Operation Phakisa Education: Why a secret? Mass surveillance, inequality, and race in South Africa's emerging national e-education system
First Monday

Operation Phakisa Education: Why a secret? Mass surveillance, inequality, and race in South Africa's emerging national e-education system by Michael Kwet



Abstract
This paper investigates several human rights concerns with respect to the South African government’s secretive plan to transform basic education, Operation Phakisa Education. The first concern is the influence of digital surveillance on education and society by government and corporate institutions. This is evaluated in light of electronic foreign and domestic government and corporate surveillance, as well as the context of socioeconomic inequality. Another is the likelihood of a chilling effect on free speech and inquiry. A third issue is the monitoring and evaluation of teachers and the associated limits on teacher autonomy. Last, it considers democratic process and informed consent. It concludes that Operation Phakisa Education poses serious problems for education and society, and contradicts principles of democratic transparency endorsed in education policy.

Contents

Introduction
South Africa: A crisis in education
Operation Phakisa Education: A program to transform education
Big data e-education and public-private partnerships
Problem #1: Government and corporate surveillance
Problem #2: Chilling effects
Problem #3: Teacher autonomy
Problem #4: Consent and democratic governance
Alternatives: Technologies that respect user and community freedom
Conclusion — Operation Phakisa Education: A secret transformation

 


 

Introduction

In 2015, the South African (SA) government launched Operation Phakisa Education (OPE), an implementation model to fast-track digital technology into all public schools. The model is designed to fulfill the plan to transform basic education with computer technology first formulated in the 2004 White Paper on e-Education: Transforming Teaching and Learning through Information and Communication Technologies (ICTs) (hereafter: White Paper). Yet controversial developments in the digital world are reaching children through public schools. Is South Africa prepared to handle the privacy challenges of deploying digital technology in the education system?

By using computers in education, or “e-education”, South African policy-makers believe they can alleviate the crisis in the basic education sector [1]. They assert that the capabilities afforded by digital technology, when combined with teacher training for computer-based pedagogy, will create an effective learning environment for the production of “twenty-first century learners”. On this view, technology offers an opportunity to overhaul the day-to-day norms of public schools. There is no scholarship to date on Operation Phakisa Education, as details have been kept a tight secret. This paper explores the ramifications of one core part of OPE: mass surveillance.

I have undertaken this study for two reasons. First, to document plans to transform the education system disclosed to me through semi-structured interviews with high-level South African policy-makers and key stakeholders. These interviews were conducted beginning October 2015 and concluded late 2016. Second, it probes the potential consequences of mass surveillance in basic education in particular and South African society in general. This includes domestic and foreign government and corporate surveillance.

In the next three sections, I detail the background context for OPE, what its elements consist of, and how big data e-education works. In each of the following four sections, I address a distinct problem posed by mass surveillance in education, with policy-maker responses included. The final section proposes some privacy-respecting technologies as solutions to what OPE policy-makers are currently using or plan to use in the near future. I conclude with a brief discussion of the significance of my findings.

 

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South Africa: A crisis in education

The South African government designates education an apex priority to alleviate poverty, reduce inequality, and stimulate economic growth [2]. Across the political spectrum, education is seen as a vital and essential tool for improving society (Malema, 2014; Al Jazeera, 2016; Zuma, 2015). Accordingly, the government devotes 6.7 percent of its Gross Domestic Product (GDP) to education. At 19.7 percent of the total annual budget, government spending on education is the highest among all sectors [3].

Despite the spending priority and emphasis on education, the basic education system remains in crisis (Masondo, 2016a). Nationally representative surveys show that over half of all students (58 percent) cannot read for meaning by the end of Grade 4 and almost a third are illiterate [4]. This has a disastrous impact on education. As van der Berg, et al. observe, “the relation between print and spoken language ... is arguably the most important skill that children learn in primary school. Failure to achieve this outcome makes it highly unlikely for many children that they will ever be able to achieve strong cognitive skills at higher grades, given their weak foundations” [5].

South Africa participates in three major cross-national standardized testing systems: the Trends in International Mathematics and Science Study (TIMSS), Southern African Consortium for Monitoring Educational Quality (SACMEQ), and Progress in Reading and Literacy Study (PIRLS). These studies are designed to gauge learner educational achievement. In each of the three tests, South Africa ranks at or near the bottom [6].

In 2011, South Africa implemented the Annual National Assessment (ANA) to evaluate learner performance. It was the first national standardized test to be conducted on an annual basis. ANA results were very poor. In the 2014 verification examinations, 57 percent and 56 percent of Grade 3 learners achieved the ANA-required literacy and numeracy levels, respectively. Mastery of the minimum language and mathematics competencies for Grade 6 was 46 percent and 32 percent, and for Grade 9, 22 percent and three percent, respectively [7].

About 75 percent of all learners pass the National Senior Certificate (NSC), also known as “matriculation” or “matric”. Yet half of any given learner cohort drops out of school by the time they reach Grade 12. Over the life of the cohort, only around 40 percent of learners matriculate (Equal Education [EE], 2016).

Despite two decades of efforts to improve education, poor and unequal performance persists. Many causal factors are at play. First and foremost, centuries of oppression have an enduring impact on the poor black majority. During apartheid, the “Bantu education” system deprived blacks (especially Africans) of educational resources and employed a dumbed down curriculum explicitly designed to peg blacks into menial labor (Tabata, 1960). State inspectors visited schools to enforce political and occupational subservience to the apartheid agenda (Chisholm, 1999). Other conditions, such as residential segregation, racial inequality, and labor exploitation, have persisted into the present. Educational and other reforms, such as subsidized housing for the poor and social welfare grants, have not been sufficient to reverse the legacy of apartheid.

A high degree of inequality internal to the South African education system persists, with sharp class and race-based disparities afflicting the present. Ninety-three percent of schools located in the former “homelands” are found in the poorest three school quintiles, whereas 70 percent of historic white schools are in the richest quintile. Pass rates and other benchmarks often track closely with race and class [8].

A dizzying array of problems combine to entrench inequality. Within the education space, resources are often lacking. According to the numbers from the Department of Basic Education (DBE), of approximately 26,000 schools:

  • 22,938 schools do not have stocked libraries, while 19,541 do not even have a space for a library;
  • 21,021 schools do not have any laboratory facilities, while 1,231 schools have stocked laboratories;
  • 2,703 schools have no fencing at all;
  • 19,037 schools do not have a computer centre, whilst a further 3,267 have a room designed as a computer centre but are not stocked with computers (Equal Education [EE], 2013).

Neoliberal commentators place primary blame on the shortcomings of educators [9]. They emphasize that teachers have relatively high rates of absenteeism [10], often fail to cover their curriculum over the course of the year, and possess poor subject knowledge and pedagogical skill [11]. Conflicts with teachers’ unions occupy the news (Masondo, 2016a; Jansen, 2014; Paton, 2016). Teachers have continually resisted media, academic, and government pressure to implement biometric surveillance for attendance, periodic inspections into classrooms, salary-linked performance (i.e., merit pay), and the encroachment of standardized testing such as the ANAs [12].

 

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Operation Phakisa Education: A program to transform education

Two decades after the fall of apartheid, educational reform has largely failed. In May 2015, the South African government announced a new plan. Jeff Radebe, Minister in the Presidency for Planning, Monitoring and Evaluation (DPME), together with Angie Motshekga, Minister of the Department of Basic Education (DBE), declared the launch Operation Phakisa Education “under the banner ‘ICT in Education: Leveraging ICTs to improve Basic Education.’” Operation Phakisa, meaning “hurry up” in Sesotho, is part of a “Big Fast Results” policy methodology engineered to “facilitate the development of detailed plans with a strong theory of change, advocating for strong monitoring, evaluation, reporting, and accountability frameworks which are essential for the successful implementation of national goals and priorities”. “Detailed and measurable plans” would be brainstormed by “key stakeholders and critical decision makers ... as opposed to higher level planning” at a four-week lab at the Birchwood Hotel in Boksburg, Johannesburg (South African Government, 2015) [13].

President Zuma resorted to the Phakisa approach after a state visit to Malaysia in August 2013. Prior to OPE, he launched two Operation Phakisa initiatives, Operation Phakisa Health and Operation Phakisa Oceans Economy. Each initiative began as a way to fast-track progress in critical development issues. All Phakisa projects feature Delivery Labs which bring together various stakeholders drawn from the public and private sectors, NGOs, and civil society [14].

From the outset, Operation Phakisa Education has been shrouded in secrecy. In 2015 and 2016, I conducted interviews with members of the South African government and key stakeholders from the public and private sectors [15]. Interview subjects attending the OPE Labs are gagged by non-disclosure agreements prohibiting them from sharing much about the Lab proceedings. There has been little public disclosure since then.

