Children and the Data Cycle: Rights and Ethics in a Big Data World

📝 Abstract

In an era of increasing dependence on data science and big data, the voices of one set of major stakeholders - the world’s children and those who advocate on their behalf - have been largely absent. A recent paper estimates one in three global internet users is a child, yet there has been little rigorous debate or understanding of how to adapt traditional, offline ethical standards for research, involving data collection from children, to a big data, online environment (Livingstone et al., 2015). This paper argues that due to the potential for severe, long-lasting and differential impacts on children, child rights need to be firmly integrated onto the agendas of global debates about ethics and data science. The authors outline their rationale for a greater focus on child rights and ethics in data science and suggest steps to move forward, focussing on the various actors within the data chain including data generators, collectors, analysts and end users. It concludes by calling for a much stronger appreciation of the links between child rights, ethics and data science disciplines and for enhanced discourse between stakeholders in the data chain and those responsible for upholding the rights of children globally.

💡 Analysis

In an era of increasing dependence on data science and big data, the voices of one set of major stakeholders - the world’s children and those who advocate on their behalf - have been largely absent. A recent paper estimates one in three global internet users is a child, yet there has been little rigorous debate or understanding of how to adapt traditional, offline ethical standards for research, involving data collection from children, to a big data, online environment (Livingstone et al., 2015). This paper argues that due to the potential for severe, long-lasting and differential impacts on children, child rights need to be firmly integrated onto the agendas of global debates about ethics and data science. The authors outline their rationale for a greater focus on child rights and ethics in data science and suggest steps to move forward, focussing on the various actors within the data chain including data generators, collectors, analysts and end users. It concludes by calling for a much stronger appreciation of the links between child rights, ethics and data science disciplines and for enhanced discourse between stakeholders in the data chain and those responsible for upholding the rights of children globally.

📄 Content

Children and the Data Cycle: Rights and Ethics in a Big Data World1

Gabrielle Berman
UNICEF Office of Research, Innocenti
Florence, Italy
gberman@unicef.org
Kerry Albright UNICEF Office of Research, Innocenti Florence, Italy
kalbright@unicef.org

ABSTRACT
In an era of increasing dependence on data science and big data, the voices of one set of major stakeholders – the world’s children and those who advocate on their behalf – have been largely absent. A recent paper estimates one in three global internet users is a child, yet there has been little rigorous debate or understanding of how to adapt traditional, offline ethical standards for research, involving data collection from children, to a big data, online environment (Livingstone et al., 2015). This paper argues that due to the potential for severe, long-lasting and differential impacts on children, child rights need to be firmly integrated onto the agendas of global debates about ethics and data science. The authors outline their rationale for a greater focus on child rights and ethics in data science and suggest steps to move forward, focussing on the various actors within the data chain including data generators, collectors, analysts and end users. It concludes by calling for a much stronger appreciation of the links between child rights, ethics and data science disciplines and for enhanced discourse between stakeholders in the data chain and those responsible for upholding the rights of children globally.

1.INTRODUCTION
UNICEF has a specific mandate to protect, respect and uphold the rights of children and their families globally and to help facilitate the full implementation of the Convention on the Rights of the Child (CRC) (UN General Assembly 1989). In undertaking research, and particularly research involving children, that mandate is clear with well-defined guidance provided by international initiatives such as the Ethical Research Involving Children programme (Graham et al., 2013). However, less international attention has been given to rigorous international frameworks for children’s data collection and analysis. UNICEF has developed a mandatory cross-organizational procedure on ethical evidence generation (UNICEF, 2015) underpinned by a belief that ethical

1 This paper is a reproduction of the original paper published as Berman, Gabrielle; Albright, Kerry (2017) Children and the Data Cycle: Rights and Ethics in a Big Data World, no. 2017-05, UNICEF Office of Research - Innocenti, Florence, available at; https://www.unicef-irc.org/publications/907/

principles and a rights-based approach are not only relevant in research, but are equally important within all forms of data collection, analysis and evaluation involving human subjects or sensitive secondary data. This procedure outlines explicit guidelines for data collection which includes reflection on issues pertaining to data privacy, the rights of children to be consulted on issues which affect them, informed consent, security and confidentiality.

However, with increasing collection of big data and a vocal data science movement calling for more open data and greater utilization of big data within public, private and not for profit policymaking arenas, ensuring the protection of and respect for children rights is becoming increasingly challenging.

With respect to defining ‘Big Data’, multiple definitions and little consensus exist, The United Nations Global Pulse (2013) highlights the nature and qualities of big data noting that:

Big Data is an umbrella term referring to the large amounts of digital data continually generated by the global population. It refers to the speed and frequency by which data is produced and collected – by an increasing number of sources. [It] generally shares some or all of the following features:

Digitally generated 2. Passively produced 3. Automatically collected 4. Geographically or temporally trackable 5. Continuously analysable. (p.3)

While recognizing these characteristics, in this paper we refer to Canavillas (2016) definition of Big Data. This reflects a position that Big Data is a technological phenomenon, in so far as it can be described as:

Data sets that are so large or complex that traditional data processing applications are inadequate to deal with them. The term ‘big data’ often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that attempt to extract value from data, (Canavillas et al., 2016).

It should also be noted that, while adopting this definition, this paper also recognizes that big data is not solely a technological phenomenon; it also has cultural and social dimensions relating to expectations of its applicability, robustness, accuracy and objectivity, across multiple domains – r

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