation of the solution through personal data concerns and privacy issues. A solution, free from personally identifiable information and suited to collaborative data sharing will, from here on in, be referred to as an open system. The TA Hub, in its current form, is an open system.

Closed system (Workbench): deeper investigative analysis (phase 2)

There are, however, clear requirements from some stakeholders to use an anti-human trafficking platform in conjunction with personally identifiable information; e.g. to provide deeper analysis of investigative data. For example, police investigations would want to use the power of the platform to find out who the people are, to whom they’re connected, in what organisations they’re involved, and how the money is flowing from one organisation to another. A different solution is required to meet these challenges; it would not be suited to collaborative data sharing, and each implementation of such a solution would be aimed at one specific organisation. This solution, handling personally identifiable information and unsuited to collaborative data sharing will, from here on in, be referred to as a closed system. A different version of the existing TA Hub will be moved from the cloud hosting environment into a partner’s own IT hosting premises within their own IT environment, where it can be augmented with their own datasets from their own / third-party IT systems. This version of the TA Hub will be called the ‘Workbench’ and is a closed system.

People

John McGrath and his ‘Tech for Good’ team developed the TA Hub platform. They are based in Dublin, Ireland. In addition to John, the team comprises 3 other engineers.

John is a Senior Solution Architect at IBM. Although the ‘Tech for Good’ projects are initially supported financially and technically by IBM, the TA Hub team is now an independent NGO. IBM’s intention is for all ‘Tech for Good’ projects to achieve a position of financial self-sustainability.

Previously, in IBM’s capacity for corporate social responsibility (CSR), John has delivered IBM grants to NGOs for specific problems, such as in the Philippines during Typhoon Haiyan and with the Red Cross during the Ebola crisis.

Rumi Mitra also attended the Kalinga Fellowship, and is Head of Corporate Citizenship at IBM India. She specializes in Information and Communication Technology for Development (ICT4D) and is focused on business responsibility and corporate social responsibility, skills and employability, diversity and inclusion, and urban planning and development.