While the full picture of OPE remains murky, some of my interview subjects disclosed parts of the plan. Critical portions of the new, secret strategies to transform post-apartheid education can be garnered from the details revealed to me by interview subjects.

In one interview, a high-level e-education policy-maker at the DBE, Richard* [16], described OPE as follows: “the government has got a vision, a plan to roll out ICTs in schools. So we developed that plan, through which we are going to do that. A comprehensive plan ... the basis of developing that plan, and the implementation of that plan, is what we call Operation Phakisa Education” [17]. The Birchwood Lab divided the conference into five “workstreams”. They are:

  1. Connectivity
  2. Devices
  3. Teacher professional development
  4. Digital content development and distribution
  5. e-Administration (Department of Planning, Monitoring and Evaluation [DPME], n.d.)

Richard described OPE as an “implementation model” to fast-track economic development in various sectors; the government aims to accelerate the rollout in the coming years. According to Richard, the White Paper still serves as the foundation for OPE. It envisions the use of ICTs to phase out apartheid-era authoritarian pedagogy, create ICT-proficient learners, and distribute digital technology to the poor black majority to bridge the digital divide (Department of Education [DoE], 2004). Yet the OPE initiative brings much more to the table. While the “comprehensive plan” that forms part of OPE has not been published, critical parts disclosed in interviews and elsewhere (discussed below) make clear that visions for education go beyond the 2004 White Paper. OPE is more than just an implementation model: it encompasses a new form of education based on the most recent technological advances.

This is largely due to the fact that computer technology has changed since the White Paper was published in 2004. The rise of cloud services, data analytics, artificial intelligence, and a shift towards mobile and tablet computers are changing the composition of the digital ecosystem. On every continent, technologists, entrepreneurs, governments, and corporations are pushing these developments into the education space (Singer, 2017; Lardinois, 2017). This includes the South African government and e-education stakeholders.

Among the many important issues surrounding OPE, this paper focuses on one: privacy in education. The South African government is attempting to turn the basic education sector into a data-driven system that will transform teaching, learning, and management. Their vision is primarily provided by United States technology corporations in partnership with the South African government. The shift to e-education has critical privacy implications that could drastically curtail civil rights and liberties in SA education and society. Before we consider privacy concerns around e-education — and policy-maker responses — we will explore two case examples of how big data works in the education sector.

 

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Big data e-education and public-private partnerships

Interview subjects make clear that big data analytics is coming to South Africa’s education system. Computer network services will collect granular records of daily educational activities to provide detailed study of learner and teacher behavior. The goal is to obtain a rich picture at all levels: learner, educator, school, circuit, district, provincial, and national. Corporate partners in e-education will provide expertise and software for the analysis of each level for “targeted intervention”. Policy-makers hope each learner will be provided with a “personalized” learning plan that can only be derived by watching and recording nearly every aspect of a learner’s digital activity.

Two products provide examples of how a data-driven approach works in education: Knewton’s big data education services (for learning) and the Michael & Susan Dell Foundation’s (MSDF) Data Driven Districts (DDD) Dashboard (for administration). We will consider each in turn.

In October 2015, Knewton announced a partnership with Africa-based Top Dog Education to provide big data education in South African schools for Grades 4–12. The partnership is Knewton’s first in Africa. A press release states that, “Initially, Top Dog and Knewton are targeting to reach 1.2 million students across Uganda, Zambia, Nigeria, Kenya, and Zimbabwe”. Top Dog Education is described as “the largest ed-tech company in Africa with over 3.5m users”. It also partnered with Vodacom “to make its content more accessible to broadband users” (Knewton, 2016; see also, Knewton, 2015b).

The details of the service are seemingly off the record — it is not known when or where the education software will be used. Neither Knewton nor Top Dog Education responded to multiple e-mail requests for an interview. Nevertheless, Knewton’s services cover millions of learners, and their contract is consistent with aims and objectives of SA interview subjects. Knewton’s Johannesburg-born founder and former CEO, Jose Ferreira, explains his vision for big data education in speeches posted on the Internet. It is worth outlining his vision for the future of education.

Speaking at the 2012 Education Datapalooza summit in Washington, D.C., Ferreira stated that humanity is entering into a “totally data mined existence”. The spread of advanced computer machinery has enabled unprecedented volumes of data collection, the widespread recording and sharing of data, and the ability to analyze that data with assistance from computers. This, he believes, will be “really fun to watch” as it alters human society beyond recognition (Ferreira, 2012).

According to Ferreira’s world view, knowing nearly everything about everyone all the time will unleash the capacity to manage human affairs rationally for their own betterment. Ferreira proudly states, at Knewton, “we literally have more data about our students than any company has about anybody else about anything, and it’s not even close”. This includes corporations like Google and Amazon, he claims, on grounds that correlations in education are much richer than loosely correlated data about, say, consumer preferences in music and food. Knewton’s collection of “millions” of data points on each student enables the company to “literally know everything about what you know and how you learn best” (Ferreira, 2012).

Through their data analytics engine, Knewton has provided an “adaptive”, “personalized” learning service to over 13 million students across the world (Knewton, 2017). Knewton promises their system will revolutionize education. Through constant monitoring of students’ cloud-based activity — which homework passages they read, how long they spend reading each part, answers to questions on quizzes, when they click out of the software, and so on — Knewton begins to profile each learner based on her history. They then evaluate her conceptual understanding down to the “atomic level” and cross-reference that learner’s “psychometric profile” against their database of millions of learners. By evaluating patterns among millions of users, Knewton’s engine claims to assess an individual’s learning needs relative to learners with similar profiles and personalize her learning experience based on how similar learners improved using various pieces of content and software-based strategies for development (Knewton 2015a; Knewton, n.d.).

For example, Lerato may be struggling with the concept of “hypotenuse” in a way similar to Mpho and Maria, who share a similar psychometric profile. Let’s say Mpho was given a 14-minute video on hypotenuse for homework while Maria was given a text passage. If Mpho exhibited a drastic improvement with the video and Maria did poorly with the text, Knewton’s system may provide Lerato a video for her next homework assignment. Knewton’s system adapts to Lerato’s learning path in a way that is personal to her. Hence the terms “adaptive” and “personalized” learning. Gone are the days where each student gets the same exact homework assignment and exam questions [18].

Knewton seeks to correlate their learner data “with other people’s datasets”. In a hypothetical example of a “food diary”, he explained that knowing “what you had for breakfast every morning at the beginning of the semester” could not only predict breakfast for the rest of the semester, but “more importantly, what you should have for breakfast”, to improve education performance metrics (Ferreira, 2012) [19]. The more information Knewton has about its users, the more they believe they can understand and cater to the individual.

While adaptive learning services providers like Knewton promise to enhance learning with data analytics, the Michael & Susan Dell Foundation promises to improve education administration. They utilize big data for education management in most of the South African school system, covering seven provinces, over nine million learners, and over 19,000 schools as of 2017 (Data Driven Districts, n.d.). Their Data Driven Districts (DDD) Dashboard system uses inputs from the South African School Administration System (SA-SAMS) to keep track of exams scores, curriculum coverage, learner grades, teacher and learner attendance, and personal information about students including their language, date of birth, grade advancement, and “social issues”. Both interview subjects from the MSDF said while the data is currently sent in on a weekly basis, it would be ideal to collect the data in real-time once high-speed Internet is deployed in schools [20].

The DDD Dashboard system is used to intensify the monitoring of teachers by district managers. This was explained by a consultant from the New Leaders Foundation, Ik Azubike, at the EduWeek Conference in Johannesburg in June 2016 (Azubike, 2016). In a YouTube video posted by New Leaders Foundation member Helen Jervis, a Gauteng Department of Education Circuit Manager, Monki Gabashane, said that district officials can use the software to “zoom into the learner and see which is the learner that is not attending school”. Gabashane remarked, “this is a very good tool” because “it gives you the confidence for you to be able to enter a school and not shake. It gives you the ammunition because we know we have that information” and “we know what you are doing” (Gabashane, 2016).

These videos make clear administrative bureaucrats are using the new cloud-based technology to sift through what happens in the classroom from external offices. Crucially, learner-centered service providers like Knewton could just as easily be used to monitor teachers in classrooms once the data is collected if it is shared with school administrators.

Statements in interviews and developments disclosed by the government demonstrate that centralized education management based on big data analytics is in the works. One high-level government official in the Department of Telecommunications and Postal Services (DTPS), Herman*, told me the DBE plans to collect learners’ browser cookies to track their Internet browsing activities in the DBE Cloud. Herman said the DBE also hopes to partner with corporations such as Microsoft to collect data in the DBE Cloud. In this scenario, proposed by Microsoft to the DTPS, the government would track the learners from childhood into their private adult lives, even after they graduate school, so long as they continue using their Microsoft Office 365 account [21].

