Paper short abstract:

This paper analyses the origins of colonialism in econometrics, exploring the history of econometrics, hierarchies in knowledge production, globalisation, and the Big Data era. I argue that to decolonise econometrics we must not only rectify geographical data gaps but address epistemic injustice.

Paper long abstract:

Econometric modelling, the analysis of economic data using statistical techniques, remains a dominant methodology favoured by mainstream economics and related disciplines. While a growing literature has sought to decolonise theories relating to economic development, the literature seeking to decolonise economic data analysis remains sparse. This paper focuses on time series econometrics (TSE) were new methods are devised to analyse (inter)dependence and spillovers between countries, the changing nature of the global economy and the transmission of economic policy. In TSE, a Eurocentric approach prevails. New techniques are designed with advanced economies in mind and evaluated using data from the US and Western Europe. Similarly, a simplistic centre-periphery lens is applied when modelling (inter)dependence between countries. I argue that this has led to datasets, models and analysis which cannot adequately capture developing and emerging economies and their role in the global economy. To unpack the origins and evolution of colonialism in TSE, I draw on postcolonial and decolonial theory and praxis as well as different strands of dependency theory. I consider the history of econometrics, hierarchies in knowledge production, globalisation and the displacement of space by time, and the empirical turn and Big Data era. I conclude that to decolonise data analysis we must go beyond rectifying geographical data gaps and bias. Instead, epistemic injustice underpinning data collection and existing modelling frameworks must be addressed so that new approaches centred on the local context can emerge.

Paper short abstract:

SAGE is a tool to assess equitable governance in conservation areas. This presentation offers learnings from conducting a meta-analysis of SAGE data across 37 sites and discusses the opportunities and risks to advancing justice in conservation through the use of SAGE for upward reporting.

Paper long abstract:

Area-based conservation has been prone to unjust power dynamics and often inequitable outcomes for local people. The new CBD’s Global Biodiversity Framework (GBF), whilst setting the target to drastically expand conserved areas worldwide, also recognises the importance of doing so under more ‘equitable governance’. Accordingly, the GBF guidance encourages its Parties to report against this target by conducting ‘site-level assessments for governance and equity’, SAGE for short. After presenting the findings from a meta-analysis of 37 SAGE assessments conducted in different contexts worldwide, this presentation discusses the opportunities and risks to advancing social justice in conservation through the use of SAGE for upward reporting and the data it provides. Whilst SAGE was in the first place developed to allow site-level actors to come together to collectively recognise and address governance challenges, a meta-analysis of the data sheds light on commonalities and differences of equitable governance across sites and in this way could guide higher-level action to support just processes in conservation. However, shifting the incentive to conduct SAGE assessments as a tool for upward reporting does not only provide an opportunity to upscale a methodology with potential to shape discourse, agendas and decision-making, but brings with it an array of ethical concerns over the motivation, process, data ownership and deployment of results. Beyond bringing our own reflections from working with SAGE and SAGE data, this space seems a unique opportunity to learn from debates on data justice in other domains.

Paper short abstract:

We outline the social justice implications of how remote sensing data could alter the governance of lands targeted for biodiversity conservation. We then discuss the networks and discourses surrounding the use of remote sensing in conservation landscapes in Spain, the UK, Guatemala, and Kenya.

Paper long abstract:

Recent years have seen rapid improvements in the availability and resolution of remote sensing data, together with major advances in the infrastructures and analytical techniques needed to process and interpret these data. But how will these advances shape the governance of lands targeted for conservation, and with what consequences for the wellbeing of those living in conserved lands? We start by presenting four potential answers to these questions, drawing on the digital development and critical data studies literatures to outline scenarios of stasis, socio-environmental synergy, dual disbenefits for people and ecologies, and complex trade-offs. We then present the preliminary results of a scoping review on how remote sensing data are being used in the governance of conservation landscapes in Spain, Guatemala, the UK, and Kenya. We reflect on the discourses surrounding the use of remote sensing technologies and data for conservation in these four socio-political contexts and under which circumstances these emerged. We also discuss the notions of data justice, either explicitly outlined or implicit, within these discourses. Our presentation will highlight some of the important social justice and development implications emerging from increasingly data-driven environmental governance, and discuss the needs and opportunities for interdisciplinary socio-environmental research to address these challenges going forward.

Paper short abstract:

To understand how synthetic data has become the new 'revolutionary' solution to data injustice, I critique how dominant data governance and risk mitigation discourses establishes a narrow definition of 'data risk'. The harm that data governance aims to address may stem from the discourse itself.

