How can data be weaponised to target marginalised groups?

How can data be weaponised to target marginalised groups?

How can data be weaponised to target marginalised groups?

Data can portray a false narrative when taken out of context. Its use and abuse can lead to adverse implications for wider society.

Society is increasingly using data to influence policy decisions and people’s lives. Particularly during the pandemic, the UK public has been constantly fed the narrative that the government’s response to the Covid-19 crisis has been guided by the science and data, while our GCSE and A-Level pupils’ futures were directly dictated by data through the algorithm. In numerous ways, data can be a tool for social good: it informs us how society is functioning, and exposes how systemic inequalities manifest in people’s reality through identifying social exclusion and marginalisation. However, data can also be dangerous when paired with prejudices or short-sightedness, in making decisions that further marginalise communities. Data can be weaponised in media narratives, in policies that reinforce systemic inequalities, through presenting misleading data visualisations, or framed to fuel hate-filled agendas. When taken out of context, data can be misinterpreted, misconstrued, and manipulated. So far, this argument appears very abstract; what actually is data? The concept seems unfathomable, given its scale and intangible nature. These examples will illustrate how the uses and abuses of data influence society, and our lives, and why this must be considered when thinking about the use of data today.

The first example refers to the debate over whether public postcode-level testing data of Covid-19 should be published to help get to the ‘root cause’ of any outbreak, through identifying potential outbreaks and responding to them quickly and effectively. However, this data was not published out of fear that certain communities would face discrimination and stigmatisation, further damaging community cohesion, given that publishing detailed data could lead to the identification of individuals or families. The government initially pushed for the data to be published, but, following the concerns from councils, the information was withheld. This fear for marginalised communities comes in the context of a surge in online anti-Muslim hatred during the UK Covid-19 lockdown, and the concern for wider BAME communities given the disproportionate impact of the virus on these communities. Furthermore, this highlights that when the wider implications for society are not considered, the publication of postcode-level data could be weaponised to further hate-fuelled rhetoric.

Secondly, a significant example of the abuse of data is highlighted (on many occasions) by the Trump administration. The case of attempting to add the ‘citizenship question’ to the 2020 US census, which was drafted to ask respondents: “Is this person a citizen of the United States?” The drafted options included: “Yes, born in the United States”; “Yes, born in Puerto Rico, Guam, the U.S. Virgin Islands, or Northern Marianas”; “Yes, born abroad of U.S. citizen parent or parents”; “Yes, U.S. citizen by naturalization”; or “No, not a U.S. citizen”. This was eventually abandoned after it was blocked by the Supreme Court and highlights how serious the implications would have been for US politics if the citizenship question had been adopted. This is due to the fact that census results are used for the distribution of seats in the House of Representatives, are a vital determinant for all levels of governments, and influence the allocation of funding for key social services.  Furthermore, it was feared that including the question in the 2020 census would have resulted in an underrepresentation of noncitizens and minority residents in the national statistics, and has been highlighted as a central strategy to increase Republican power, by excluding noncitizens from the census figures. This agenda highlights how data can be utilised to further discriminate against already marginalised communities.

Data must be used as a tool for social change instead of a weapon of political marginalisation and exclusion. It is crucial that we are educated about the dangers of data manipulation and the potential for published data to be weaponised against marginalised communities. Over three decades ago, JAN Trust was created to support these very minority communities in North London and beyond, by working to strengthen and support these communities we keep women and their children safe. Please see our website to find out more about our work.