Two high-level policy-makers in the DBE also endorsed and disclosed developments for big data analytics. Richard told me the DBE Cloud was scheduled for completion later that month. It will include a learner management system and data analytics. He said that personalized adaptive learning “is where we are going”. Data about students and learners will be collected and analyzed by the DBE via the DBE Cloud. Metadata analysis of which digital resources are being used and sought out by who and when will also be conducted by the DBE. Some of the data will be “general” (aggregated) but some will be personal (down to the individual). Plans for which kinds of data analytics will be conducted — especially regarding how granular collection might be done — are still in development. Analytics will include school performance outcomes [22].

In an interview with an e-education official from the Gauteng Department of Education (GDE), Tefo* said that “integrating [personalized] assessments into the solution — that is the next phase we are working on”. When asked about integration into the DBE Cloud, Tefo said, “we want to leverage on such resources” but that has “not been finalized yet” [23]. The DBE Cloud is partially completed and is live at http://www.dbecloud.org.za/lms/dbe.

 

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Problem #1: Government and corporate surveillance

One danger posed by big data education is the expansion of state and corporate surveillance through e-education services. While a comprehensive review of surveillance issues is beyond the scope of this paper, a collection of important anecdotes illustrates how political and commercial surveillance threatens South African society. This section provides a brief overview to set the stage for problems 2–4 in the following sections.

History provides many examples of how surveillance has been used against political organizations and individuals. For more than a century, the United States has been tied to the racist surveillance of South Africans for the purpose of labor exploitation. This began at the end of the nineteenth century when the U.S. gained a foothold in the South African mining industry. In 1897, a leading American engineer proposed that:

... a most excellent law ... namely, the Pass Law ... if properly carried out, and efficiently administered, will enable us to get complete control over our kaffiri [24] labourers ... If every kaffir could be traced; if it could be told whether they have been registered before, or been in the service of a company, then we would have control over them [25].

Decades later, IBM New York aided and abetted the National Party government by enabling its subsidiary, IBM South Africa, to service apartheid. This began with the shipment of its IBM keypunch machines to South Africa in 1952. IBM created, maintained, and provided the technological equipment to power the computerized national identification system that helped the apartheid regime denationalize the country’s black population (Kayyali, 2015).

The pass system was a famous feature of South African governance. Internal passports began with the colonization of the Western Cape. It intensified during the nineteenth century with the discovery of diamonds and gold, to control black miners. Pass book surveillance culminated in a national pass law system designed to track and control the personal history and movements of all black South Africans. The apartheid reference book system, which many derisively called “dompas” (meaning “stupid pass”), was engineered for totalitarian surveillance under centralized bureaucratic authority [26].

While IBM provided computational assistance for the population registry beginning in 1952, the reference book system could not be practically implemented, especially in the rural countryside. State capacity to process cards, train workers in fingerprint interpretation, and control defacement and fraud was too resource-intensive for efficient operation. With its failure apparent in the early 1960s, the dompas became a tool for white supremacist police brutality. Average monthly arrests numbered 49,000 by mid-1962, and a “macabre symmetry in the figures for monthly registrations in the 1950s and monthly arrests in the 1960s” emerged [27].

In 1960, a protest against the pass law system culminated in the Sharpeville Massacre. The event helped mark the beginning of violent resistance to the apartheid state. In its wake, the apartheid government banned black oppositional political parties, including the African National Congress (ANC). In May 2016, ex-CIA agent Donald Rickard informed the media he tipped off the South African authorities about Nelson Mandela’s whereabouts in 1962, leading to his capture by South African police. Rickard expressed no regret, and he died before further questions could be asked (Fallon, 2016). The apartheid state sought to suppress the anti-apartheid movement with police surveillance and the enforcement of racist apartheid laws. As a result, many anti-apartheid activists were forced into exile.

The use of surveillance was also a tool of repression for the United States. Throughout the twentieth century, new forms of surveillance were used as an instrument of U.S. imperialism. Historian Alfred McCoy documented the genesis of U.S. global surveillance in his seminal work, Policing America’s empire: The United States, the Philippines, and the rise of the surveillance state. McCoy traces the United States’s surveillance empire to “America’s first information revolution” beginning in the late nineteenth century. During that period, the quadruplex telegraph, commercial typewriter, Dewey decimal system, biometric techniques, photographical files, and the Hollerith punchcard combined to enable “the management of textual, statistical, and analytical data” (McCoy, 2013). The U.S. invaded the Philippines in 1898; by 1901, Captain Ralph Van Deman, the “father of U.S. military intelligence”, assumed command of the U.S. military’s first field intelligence unit. His division “detailed information on thousands of Filipino leaders, including their physical appearance, personal finances, landed property, political loyalties, and kinship networks” (McCoy, 2013). Information obtained was used to exercise control over the Philippine population.

The new high-tech surveillance apparatus soon came home to the United States. It was used for the Palmer Raids, Richard Nixon’s “pink sheets”, and other repressive political agendas against politically active organizations [28]. In one high-profile incident, FBI Director J. Edgar Hoover’s deputy, William Sullivan, wrote a letter to Dr. Martin Luther King, Jr. prodding him to commit suicide. Sullivan threatened to reveal Dr. King’s extra-marital affair discovered through FBI surveillance. He offered Dr. King “one way out” before his “filthy, abnormal fraudulent self is bared to the nation” (Gage, 2014; Electronic Frontier Foundation [EFF], 2014). Throughout the twentieth century, various U.S.-based social justice groups, workers, and activists became victims of surveillance-based policing (Boykoff, 2007; Wu, 2015).

Today, the United States is at the center of a new, digital global surveillance apparatus. U.S. whistleblowers like William Binney, Thomas Drake, Kirk Wiebe, and Ed Lumis revealed that the U.S. government is conducting bulk surveillance on foreign and domestic populations. Their claims were confirmed by Edward Snowden, who leaked a massive trove of documents to journalists in June 2013. Various leaks and whistleblowers have revealed that the United States government partners with major U.S.-based technology corporations to conduct mass surveillance on domestic and global populations. The National Security Agency (NSA) is at the center of the new surveillance regime (Greenwald, 2014; Granick, 2017).

The vast scope of NSA surveillance is indicated by various programs disclosed by whistleblowers. The two primary tools used to conduct surveillance are Upstream (which taps the Internet backbone, often with direct cooperation from U.S. corporations) and PRISM (which gives the NSA access to data from major corporate service providers such as Facebook, Google, Microsoft, and Skype) (Macaskill and Dance, 2013). A program called XKEYSCORE is used to collect “nearly everything a user does on the Internet” and provide them with a Google-like search interface for surveillance targets (Greenwald, 2013; Dorling, 2013).

Through BULLRUN, the NSA inserted vulnerabilities into popular protocols like HTTPS, voice-over-IP, and Secure Sockets Layer (SSL) (Ball, et al., 2013) [29]. The NSA permits it to store any and all encrypted communications for as long as they wish, in hopes they may one day decrypt the content (Perloth, et al., 2013).

The NSA’s new $2 billion facility in Bluffdale, Utah has four 25,000-square-foot data halls to store “rows and rows” of servers (Bamford, 2012). According to NSA whistleblower William Binney, Bluffdale was built to expand the NSA’s data storage capacity. He estimates “just for e-mails and phone calls alone they have approaching 20 trillion transactions of US citizens with other US citizens” (Binney, 2013). Banking, social networking data, and other services add trillions of more transactions.

The mass interception and collection of electronic communications demonstrates that the United States and its allies aim to bring nearly all electronic communications under its vast global surveillance net.

There are recent examples of Western intelligence agencies spying on South Africans. In June 2014, the Washington Post reported that the NSA provided legal certification “to intercept through U.S. companies not just the communications of its overseas targets but any communications about its targets as well” (Nakashima and Gellman, 2014). One hundred ninety three countries are certified targets, including South Africa (Washington Post, 2014). In 2014, Der Spiegel published slides detailing an NSA program, TREASUREMAP, which aims to provide a “near real-time, interactive map of the global internet” that plots every device connected in “a kind of Google Earth for global data traffic, a bird’s eye view of the planet’s digital arteries” (Müller-Maguhn, et al., 2014). The NSA includes South Africa among its “13 covered servers in unwitting data centers around the globe” (National Security Agency [NSA], n.d.). The data centers help the NSA “perform [DNS] monitoring covertly and to get a more global view on DNS name resolution and service availability” [30].

In 2016, Le Monde reported that Britain’s Government Communications Headquarters (GCHQ), an NSA ally, tapped into telecommunications networks by targeting their managers. South Africa-based telecommunications corporation MTN Group was among those under surveillance (Leloup and Utersinger, 2016). The GCHQ also aimed to retrieve the briefings of the South African delegates to G20 and G8 summit meetings (Guardian, 2013). In 2015, the United Kingdom Investigatory Powers Tribunal found the GCHQ unlawfully breached the European Convention on Human Rights for spying on the South African-based Legal Resources Centre (LRC) (RDM Newswire, 2015). The LRC is known for its work protecting human rights.