Paper long abstract:

In line with the critique of technocratic solutions in development, this paper tackles the emerging innovation of ‘synthetic data’. Synthetic data is AI-generated image or tabular datasets used to substitute real-life data to train machine learning models, now framed as the ‘safe, ethical alternative’ and solving issues of bias and privacy. The promises of synthetic data are contingent upon a particular, narrow definition of ‘data risks’. Data-fication, and now AI, is often criticised for its opacity and exacerbation of pre-existing power imbalances. However, attention to dominant discourses on data governance and reform, both within the private and public sector, illuminates how many recommendations rely on a simplified ethical framework of ‘privacy’ and ‘bias’. This paper looks at how privacy and bias are understood and evaluated for generating synthetic data to demonstrate that the current discourse and best practices may legitimise ‘synthetic data’ as an appropriate mitigation strategy, and the possible implications of this. Ultimately, this study argues that the dominant discourse on data governance and risk mitigation may be enabling technical solutions that potentially replicate and exacerbate existing issues. As such, more rigorous definitions of ‘risk’ should be adopted by mainstream data justice narratives.

Paper short abstract:

Brazil is a crucial player in tackling climate change, and there are recent institutional calls for using remote sensing data in court cases. This study examines the effective use of this data and its role as a boundary object between oversight, investigation, prosecution, and judgment bodies.

Paper long abstract:

The article studies the implications of satellite remote sensing data as a boundary object in monitoring, investigation, prosecution and judgment in Brazil's environmental lawsuits. It is relevant because tackling climate change is urgent and challenging for implementing the Sustainable Development Goals, and Brazil is a crucial player in protecting the Amazon rainforest. The Police, Public Prosecutors and Judges have received recent recommendations from their superior bodies for using remote sensing data in court cases. For this purpose, they count on another tool with daily high-resolution satellite images. Geospatial information systems were among the topics of a public hearing that discussed parameters for quantifying environmental damage from deforestation. However, the effectiveness of this data in court decisions remains unclear. Therefore, the research question is: how effective is the use of remote sensing data for monitoring, investigation, instruction, and judgment in civil and criminal environmental suits? It is qualitative empirical research through exploratory documentary analysis of data available on the web pages of governmental bodies, the contributions to the Public Hearing, the responses to requests for access to information, and a sample of environmental crime cases. In addition to presenting the current stage of adherence to the recommendations, the research contributes by identifying challenges in monitoring the use of this data and assessing its effectiveness in environmental protection. It also proposes a model with the variables that influence the role of remote sensing images as a boundary object between oversight, investigation, prosecution, and judgment.

Paper short abstract:

The paper explores a data justice approach in tracking research influence on policy. It uses data science to assess research influence on open government policies in Latin America. It highlights the data disparities and contributes to work on equitable data landscapes in development.

Paper long abstract:

In the evolving landscape of data-driven development, understanding the impact of research on national and international policy is paramount. This paper delves into the challenging realm of Monitoring, Evaluation, and Learning (MEL) in research for development, particularly focusing on an underexplored area of data justice: tracking policy influence from scientific research.

This paper combines an extensive literature review with 10 in-depth expert interviews that systematize the importance of tracking research influence, main methodologies used, and the current characteristics of the data ecosystem in MEL for development. It then uses a computational data science approach to assess the influence of research on open government policies in Latin America. Specifically, it explores a searchable index of millions of policy documents (Overton), combined with contextual information, to assess possible metrics of research influence on policy.

While unveiling the potential of data and tools based on large language models (LLMs) in the MEL domain, the paper uncovers a stark reality: the data is incomplete, and its advantages are skewed towards the Global North. The coverage and representation in the Global South are significantly lacking, with idiosyncratic differences influencing how research is used in policy decisions.

This research contributes to the broader discourse on fairness and justice in data and computational systems. It emphasizes the need for nuanced approaches in evaluating research impact on policy decisions, advocating for a more equitable data landscape in the pursuit of global development goals.

Paper short abstract:

To explore how social registries have profound implications for social policy systems, at the institutional and policy level by shaping the model of targeting and the eligibility conditions, and at the level of implementation by depoliticising the way claims can be made on the state.

Paper long abstract:

Despite criticisms and chronic operational problems, the World Bank has been promoting an agenda of establishing and using social registries for poverty targeting in cash transfer programmes and other policy areas, with the intention of making these registries into the backbone of social policy provisioning in the Global South. Social registries are large-scale data systems that collect socio-economic data on households for poverty targeting. Since 2010, the World Bank has provided loans to develop social registries to forty-one Sub-Saharan African countries, with a significant increase since COVID-19. However, the implications of these data systems in shaping social policy systems and people’s eligibility and access to social entitlements has received scant attention.

