• The 'digital divide' disproportionately affects groups like LGBTI people, those with disabilities and forced migrants.

• Data exclusion can slow down advocacy efforts for these groups.

• Their marginalization and invisibility is detrimental to societies and economies.

On any given day, we’re saturated with technology that also gathers critical information on our locations, actions and intentions – big data is omnipresent. Traditionally, we have been surrounded by diagnostics, opinion polls and censuses, all to benchmark our collective needs, wants and outcomes, so that state and non-state actors can better know us. In a time like none other, we’re attuned to the myriad of ways that we collect data on each other, and expect that they inform better systems. The era of data, an age of analytics, is here.

And it’s leaving people behind.

As the World Bank’s 2016 World Development Report reiterates, online technologies still remain inaccessible or unaffordable to many populations around the world, often with a clear “digital” divide along gender, age, area, and income lines. I’d like to focus on three specific groups: lesbian, gay, bisexual, transgender and intersex (LGBTI) people; persons with disabilities; and forced migrants. These are groups who paradoxically experience significant stigma through the gaze of the mainstream (hyper-visible) and who are also excluded from this era of data (invisible).

I examine these groups to call attention to significant quantitative data gaps and how all stakeholders can consider a more thoughtful approach to knowledge and interventions. This post cannot give definitive solutions, yet I hope it calls attention to why we should advance.

The invisible/hyper-visible paradox

A social inclusion framework shows us how these groups can be simultaneously one thing and its exact opposite. Around the world, some groups face legal discrimination and stigma, which serves to exclude them from markets, services, spaces and data collection. Regarding the latter, this can result from actively excluding groups from research endeavours, or the failure to ask about the very characteristics that the mainstream stigmatizes (e.g. disability status, gender identity, etc.). For example, basic population estimates often don’t exist for LGBTI people and some forced migrants, allowing some governments to deny their very existence – i.e. rendering them invisible. At the same tie, these groups still exist in a context that often scapegoats or vilifies them, fueling hyper-visibility in the eyes of their societies – hence the paradox. The challenges of stigma-driven hyper-visibility for all three groups can be significant: prison, compulsory surgeries, forced sterilization, the deprivation of autonomy, expulsion from a host country on a whim, violence, labour market discrimination, or poverty cycles, to name a few.

Data is knowledge – knowledge is power

When representations of actual phenomenon (“things”) are brought together and portrayed symbolically in order to understand them, we have “data” ready for analysis. Analyzed data is not a panacea to solve all problems, but rather a way to know the depth of a phenomenon (qualitative) as well as breadth (quantitative). When collected and analyzed with quality and integrity, it guides how we know and operate, and is the basis of knowledge.

LGBTI people, persons with disabilities, and forced migrants are groups who have shown significant resilience – a lack of quantitative data does not equate to powerlessness. Regardless, data has an innate authority that can be the best basis for evidence-based interventions. (For example, see how sex-disaggregation within diagnostics helps combat gender-based violence, or how counting and working with “key populations” can lower HIV transmission rates). Without more quantitative data, there is a real risk of advocacy efforts being sequestered as niche or inconsequential, perhaps even leading toward a plateau of inclusion.

Image: World Bank

Such stagnancy is detrimental to these groups’ well-being as well as society’s. Pioneering research shows that excluding LGBTI people, persons with disabilities, and (in this case) economic migrants can fuel poverty cycles and also significantly limit macroeconomic growth, human development outcomes, the Sustainable Development Goals and private-sector profits. Inversely, inclusion of these groups leads to significant gains in social and economic growth (see here for LGBTI issues, disability issues, and migration), and stronger private sector profits. But to attain more of these goals will require a deeper, more granular understanding of the extent of their challenges and contributions, to fuel evidence-based interventions and policies that work.

Standards and safeguards

In response to overall data needs, the UN released a 2015 report on mobilizing the “data revolution” for sustainable development – calling attention to data quality, integrity, transparency, disaggregation, protection, privacy, governance and other principles. Five years later, companies have only become more effective at capturing and monetizing data, with no clear standards or safeguards in place to promote the aforementioned principles. This UN call to action seems off-target when it places the bulk of responsibility on governments (as duty-bearers) to guide the “revolution”. With the exception of European Union regulations, many of the world’s governments don’t seem as quick to understand or act. For example, the current US Administration excluded LGBT questions from its census as it tried to add questions on “citizenship”, showing a politicization of the census as well as a differential capacity to safeguard various groups.

Regarding socially excluded groups, standards and safeguards are crucial – and we shouldn’t only expect governments to lead this. Rather, civil society, international organizations, the development community, and progressive governmental and corporate representatives should convene to agree upon standards and safeguards, formulated with an understanding of: the incentives of those currently collecting data; differing collection methods (new, traditional, hybrid); data usage; and how to craft mutually beneficial partnerships to safely fill knowledge gaps. Though not easy, this effort can be driven by the axiom that, when counted and actively included, these groups bring tremendous benefits to their communities, societies, businesses and economies.

Mobilising Action for Inclusive Societies

Recent years have witnessed some of the largest protests in human history. People are taking to the streets amid a desire for change, putting pressure on decision-makers for urgent and courageous leadership to find sustainable and inclusive solutions to some of the major challenges ahead of us.

A range of forces are at play. By 2022, some 60% of gross domestic product will be digitized - but current education systems are failing to prepare people for decent work in this future. Based on current trends, it will also take approximately two centuries to close the global economic gender gap. Meanwhile, the world’s richest 1% are on course to control as much as two-thirds of the world’s wealth by 2030.

To tackle these challenges, Mobilising Action for Inclusive Societies is one of the four focus areas at the World Economic Forum's 2019 Sustainable Development Impact summit. A range of sessions will bring stakeholders together to take action that will bolster local entrepreneurship and innovation, while making growth more equitable.

This post can only scratch the surface. As we continue to rely on innovative and traditional data collection, I hope we realize our collective detriment for insufficiently counting people, their challenges, and their contributions. Some new efforts are getting us there – see development approaches to evidenced-based interventions for those impacted by fragility, conflict, and violence. But there remain numerous stakeholders and endeavours that can do more for invisible yet hyper-visible groups. Generating this knowledge will be empowering.