Within South Africa there is suspicion that domestic corporations and the state are conducting bulk surveillance. In 2011, Wikileaks published leaked documents from Stellenbosch-based VASTech SA Pty Ltd. showcasing equipment for bulk communications interception. The content of phone calls and e-mail messages, as well as metadata from telephone and Internet communications, can be swept up by VASTech’s Zebra, Badger, and Satellite Signal Analyser products (Swart, 2016a). The equipment was sold to Muammar Gaddafi, who used it for bulk surveillance of the Libyan population (Sonne and Coker, 2011). In October 2016, The Intercept published a leaked document revealing that VASTech has since developed more powerful “NSA-like” equipment it claims “rivals a government spy agency” (McLaughlin, 2016).

During the mid-2000s, VASTech was subsidized by the South African government (Mchunu, 2013). It is not known if the government owns or uses VASTech’s mass surveillance equipment. However, the evidence suggests it desires to conduct bulk surveillance to counter political dissent. In June 2016, investigative journalist Heidi Swart reported contents of a leaked document, “The 2014 National Intelligence Priorities”. According to Swart, “The document states that countering the ‘most serious threats to our national security’ that require ‘immediate and sustained intelligence collection” involves the ‘maximum use of covert human and technical means’.’ The “intelligence gathering is justified by several ‘threats to national security’. For example, one intelligence priority for 2014 centered on national and provincial elections. The SSA Domestic Branch was tasked with investigating and counterplanning for a ‘so-called “Arab Spring” uprising prior to elections’”. “Another area of interest for the SAA,” Swart added, “was investigating and counterplanning for ‘violent industrial action’, with the investigation of ‘inter-union rivalry as a driver of violent industrial action’ high on the agenda. The transport industry was to be watched to allow for ‘counterplanning for violence in the taxi industry’”. Areas of surveillance include “terrorism, espionage, violence against foreign nationals, gangsterism, and the private security industry” (Swart, 2016b).

Privacy advocates consider South African communications legislation too weak to adequately safeguard privacy (Right2Know, 2014). Under the Regulation of Interception of Communications and Provision Act (RICA), telecommunications service providers must deploy infrastructure to allow the monitoring and interception of communications, while Internet service providers are required to store citizen metadata for three–five years. Legislation fails to regulate the most powerful mass surveillance capabilities conducted at the National Communications Centre, and citizens are required to register SIM cards in a national database (Right2Know, 2016). The “2014 National Priorities” document and other facts about surveillance equipment and legislation make clear that all South African inhabitants face the threat of mass government surveillance.

As digital technology spreads in South Africa, its inhabitants must also grapple with ubiquitous surveillance captured for big data analytics via the private sector. There are warning signs that this will have deleterious effects on civil rights and liberties. In May 2016, Angwin, et al. published a case study for ProPublica in which the Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) computer software created by Northpointe corporation for the U.S. criminal justice system assigned a higher criminal “risk assessment” to blacks than to whites. ProPublica’s study assessed 7,000 people arrested in Florida. They found the risk assessment algorithm used to predict violent crime flagged black defendants as future criminals at twice the rate as white defendants.

Northpointe’s algorithm is proprietary. As such, there is no way for the public to understand how it gave rise to this outcome. However, some details were provided to ProPublica. Northpointe does not categorize individuals by race, but they do assess factors correlated to race, such as educational degree and employment status. Northpointe’s founder, Tim Brennan, maintains that categories correlated to race like poverty, joblessness, and social marginalization must be included lest “your ... accuracy goes down” (Angwin, et al., 2016). Their predictive policing software is among the most widely used assessment tools in the U.S. criminal justice system.

Commercial surveillance also threatens to reinforce socioeconomic inequality. For example, companies are seeking to exploit novel forms of data to determine credit scores. Social networking services like Facebook seek to determine creditworthiness based on “social credit scores” (data from social networking) (Packin and Lev-Aretz, 2016). A person’s Facebook friends, for example, might better indicate her creditworthiness than her financial history derived from a FICO score. As with Northpointe’s algorithm, facially neutral categories might adversely affect oppressed groups. In the case of race, if having personal wealth and wealthy friends raises your credit score, and white people have more wealth, then the algorithm would favor whites and reinforce race-based inequality [31].

Socioeconomic inequality is all the more prone to insidious reinforcement when race-associated attributes tacitly emerge through data analytics. This is sometimes called “latent trait inference” whereby algorithmic processes are able to accurately infer traits from data even if they are not disclosed.

Facebook has been dancing around this issue. For example, their users do not disclose their race (there is no “race” category), but Facebook offers advertisers “ethnic affinity” categories such as African American, Asian American, and Hispanic. Given that any user from any “race” can fall into the category based on “indicators” (e.g., a white person who is a member of the African American Chamber of Commerce will help define their “ethnic affinity”), Facebook states they are not racially profiling (Newtiz, 2016).

In March 2016, Business Insider revealed different users received different trailers for the film Straight Outta Compton based on their Facebook affinity group (McAlone, 2016). There were two different Straight Outta Compton trailers delivered to the affinity groups. The trailer shown to white people boxed into their own ethnic affinity group portrayed the film as a “gangster movie” full of violence and conflicts with police. The trailer shown to black people pegged into their respective affinity group portrayed the film as a biopic, with violence contextualized as “‘protest’ imagery created by the very relatable, beloved members of N.W.A.” (Newitz, 2016).

In another instance, Facebook was sued by its users over “over alleged discriminatory policies that they say violate the US Federal Housing Act of 1964” (Farivar, 2016). The ethnic affinity grouping allowed marketers to offer housing advertisements that exclude ethnic affinity groups (Angwin and Parris, Jr., 2016) [32].

Under apartheid, the South African Broadcasting Corporation (SABC) also provided different media content for its official race categories. Channel TV1 was reserved for whites and TV2/3 was reserved for blacks. Their language policy called for “culturally authentic communication” [33]. English terms like “potato chips” and “toothpaste” were prohibited by TV2/3. There were no corresponding terms in Zulu, Xhosa, or Tswana, so advertisers were forced to describe them as “slice of potato fried in oil” or “the soap that cleans your teeth” [34]. Separate media content was designed to reinforce racial segregation. While big data content delivery does not filter as sharply, discriminatory content delivery via filter bubbles threatens to segregate cultural groups, with adverse effects on oppressed groups and social cohesion.

The poor black majority thus has many reasons to worry about government and commercial surveillance. When asked about collection of student data, a high level e-education official, Sipho* said, “There are a lot of contentious problems. It’s very much linked the right to privacy of individuals and so forth”. When asked about the fact that Google and the United States government will be tracking the youth from a young age, Sipho responded that “we are not having such a discussion at the moment” [35].

When asked about NSA data collection from services used in South African schools, Herman said, “if any private sector comes to us with such things, we sign a mandatory non-disclosure agreement ... between government and the respective party, prohibiting them from sharing such information” [36]. However, cybersecurity expert Bruce Schneier said a non-disclosure agreement could not prevent corporate data-sharing with the NSA. When I proposed Herman’s claim to Schneier, he told me, “they have to share with the government” — and a non-disclosure agreement cannot prevent that [37]. The Executive Director of the Electronic Frontier Foundation (EFF), Cindy Cohn, concurred. She stated, “that’s not the way it works”. U.S. corporations are legally compelled to share data with intelligence services, Cohn remarked, so “you don’t get to contract your way around a statutory mandate that the information be handed over” [38].

Department of Basic Education policy-makers seem unprepared to handle digital privacy issues. Tefo said that “we can’t invade learners’ privacy unless we can confirm these learners are accessing undesirable sites” [39]. When asked about NSA and U.S. corporate surveillance, with a case example of Google hosting school e-mail, Tefo responded, “those are areas that we are grappling with and we have not yet established norms to a point where we can become comfortable where we have a controlled environment” [40]. Tefo’s comments skirt the issue that the state is requiring school members to use privacy-violating services — such as those offered by Google and Microsoft — and fails to address plans for the DBE Cloud despite the fact that there are high-quality alternatives to surveillance-based services in education.

According to Tefo, it is too expensive for the government to protect the privacy of learners. He remarked that South African officials have “safe platforms” but “for schools you can imagine it requires huge resources to create a safe platform”. When the e-education program moves along, he said, “we will have to mitigate” these issues as they are “the gaps that we must close” [41].