Drawing on fieldwork in Kenya and a general assessment of this agenda across the Global South, this paper explores the implications of social registries on social policy systems. We argue that social registries are profoundly influencing social policy architectures, albeit in discrete and even covert ways, through institutionalising segregationist and disempowering modalities of targeting in social protection, which deeply shape the way claims can be made on the state. In lieu of building civil registries that cover the whole population, the registries are also creating data systems that are biased towards these modalities and ill-equipped for transitioning towards more universalistic modalities of social policy.

From a data justice perspective, this research demonstrates how data systems in development policy can be used to obscure politicised agendas, such as using social registries to lock countries into a neoliberalised social policy trajectories.

Paper short abstract:

We explore the role of data and digital technologies in legitimizing CSOs' work in China, especially how they make sense of their advocacy work in relation to ESG (Environment, Social and Governance) data, and local dynamic and micro-power relations between government, market and civil society.

Paper long abstract:

Under the global development discourse advocating green transition and digital transformation, a growing number of initiatives led by local civil society organizations (CSOs) are being initiated in China. They are increasingly engaging various forms/types of ESG (Environmental, Social and Governance) data and utilizing related digital technologies (such as AI, IoT, big data etc.) to advocate for environmental protection and climate change mitigation. This paper presents a case study of a Shanghai-based CSO who is specialized in ESG data gathering and processing and has been well recognized in the local ESG professional community. We explore the role of data and digital technologies in legitimizing the ongoing CSOs’ work in the Chinese context. The article addresses the question: How does this Shanghai CSO execute its ‘advocacy’ through ESG data? and we especially give voice to the world of local CSOs, understanding and learning from their perspectives, experiences, and initiatives. Our ambition is to demonstrate how such organizations make sense of their work in relation to data, what types of change they helped enact, in terms of its forms/types they managed to push forward socially just development, as well as how (and why) they did so. Furthermore, the article contributes to the rethinking narrative on social justice development practices and approaches in terms of data justice and governance.

Paper short abstract:

We explore the expanding 'datafication' of health, specifically community health, as enacted by state and non-state actors. We push back against North/South, colonizer/colonized binarisms in favour of a nuanced picture of how new 'data relations' benefit elites politically as well as economically.

Paper long abstract:

International political economy often points to foreign actors’ practices of value extraction in the South, which enrich capitalist elites in the North. Recent literature on ‘data colonialism’ adds weight to this corpus. In this article, we point to less obvious forms of data capitalism and extraction on the part of domestic elites in east Africa, prompting a more expansive understanding of accumulation than profit alone. Drawing on Couldry and Mejias’ notion of ‘data relations’, we examine community health as an unlikely frontier of the datafication of everyday life in Burundi and Kenya, staffed by unsalaried Community Health Workers. While community health is a space inhabited by either state-based (Burundi) or a blend of state and non-profit actors (Kenya), we observe similar, intensifying logics of extraction and commodification. However, we go beyond commercial valuations to explore how data relations engender political capital, as well as enact new forms of social surveillance and control. Given the contentious politics of data extraction within communities, the datafication of healthcare requires forceful, at times oppressive interventions at different levels of the state, which works against community health’s founding ethos. While development authoritarianism is more apparent in Burundi, we explore resonant dynamics in Kenya, whereby state and non-state actors meld managerialism regarding cost effectiveness and performance incentives with authoritarian repertoires of duty, sacrifice and labour. We thus conclude community health to be a particularly insidious site of data relations, subsidized by cheap labour, and is one ripe for future exploitation by a range of vested interests.

Paper short abstract:

Our paper focuses on how Big Tech is reshaping humanitarian data infrastructures and anticipatory humanitarian action. In so doing, we bring the concept of data curation, the behind-the-scene activity of constructing fungible and reusable data sets, to the centre of the data justice debate.

Paper long abstract:

The last decade has seen an increasing influence of corporate firms on the humanitarian and development space, as highlighted by the so-called AI for Social Good (AI4SG) movement. Within this discourse, there is growing interest in Anticipatory Humanitarian Action (AHA), an emerging field of policy and practice that rests on data analytics to generate insights into humanitarian crises and displacement trajectories. These AHA initiatives bring together Big Tech’s unrivaled computing power and international organisations’ and national governments’ data to build and train predictive models. However, these partnerships raise serious questions about the production and consequences of this form of data-driven humanitarianism.

Our paper focuses on how Big Tech’s involvement is reshaping humanitarian data infrastructures. In particular, we examine how synergies and tensions between corporate and humanitarian actors define the ‘data set politics’ underpinning the machine learning-based predictive models developed by Big Tech and UN agencies.

By delving into the power relations surrounding and seeping into the construction and use of data sets, we extend the ethical concerns addressed within the data justice debate to data curation, the behind-the-scene activity of constructing data sets that could be used in different contexts and for different purposes.