When asked about foreign and corporate surveillance, Richard responded:

I hear your question. You’re far ahead. You’re so far ahead, but you know, I don’t know what I’d do, because, I mean, we haven’t even got there. I think we need to deal with ... the basic stuff, and then you get the more complicated stuff ... Maybe 2019 we’ll be there where you’re talking about. But it’s not that we’re not aware of these things, but we are not prioritizing our minds [for these issues]. [42]

Richard said the DBE had just drafted a document on e-theft, but he doesn’t know “whether any of the aspects that you are talking about [are] actually covered in this document”. Richard added that “we’re not going to be opening up the information of learners to the general public or just anybody — we’re going to be using private networks”. He said the DBE needs to “[protect] those learners and the user of the education system from what would happen if the information is out”. Privacy solutions are “being considered”, he insisted, and the DBE “actually do need to conform to that” [43].

Richard’s remarks ignore that software like Google Android and Microsoft Office 365 run off Google- and Microsoft-owned clouds. The information is necessarily “out” as a function of using their services and, it must be assumed, accessible to — if not wholly collected by — foreign intelligence. Like Tefo, Richard holds a contradiction: he endorses privacy protection without ruling out software choices that violate user privacy. Herman, Tefo, and Richard suggest solutions which cannot secure the privacy of e-education users. As it stands, the South African government is moving towards placing most of its population under bulk surveillance through foreign corporations and government intelligence agencies, in addition to their own surveillance through services like the DBE Cloud.

 

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Problem #2: Chilling effects

The second problem with big data e-education is the likely “chilling effect” on informed participants. According to a large body of research, surveillance chills free speech and inquiry. Study after study shows individuals conform to the expectations of the status quo when they know they are being watched. It reasonable to expect that pervasive data collection will curb the speech, inquiry, and behavior of learners and educators if they know their activity is under corporate and government surveillance.

In a widely publicized study, Penney (2016) demonstrated that “government surveillance and similar actions impact online activities, including access to information and knowledge online” [44]. Penney found that traffic to Wikipedia decreased after news about the NSA/PRISM program broke in June 2013. His study looked at Wikipedia Web traffic to items associated with terrorism and national security on the Department of Homeland Security list — items that people may not want to visit if they are being watched by their government. After independently testing the 48 chosen terms and applying a control group, Penney found an immediate, highly significant drop in traffic to the 48 pages among Wikipedia users — an estimated several million in the dataset — directly after the June 2013 revelations. Specifically, page views for terrorism-related articles (e.g., “Al Qaeda”) sharply dropped upon the June 2013 revelations and remained low over time, while page views from control groups, such as domestic security-related articles (e.g., “Port Authority”) and popular Wikipedia articles (e.g., “2014 FIFA World Cup”) did not. Penney concluded fears about government surveillance had “a salient and observable chilling effect on Wikipedia users accessing certain Wikipedia articles” [45].

Other recent studies have found chilling effects on speech and behavior induced by surveillance. These include a similarly structured but shorter-term study which found an impact on terrorism-related and personally embarrassing Google searches after the NSA/PRISM revelations (Marthews and Tucker, 2017); two PEN America survey studies which found reports of severe self-censorship in writing, conversation, and inquiry (PEN America, 2015, 2013); and a 2016 study of Facebook which found that certain types of individuals are prone to conformist political posting when they believe they are being monitored (Stoycheff, 2016). In South Africa, a study by Admire Mare (2016) found that South African activists, journalists, lawyers, and academics are self-censoring their career and personal political activities, expression, and communications in response to the experience or threat of surveillance.

This should be of major concern to any use of surveillance-based services in school. Studies on machine learning and other statistical techniques profiling users reveal that striking facts can be learned about people from limited samples of their digital footprint: Web searches, Facebook likes, purchases, telephone call records, and other forms of metadata.

In a study of 86,220 volunteers, Youyou, et al. (2015) found that computer predictions based on Facebook likes were more accurate than those made by participants’ Facebook friends using a personality questionnaire. In addition, they found computer-based personality judgments have higher external validity when predicting life outcomes such as drug use, political attitudes, and physical health — in some instances even better than self-rated scores.

The test measured personality traits like openness, conscientiousness, extraversion, agreeableness, and neuroticism. Computer models needed 10, 70, 150, and 300 Likes to outperform an average work colleague, cohabitant or friend, family member, and spouse, respectively. For external criteria (real-life behavior, behaviorally-related traits, and life outcomes), computers outperformed humans across 12 of 13 categories, including depression, impulsivity, substance abuse, and network size.

Studies like these abound, covering how samples from sources of data (such as Twitter data, telephone metadata, web browsing, and search history) yield various types of inferences (age, gender, occupation level, sexual orientation, predictions about parental divorce, pregnancy, suicidal thoughts, specific medical conditions, identities of intimate partners, religious affiliation, and more) (Kosinski, et al., 2013). Awareness of big data education services’ capacity to profile and predict individual personalities and behaviors could severely curb educational freedom.

South African interview subjects often contended that learner and educator privacy is safeguarded by “de-identification”. This was frequently mentioned by government policy-makers and key stakeholders in response to questions about how to protect privacy. However, studies show the triviality of re-identifying datasets by cross-referencing de-identified data with a few known quasi-identifiers (such as sex, zip code, and birthday) or other easily obtainable datasets (Narayanan and Shmatikov, 2008; de Montjoye, et al., 2015; Mayer, et al., 2016). This reaches consensus when richly detailed datasets are linked to individuals with persistent unique identifiers — a necessary feature for analytics that profile at the individual level [46]. An expert advisory report to the President of the United States thus held that because it is quite feasible to “re-identify” data, claims of data “anonymization” engender a “false expectation of privacy” [47].

If learners and teachers are forced to use government and corporate software services described above, they will be under heavy surveillance by their own government, foreign intelligence agencies, and corporate actors, with adverse effects on classroom participants. Nevertheless, South African policy-makers interviewed were dismissive of the surveillance threat to education freedom. When asked about a chilling effect, Richard responded that “you have to watch” and “guide” learners “otherwise they will view pornography or videos or social media” — a non-response to the question. Although he added, “yes you can do that by educating them, that would be the best, the ideal situation”, he failed to address concerns about chilling effects [48]. By contrast, Herman was not bothered by the suppression of speech and inquiry via surveillance. He simply said, “children need to be controlled”. If “political dissent” is threatened by surveillance, he added, “they can dissent at home” [49].

 

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Problem #3: Teacher autonomy

According to Columbian law professor Eben Moglen, privacy “combines three things: first is secrecy, or our ability to keep the content of our messages known only to those we intend to receive them. Second is anonymity, or secrecy about who is sending and receiving messages, where the content of the messages may not be secret at all.” This applies to both publishing and reading. “Third,” Moglen continues, “is autonomy, or our ability to make our own life decisions free from any force that has violated our secrecy or our anonymity” (Moglen, 2014).

The big data component of Operation Phakisa Education threatens the autonomy of school participants. South African teachers have been at loggerheads with the government over external inspectors since days of apartheid. In the past few years, teachers’ unions successfully defied government requests for biometric fingerprint attendance monitoring. As time goes on, however, real-time cloud-based analytics can accomplish the same surveillance goals and more — in a much more invasive fashion. The DBE is pushing cloud-based dashboard software such as the Michael & Susan Dell Foundation DDD Dashboard to monitor teachers and learners in their classrooms. This is a critical development, as teacher absenteeism and insufficient curriculum coverage are two of the most common complaints about school performance in mainstream discussions of SA education. Over 18,000 schools are now supported by the DDD team in seven provinces. Rachel (MSDF) expects that the entire country will be covered by the MSDF DDD Dashboard in the near future [50].

Chisholm (1999) provides examples of apartheid-era tactics used to control teachers’ work in black schools. In one instance, a deputy principal in a Soweto girls’ school explained, “Like in the past we used to have a record, a logbook. If a teacher doesn’t go to class, we’ll record that teacher didn’t go to class. If we record the teacher three times, we refer the matter to the inspector”. Control of black teachers, enforced through surveillance, was “direct and linked to official concerns with social control and departmental demands for loyalty and subservience” [51].

According to Chisholm:

The main concern with procedures for evaluation was monitoring and surveillance. These were performed on the basis of checklists which evaluated teachers in terms of four components: curricular efficacy, extra-curricular efficacy, personality and character traits, and professional disposition and attitude. In the context of growing resistance by teachers to apartheid education, the latter were increasingly used to assess and measure loyalty to the department controlling African education [52].

Recently, the government has been pushing to bring back “surprise school inspectors” to address teacher absenteeism and monitor curriculum coverage (Anthony, 2013; Masondo, 2016b). All of the major teachers’ unions rejected the proposal.

The latest digital technologies offer all of the same capabilities the apartheid state used to monitor and control black teachers. In the digital era, if the data is collected, analytics can be turned on at the flip of a switch. This means that teachers under the watchful eye of big data systems are perpetually threatened by a surveillance regime not experienced since the days of apartheid — one that is more invasive due to advances in technology.

When asked about surveillance of teachers through data analytics, Richard said that there will be tracking of teacher data, but:

We know ... how sensitive these things are, especially with the unions and we wouldn’t do that without their broader — without their knowledge. Teachers don’t like being monitored and if you’re going to monitor them they need to know why and as such if we’re going to be doing that — it depends on what you are going to be monitoring. Are you monitoring their attendance, in class? Are you intending on monitoring — for what? So ... you need to know what things you are monitoring. And you need to get that permission [for] their consent as to what you are monitoring. But we know the various aspects in which you do not dare try to monitor — that will get you into conflict with the teacher unions. So yes, we are not going to [be] monitoring the aspects that are controversial. If we are monitoring anything to do with this, they will definitely know. You can’t do anything without asking the unions [53].

This position relies on permanent trust as well as awareness of how new EdTech products work. Should cloud-based personalized/adaptive learning spread throughout the school system, the government will have a rich, real-time surveillance system under their control. With teachers now reliant upon computers for daily activities, the government would have increased their power to compel teachers to submit to surveillance analytics of the kind they are currently resisting.

The other government officials sampled in this paper were not asked about teacher monitoring specifically. However, they failed to raise the issue of teacher surveillance when asked about data monitoring — only learners were mentioned. This indicates a lack of consideration for the equally important issue of teacher autonomy. It is not clear that many policy-makers, teachers’ unions, or other basic education participants understand the surveillance dimension of big data education.

 

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Problem #4: Consent and democratic governance

South Africa has a weak capacity to adopt computer-based changes to its society through a democratic process. Many learners and their parental guardians are illiterate or cannot read well, and have little or no exposure to computer technology and Internet access beyond a feature phone on an EDGE network. Moreover, the mainstream media and academic circuit have mostly failed to engage the digital revolution, so there is little information published to raise awareness — at least in a South African context. The current capacity for activist, legal, and informed citizen engagement is remarkably low.

The unlikely prospect of democratic participation was expressed by SPARK Schools CEO Stacey Brewer, who said that in contrast to the United States, in South Africa, “We currently do not face red tape such as political resistance ... not having to carry the burden of issues such as these allow us to scale at pace with less barriers to entry” (Quattrocchi, 2014). Brewer’s private schools utilize EdTech in the classroom. She believes “Systematic market disruptions is [sic] needed immediately to ensure South Africa is able to take the steps necessary to accelerate the countries [sic] development” (Quattrocchi, 2014).

Privacy is a fundamental human right recognized in international law [54]. New developments in technology have drawn attention to privacy, with concern from human rights advocates, organizations, and the legal community. In April 2013, just prior to the Snowden revelations, the United Nations Special Rapporteur on Freedom of Expression and Opinion issued a report highlighting the dangers of digital-era surveillance to fundamental human rights (United Nations, General Assembly (UNGA), Human Rights Council, 2013). In July 2013, just after the Snowden leaks were published, the UN High Commissioner for human rights, Navi Pillay, warned that “surveillance without adequate safeguards to protect the right to privacy actually risk impacting negatively on the enjoyment of human rights and fundamental freedoms”. Pillay, who has served as a South African lawyer, judge, and human rights activist, remarked, “People need to be confident that their private communications are not being unduly scrutinized by the State”. She added, “The right to privacy, the right to access to information and freedom of expression are closely linked” (UN News Centre, 2013).

On 18 December 2013, the United Nations General Assembly (UNGA) adopted a resolution reaffirming the human right to privacy in the digital age, as set out in article 12 of the Universal Declaration of Human Rights and article 17 of the International Covenant on Civil and Political Rights (United Nations, General Assembly [UNGA], 2014a). The resolution noted that rapid advances in technology may offer new benefits to society, but they are also enabling violations of privacy by governments, companies, and individuals “which may violate or abuse human rights, in particular the right to privacy” (United Nations, General Assembly [UNGA], 2014a). In November 2014, the UNGA adopted a resolution once again reaffirming the right to privacy in the digital age, this time calling upon member States to review their legislation and polices to ensure they accord with human rights law (United Nations, General Assembly [UNGA], 2014b). In November 2016, the UNGA’s Third Committee yet again reaffirmed the right to privacy. This time they emphasized the protection against private sector abuses, expressing concerns about the sale and re-sale of personal data, transparency in company policy, and the need for informed consent. The resolution noted that privacy violations frequently have a disparate effect on women, children, and vulnerable or marginalized communities (Brown, 2016).

While the United Nations was working out privacy recommendations and resolutions, beginning in October 2012, over 40 experts in privacy and security commenced a series of its own meetings addressing digital-era surveillance. The drafting process included input from the United Nations Special Rapporteur, prominent electronic civil liberties organizations (such as Access Now, the Electronic Frontier Foundation, and Privacy International), NGOs, lawyers, and human rights advocates. They issued their first draft publication on 10 July 2013, “International Principles on the Application of Human Rights to Communications Surveillance” (also called the “Necessary and Proportionate Principles” or “The Principles”; a final version was issued in May 2014; see Necessary and Proportionate Coalition, 2014). Prominent South African organizations such as the Media Policy and Democracy Project have drawn upon the Necessary and Proportionate Principles to inform their analysis of South African surveillance (Mare with Duncan, 2015).

SA is also party to the African Charter on the Rights and Welfare of the Child. Article 10 ensures the right to privacy for the child — including protection against “arbitrary or unlawful interference” with the child’s privacy. Article 11 ensures that “a child who is subjected to schools or parental discipline shall be treated with humanity and with respect for the inherent dignity of the child and in conformity with the present Charter” (African Charter on the Rights and Welfare of the Child, 1990). Moreover, Section 14 of the Constitution of the Republic of South Africa, 1996, provides everyone the right to privacy, while the Constitution (section 39(1)(b)) provides that a domestic court, tribune, or forum must consider international law, including in the interpretation of legislation (Republic of South Africa, 1996).

On 27 April 2016, the Human Rights Commission (HRC) issued its final assessment of South Africa’s compliance with the International Covenant on Civil and Political Rights. The report followed submissions to the HRC by the Right2Know Campaign and Privacy International. The HRC echoed R2K and Privacy International’s concerns and suggested remedies pertaining to mass surveillance, data retention, and weaknesses in domestic law with respect to the right to privacy (United Nations, Human Rights Committee, 2016).

It remains to be seen how South Africa will reconcile state and private sector surveillance practices against commitments to privacy under international and domestic law. United Nations General Assembly resolutions are non-binding, thus states and civil society must apply pressure to bring them to life. Issues surrounding e-education are all the more pertinent when considering the importance of privacy to education and childhood development.

Other countries seem more capable of enforcing democratic checks on new technology. The American Civil Liberties Union, along with the Tenth Amendment Center, recently drafted model legislation calling for strict limitations on the data collection powers of EdTech vendors in the United States (Doran, 2016). There have been several incidents of legal action taken against Google for privacy violations, including in the education space [55]. A Google South Africa interview subject, Jill*, failed to answer most of the privacy questions asked pertaining to Google Apps for Education [56]. Many of my questions were crafted by the Electronic Frontier Foundation and U.S. Senator Al Franken with respect to Google Apps for Education (see Electronic Frontier Foundation [EFF], 2015; Franken, 2015). Questions about learner and teacher privacy are as relevant as in South Africa as they are in the United States. Yet in South Africa there is little awareness or pressure from the general public or legal community.

The South African government endorses community engagement and collaboration in its policy documents. The White Paper (2004) states, “Institutions must work in partnership with families and the wider community to ensure shared knowledge about ICTs and extended opportunities for learning and development through ICTs. Community engagement in ICT planning, implementing and monitoring is crucial for the formation, maintenance and security of an e-School” [57]. The National Planning Commission (2012) calls for “mutual accountability between schools and communities” [58]. The Department of Basic Education (2011) endorses “the need for a ‘social contract’ between government, teacher unions, teacher training institutions, parent and SGB organisations, business and civil society organisations” [59].

Despite these pronouncements, there is no public disclosure about the multitude of privacy problems accompanying Operation Phakisa Education. Government promises of democratic inclusion and transparency betray their present behavior. While they deem e-education “transformational”, new plans have been developed behind closed doors, the details of which remain secret. This is all the more problematic when considering that the poor black majority have little or no experience with personal computers. Open consultation with the public is essential if they are to have a chance to voice their opinions.

OPE incorporates many new technologies designed to overhaul the public education system. Some of the technologies have already been launched in classrooms across the country. Richard and Tefo both stated that the education sector is in its early phase of implementation, and that more “complicated” and advanced technologies will be developed and deployed in time. Tefo said the government aims to utilize more advanced data analytics by 2019. Tens of thousands of Grade 12 learners had already received tablets in the Gauteng province by 2015 (Shezi, 2016). Herman said 2019 is the target to connect all schools to broadband, while Richard hopes by 2019 the initial phase of the national e-education rollout will be completed.