Drawing on a mix of primary and secondary sources, we contribute to the conversation about the possibilities and risks that AI and ML hold in the realization of the SDGs, the increasing role that Big Tech is playing in this space, and the implications of data-driven innovation for justice in the humanitarian sector.

Paper short abstract:

This paper provides an analysis of aid donors' support for the controversial 2014 Myanmar census. In the context of the unfolding Rohingya crisis, the census was part of the Government's discriminatory policies towards the Rohingya. This paper analyses why donors provided support for the process.

Paper long abstract:

Myanmar’s political reforms in 2011 led to the influx of aid donors and other development actors to the country. In seeking to support largescale socio-economic development initiatives in the country, a crucial challenge these actors faced was the lack of data regarding the country and its population. Bilateral donors and UN agencies – including the UK’s DFID, Australia’s DFAT, and the UNFPA – sought to address this by supporting the Government of Myanmar (GoM) to conduct the country’s first national census since 1983. Early on, concerns were raised about how the politically-sensitive issue of ethnicity would be addressed in the census – given the ongoing ethnic conflicts and the unfolding Rohingya crisis. Despite assurances that respondents would be able to self-identify, when the census was conducted in April 2014, the GoM had included a list of national ethnic groups that excluded identities such as the Rohingya and misclassified other ethnic groups, provoking outrage. Human rights organisations accused donors of complicity in the GoM’s discriminatory policies towards the Rohingya. In this paper, we examine why aid donors chose to fund and support the Myanmar census despite the risks of the GoM using it as part of its process of ethnic cleansing. Drawing on interviews and key reports, we examine a range of possible explanations -- such as geopolitical interests, technocratic and economic bias, and bureaucratic inertia. The paper sheds light on how the census process reinforced the GoM’s discrimination against the Rohingya and why aid donors supported this process.

Paper short abstract:

Statistical data have become a key input for contemporary development interventions. This paper analyses the complex acts of mediation that enumerators perform while navigating survey sites and seeks to unpack the labour and social processes that underlie this crucial knowledge infrastructure.

Paper long abstract:

Ethnographic accounts of statistical production have emphasised the considerable work of interpretation and translation that accompanies the construction of universal numerical measures for socio-economic phenomena (Merry 2010; 2015). While much of this literature has focused on the role of technocrats and policy elites in data value chains, a growing scholarship has emerged that seeks to analyse the crucial labour of enumerators and front-line workers in the production of data (Kingori 2013; Seth 2018). Drawing on such work, this paper examines the epistemic role of enumerators in large-scale surveys. Based on an ethnography of a health policy survey in central India, it shows the complex social role that enumerators play in the survey process. Enumerators utilise a range of tacit practical skills to perform tasks that are necessary for surveying such as building rapport with respondents and explaining complex terms in questionnaires. Further, they rely on implicit knowledge to navigate administrative hurdles and forms of social hierarchy that they encounter at survey sites. This paper argues that the labour performed by enumerators is itself “ethnographic” in nature and seeks to highlight its centrality for the production of socio-economic data. It also provides details of how enumerators are hired and managed in the context of customised surveys commissioned by development organisations and contracted to private survey firms. By focusing on the essential labour and organisational process that underlie data production, this paper seeks to advance data justice scholarship and further our understanding of the socio-political structures within which data are created.

Paper short abstract:

This paper examines how digital data is collected, processed, and managed in two Huawei-built data centres in Egypt and Algeria, both of which have adopted data governance frameworks pressing for data localisation in order to strengthen digital sovereignty and digital development.

Paper long abstract:

As China builds an increasing share of the underpinning infrastructure for hosting data in developing countries, it is important to ask how the global expansion of Chinese-built data centres and cloud services is reshaping data inequalities? To answer this question, this paper examines how digital data is collected, processed, and managed in two Huawei-built data centres in Egypt and Algeria, both of which have adopted data governance frameworks pressing for data localisation in order to strengthen digital sovereignty and digital development. In Egypt, I explore Huawei’s contract with the National Research Centre (NRC), the country’s largest research institution and in Algeria, I explore its project with Sonatrach, the state-owned energy firm.

The paper finds that these two North African countries have engaged in superficial data localisation efforts, whereby data in strategic sectors is localised within national borders but is still processed by foreign multinationals. Even though the NRC and Sonatrach took the initial step of localising their data by constructing and running their own data centres, these initiatives were quickly abandoned in favour of more efficient solutions that ultimately outsourced the management and expansion of their respective data centres to Huawei. Control over infrastructure and the data it hosts remains in the hands of the Chinese and non-Chinese tech giant, limiting opportunities for technological learning. While emerging data governance frameworks in Algeria and Egypt are failing to achieve their dual objectives of data sovereignty and economic development, both are using the emerging data system to expand their surveillance capabilities.