Richard iterated that “we are not changing the [White Paper] policy because the policy is still very relevant — the output and the goals is to educate kids and the process is very relevant”. Revisions, he remarked, are “just an issue of ... maybe things [that] were not there, things like the tablets that kind of thing, but that’s not a big develop[ment], things you can’t accommodate in your plan. But in terms of the policy, its objective is fine” [60]. This sweeps aside the drastic changes to digital technology since the White Paper was published in 2004: the rise of cloud services, government mass surveillance programs, the big data revolution, the spread of mobile computing to the poor, the expanded power and market dominance of Silicon Valley corporations, growing prominence of free software, rapid development of artificial intelligence, and much more.

Sipho said there is a report on Operation Phakisa Education, but he has “no idea” when it will be out [61]. When asked if there will be a report released detailing OPE, Richard said “That depends on the President. The President will have to release it, and you can’t tell the President when to release something” [62].

As of mid-2017, there is still no report available on the OPE initiative [63]. There is some progress reported about the delivery of physical technology to schools. This includes the rolling out of 111 Education apps on the DBE Cloud and DBE Web site; the training of 21,467 teachers, 263 principals, and all provincial and district e-Learning officials in all nine provinces; the delivery of 98,307 devices (at 24 tablets and three laptops per school); and the rollout of broadband connectivity and a local server to 3,641 schools (surpassing the original target) [64] (Parliamentary Monitoring Group [PMG], 2017a; Parliamentary Monitoring Group [PMG], 2017b; Odendaal, 2017).

The education transformation agenda itself — including substantial information about the OPE initiative — remains hidden away from the public. Without clear and consistent reporting, outreach, and public consultation, OPE assumes an authoritarian form. The e-education rollout presents the most dramatic change to education since the transition to formal democracy. Yet it has been planned, shaped, and implemented by elites in the absence democratic participation.

 

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Alternatives: Technologies that respect user and community freedom

In 1986, the ANC and its paramilitary wing, Umkhonto we Sizwe (MK), launched Operation Vula — an initiative to bring exiled leaders and military capacity back into South Africa in support of a potentially armed movement against the apartheid state. Participants in Vula relied on an encrypted communication system they created to communicate safely across borders. The system was primarily built and operated by ANC underground activists Tim Jenkin and Ron Press, who wrote the one-time pad encryption software used to secure ANC/MK real-time electronic communications (Jenkin, n.d.). According to ANC members:

... the Vula communication system was used to coordinate meetings and actions, to debate strategy, to report operational outcomes, to share military and political intelligence, and much more. The ultimate effect was that operatives within South Africa had immediate access to powerful allies, while the South African government’s capacity to repress ANC communication was significantly reduced [65].

Encryption and software in the service of privacy thus played a pivotal role in the late ANC struggle against the apartheid state.

During the 1980s, a People’s Education for People’s Power movement was formed to counter apartheid education (Sisulu, 1987; National Education Crisis Committee, 1986; Mashamba, 1990). As South Africa moves into the digital age, the cultivation of what we might call People’s Technology for People’s Power could safeguard privacy in South Africa’s digital society.

There are many software tools available for privacy protection. If source code is open for inspection and modification by the public, it can be evaluated by public experts for security flaws or malicious features. For this reason, many privacy advocates endorse Free and open source software (FOSS) for computer security (e.g., Schneier, 1999; Snowden, 2016). The South African government has a FOSS policy preference for use in the public sector. Under this policy, proprietary software should only be used if it is demonstrated to be superior to FOSS alternatives. The policy holds that FOSS is best practice for security. In this regard, FOSS should be addressed by policy-makers for use in the classroom, in the interests of privacy and security.

Some public privacy guides could provide a useful starting point for e-education software (e.g., see https://ssd.eff.org). A distribution of GNU/Linux, such as Debian or Ubuntu [66], strikes an effective balance between usability and end-user security. For smartphones or tablets, Android variants like CopperheadOS offer secure alternatives to Google and OEM-supplied versions of Android. Respect for user privacy on these Android variants is also much better than Apple’s iOS and Windows 10 Mobile. E-mail services like ProtonMail and Tutanota could provide an alternative to providers like Google and Microsoft. The Tor browser could be used to protect student anonymity while browsing the Web. DuckDuckGo and StartPage can be encouraged as a substitute for surveillance-based search engines (such as Google Search, Yahoo, and Bing).

For e-administration, data analytics could be kept to a minimum. Methods such as random sampling could replace granular collection down to the individual level.

Educating users is critical to privacy protection. Critical awareness of how computer-based data collection and surveillance works — as well as the political history of surveillance — should be included in school curriculum and e-education training. Informing the public about surveillance in the digital age is necessary for transparent governance, accountability, democratic participation, and informed consent in the classroom. However, raising awareness presents a conundrum to current plans favored by South African policy-makers and stakeholders. Government and corporate surveillance is so far-reaching and invasive that any basic level of awareness will likely create a chilling effect detrimental to education, civil rights, and civil liberties. Time will tell if and how the government will respond to this dilemma.

 

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Conclusion — Operation Phakisa Education: A secret transformation

Digital technology could offer valuable resources to improve basic education in South Africa. Yet presently favored forms of e-education incorporate dangerous forms of state and corporate surveillance. This is all the more troubling given that the decision to fast-track e-education without broad public consultation stands in violation of government commitments to transparency and democratic process. It is not clear that the public would be happy about introducing mass surveillance into its public schools and households.

Surveillance has long been used in the United States and South Africa to service the interests of state and corporate power, with devastating consequences on oppressed peoples. New forms of surveillance are far more powerful than anything previously imagined. The extension of ubiquitous surveillance to education and childhood is a radical new development in human history. It has the potential to chill speech and inquiry, curb democratic forms of civic engagement, suppress popular movements and protest, and disturb he psyche of young people who will eventually learn that there is a detailed data trail capturing their life history.

Classroom freedom is likewise threatened as teachers become subjected to the watchful eye of state and corporate service providers. Under apartheid, state inspectors intruded on black teachers to monitor their behavior and enforce the status quo. With ubiquitous tracking of network activity and classroom activity, teachers face surveillance not experienced since the days of apartheid.

The dual purpose of Operation Phakisa Education — to transform education and to bridge the digital divide between the poor black majority and the wealthy white minority — serves laudable goals. Yet the implementation of surveillance-based software, devices, and services from the likes of Google, Microsoft, and Apple threatens to entrench their products in education and the general society. Hooking children and schools into surveillance-based corporate platforms can have deep and longstanding consequences for South Africa’s digital revolution. Freedom-respecting technologies could be chosen at the outset, and it will be difficult to switch once particular options are rooted deep inside the school system. A discussion about People’s Technology for People’s Freedom has never been more pressing in South Africa.

A privacy policy covering specific technologies for schools can help address the problems outlined in this paper. Such a policy could be tabled for public consultation and clarify the government’s position on privacy in education and society. Privacy-respecting alternatives to corporate software and services are available for use in education.

It will take time to equip the public with the knowledge necessary to understand the privacy implications accompanying e-education. State and commercial surveillance, chilling effects, the undermining of teacher autonomy, lack of democratic process, and the potential for civil rights and liberties violations all present serious challenges to the future of South Africa. OPE is designed to transform post-apartheid education, but its current trajectory can have disastrous consequences. At bare minimum, an informed public should have a say. If democracy is a cornerstone of South African society, the government must disclose the details surrounding Operation Phakisa Education and address the privacy issues explored in this paper. End of article

 

About the author

Michael Kwet is a Visiting Fellow at Yale Privacy Lab (https://privacylab.yale.edu), an initiative of the Information Society Project at Yale Law School, and a Ph.D. candidate at Rhodes University.
E-mail: michael [dot] kwet [at] yale [dot] edu

 

Notes

1. Tshimanika, 2014, p. 3; Nkosi, 2015.

2. National Planning Commission (NPC), 2012, p. 27; Department of Basic Education, 2011, p. 24; Motshekga, 2014.

3. South Africa Institute of Race Relations (SAIRR), 2016, p. 437.

4. Van der Berg, et al., 2016, pp. 5, 14. There is variation by province: “in the Western Cape only 11% of students were illiterate and 27% could not read for meaning. In Limpopo 50% were illiterate and 83% could not read for meaning at the end of grade 4” — van der Berg, et al., 2016, p. 16.

5. Van der Berg, et al., 2016, p. 22.

6. Human Sciences Research Council (HSRC), 2012; Department of Basic Education, 2011, pp. 73–75.

7. Department of Basic Education, 2014, pp. 66, 70–71. The ANAs were eventually canceled due to popular teacher resistance. They will be replaced by a new assessment instrument, the National Integrated Assessment Framework (NIAF), to take place once every three years starting in 2018.

8. Department of Basic Education, 2011, p. 22.

9. A small collection of voices who work for or studied at Stellenbosch University are frequently published and referenced in the press and academia. Some of them endorse the “human capital” theory of education and economy as “received wisdom” (Spaull, 2011). For criticisms of the human capital theory of education in a South African context, see Vally and Motala, 2014.

10. Teacher absences are highest in the two poorest provinces, KwaZulu-Natal and Eastern Cape, suggesting a link to poverty (Department of Basic Education, 2015, p. 37).

11. The 2007 SACMEQ examinations showed that “only 32 percent of Grade 6 mathematics teachers in South Africa had desirable subject knowledge in mathematics” (Hungi, et al., 2011, p. 52, as cited in van der Berg, et al., 2016, p. 44). Once again, variation is high: Mpumalanga had just four percent whereas the Western Cape had 64 percent (van der Berg, et al., 2016, p. 8).

12. In 2016, the Minister of Basic Education, Angie Motshekga, commissioned a task team to investigate the sale of “jobs for cash” by members of teachers’ unions. The “Volmink Report” alleged there is widespread and systematic corruption in educator post provisioning due to the power and influence of teachers’ unions. The unions accept that corruption sometimes occurs, but deny any systematic corruption.

13. The Johannesburg Lab was preceded by a two-week Challenge Scoping Lab hosted by the Global Knowledge Initiative (GKI), World Bank, and South African government, with a variety of stakeholders in attendance (Global Knowledge Initiative, 2016).

14. For details on the Operation Phakisa Education project, see http://www.operationphakisa.gov.za.

15. Government and some other interview subjects opted to have their identities protected. In this paper, I assign those interview subjects pseudonyms.

16. * indicates a pseudonym chosen to protect the identity of the interview subject.

17. Richard, personal interview, 14 June 2016.

18. While this is a very simplified explanation of how Knewton works, it provides a general approximation.

19. While Ferreira did not specify the extent of “other people’s data sets”, he recommended to a public audience that they spider the web and scrape public data from Facebook, Twitter, and other Web services that could be used against users to profit from insurance (Ferreira, 2013).

20. Stephen*, personal interview, 30 September 2016; Rachel*, personal interview, 7 October 2016.

21. Herman, personal interview, 9 October 2015.

22. Richard, personal interview, 14 June 2016.

23. Tefo, personal interview, 28 September 2016.

24. In South Africa, kaffir is a derogatory term to referring to black people.

25. Witwatersrand Chamber of Mines, Johannesburg, S.A.R., 1897, p. 44; see also, Breckenridge, 2014, pp. 67–68.

26. Breckenridge, 2014, pp. 138–163.

27. Breckenridge, 2014, p. 157.

28. McCoy, 2009, pp. 312–316, 342–345.

29. The tech world was furious when Snowden leaks revealed the NSA created secret backdoors and undermined encryption systems and standards. For example, the random number generator Dual_EC_DRBG included a backdoor undermining the encryption standard that used it (Zetter, 2013). Dual_EC_DRBG was formally adopted by the U. S. National Institute of Standards and Technology (NIST) in 2006 and used as the default random number generator in the BSAFE software library of corporate giant RSA Security. During that period, the NSA had a secret US$10 million contract with RSA Security; technologists and electronic civil liberty advocates believe the NIST and RSA colluded with the NSA to undermine public encryption (Menn, 2013).

30. Grothoff, et al., 2015, p. 1. As Grothoff, et al. (2015) explain, “This allows passive attackers to monitor the queries of [Internet] users and see which services they are using and which websites they are visiting. For an active attacker, DNS facilitates locating potentially vulnerable services, which is the first step to their subsequent exploitation with commercially available 0-day attacks” (p. 1).

31. Ostensibly, this applies to groups along lines of sex, gender, nationality, religion, and other demographics.

32. In response to pressure from policy-makers and civil rights activists, Facebook decided to “stop letting marketers run housing, employment, and credit ads that target or exclude users by racial and ethnic identity on the social network” (Peterson, 2016; see also, Egan, 2016). Nevertheless, this maintains the “ethnic affinity solution” for various categories of advertisements.

33. Holt, 2010, p. 55.

34. Ibid.

35. Sipho, personal interview, 8 October 2015.

36. Herman, personal interview, 9 October 2015.

37. Schneier, personal interview, 18 January 2016.

38. Cohn, personal interview, 11 November 2015.

39. Tefo, personal interview, 28 September 2016.

40. Tefo, personal interview, 28 September 2016.

41. Tefo, personal interview, 28 September 2016.

42. Richard, personal interview, 14 June 2016.

43. Richard, personal interview, 14 June 2016.

44. Penney, 2016, p. 117.

45. Penney, 2016, p. 168.

46. Narayanan and Felton, 2014, pp. 1–2.

47. PCAST, 2014, p. 39.

48. Richard, personal interview, 14 June 2016.

49. Herman, personal interview, 9 October 2015.

50. Rachel, personal interview, 7 October 2016.

51. Chisholm, 1999, p. 115.

52. Chisholm, 1999, pp. 115–116.

53. Richard, personal interview, 14 June 2016.

54. See especially the Universal Declaration of Human Rights, article 12 and the International Covenant on Civil and Political Rights, article 17.

55. Public Citizen, 2014, pp. 33–34.

56. Jill, personal interview, 8 March 2016.

57. White Paper, 2004, p. 32.

58. National Planning Commission, 2012, p. 295.

59. Department of Basic Education, 2011, pp. 29–30.

60. Richard, personal interview, 14 June 2016.

61. Sipho, personal interview, 8 October 2015.

62. Richard, personal interview, 14 June 2016.

63. By contrast, there have been detailed reports released for Operation Phakisa Oceans Economy and Operation Phakisa Health.

64. Just over half of all public schools are now connected to the Internet; (ITWeb, 2017).

65. Garrett and Edwards, 2007, p. 15.

66. Ubuntu has been criticized for collaborating with Amazon to collect data (Brodkin, 2012). If protection against unnecessary commercial data collection is valued for schools, any distribution of Ubuntu chosen should not include that feature.

 

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Appendix

Interview subjects

* indicates a pseudonym.
Policy-makers listed occupy high-level positions in their departments.

Herman* (Department of Telecommunications and Postal Services)
Interview date: 9 October 2015
Herman works on issues related to devices and network connectivity for education at the National DTPS.

Sipho* (Department of Basic Education)
Interview date: 8 October 2015
Sipho works on e-education at the National DBE.

Richard* (Department of Basic Education)
Interview date: 14 June 2016
Richard works on e-education at the National DBE.

Tefo* (Gauteng Department of Education)
Interview date: 28 September 2016
Tefo works on e-education at the GDE.

Cindy Cohn (Electronic Frontier Foundation)
Interview date: 10 November 2015
Cindy Cohn is the Executive Director of the Electronic Frontier Foundation and a civil liberties attorney specializing in digital technology law. From 2000–2015, she was Legal Director and General Counsel at the EFF. Cohn serves as counsel in cases challenging NSA surveillance; she has worked on many high-profile cases. She is a member of the Board of Directors for the Tor Project. Cohn is has been named one of the most influential lawyers in the United States, and is the recipient of numerous awards.

Bruce Schneier (Harvard Berkman Center, Tor, IBM)
Interview date: 18 January 2016
Bruce Schneier is a world-class expert on cryptography and computer security, privacy specialist, and popular author. Schneier wrote a classic work for engineers in the field of cryptography. He helped journalist Glenn Greenwald review Edward Snowden’s NSA documents, and was asked to brief members of the U.S. Congress about NSA activities. Schneier has previously worked for the government (Department of Defense) and private industry (he currently works for IBM). He is a fellow at the Berkman Center for Internet & Society at Harvard Law School, a Program Fellow at the New America Foundation’s Open Technology Institute, a member of the Board of Directors of the Tor Project, and a board member at the Electronic Frontier Foundation.

Jill* (Google SA)
Interview date: 7 March 2016
Jill works on e-education for Google South Africa. At the time of our interview, Jill said Google for Education has a tiny staff in South Africa.

Stephen* (Michael & Susan Dell Foundation)
Interview date: 30 September 2016
Stephen works on K-12 education and innovation, as well as post-secondary youth employment, for the MSDF Data Driven Districts project.

Rachel* (Michael & Susan Dell Foundation)
Interview date: 7 October 2016
Rachel works on the MSDF Data Driven Districts education portfolio, the largest program of the Data Driven Districts project.

 


Editorial history

Received 2 August 2017; revised 15 November 2017; accepted 25 November 2017.


Creative Commons License
This paper is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

Operation Phakisa Education: Why a secret? Mass surveillance, inequality, and race in South Africa’s emerging national e-education system
by Michael Kwet.
First Monday, Volume 22, Number 12 - 4 December 2017
http://firstmonday.org/ojs/index.php/fm/article/view/8054/6585
doi: http://dx.doi.org/10.5210/fm.v22i112.8054





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