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Big Data and Electoral Politics in India

What happens when big data and big politics collide?  One answer arises from a recent study of big data in the electricity distribution sector in an Indian state: “Exploring Big Data for Development: An Electricity Sector Case Study from India”.

[1]

The state electricity corporation has introduced millions of online digital meters that measure electricity flow along the distribution network and down to the level of consumers.  Producing a large stream of real-time data, these innovations should have addressed a critical problem in India: theft / non-payment by consumers which creates losses up to one-third of all supplied power.  But they did not.  Why should that be?

Big data does reduce some losses: technical losses from electrical resistance and faults are down; payment losses from urban consumers are down.  But the big data era has seen an unprecedented expansion of rural electrification, and in rural areas, payment losses have risen to 50% or more.  In other words, the corporation receives less than half the revenue it should given the electricity it is supplying to rural areas.

The expansion in rural electrification has been mandated by politicians.  The high level of rural payment losses has been condoned by politicians, given significant positive association between levels of electricity non-payment and likelihood of seat retention at an election.

Is this the silencing of big data in the face of big politics: the capability for accurate metering and billing of almost all consumers simply being overridden by electoral imperatives?  Not quite, because big data has been involved via an offsetting effect, and an epistemic effect.

  1. Offsetting Effect. Big data-driven technical and urban consumer loss reductions have allowed the State Government to “get away” with its political approach to rural electrification. The two effects of technical/urban loss reduction and political loss increase have roughly balanced one another out; a disappointing aggregate outcome but one that just falls under the threshold that would trigger some direct intervention by the regulators or by Central Government.
  2. Epistemic Effect. Big data creates a separate virtual model of phemonena: a so-called “data double”. This in turn can alter the “imaginaries” of those involved – the mental model and worldviews they have about the phenomena – and the wider discourse about the phenomena.
    This has happened in India.  Big data has created a new imaginary for electricity, particularly within the minds of politicians.  Before big data, the policy paradigm was one that saw electricity in terms of constraint: geographic constraint such that not all areas could be connected, and supply constraint such that “load-shedding” – regular blackouts and brownouts – was regarded as integral.
    After big data, the new paradigm is one of continuous, high-quality, universal electricity.  Plans and promises are now based on the idea that all districts – and all voters – can have 24 x 7 power.

In sum, one thing we know of digital systems is that they have unanticipated consequences.  This has been true of big data in this Indian state.  Far from reducing losses, the data-enabled growth in electricity connectivity has helped fuel a politically-enabled growth in free appropriation of electricity.

For further details, please refer to the working paper on this topic.

[1] Credit: Jorge Royan (Own work) CC-BY-SA-3.0, via Wikimedia Commons https://commons.wikimedia.org/wiki/File:India_-_Kolkata_electricity_meters_-_3832.jpg

Manchester School of Computer Science team returns from teaching in Malawi

19 July 2017 1 comment

An outreach team from the University of Manchester’s School of Computer Science has returned from a pilot project in Malawi, teaching computing in schools in the North of the country.

It was a great experience all round, for the staff, CS students and schoolteachers on the team, and for the schools, where we met real enthusiasm from the teachers and from the schoolchildren too, who engaged well with the subject despite never having touched a computer, or even a keyboard before! They requested we taught throughout the weekends as well, which we did. The message for next year is “bigger and better”, and planning has already begun.

You may read more in a Report on the Project, with insights into some key issues that arose including pedagogic approach, infrastructure, language, gender inequalities, and sustainability and scalability of impact.

There will be a Computer Science seminar in which we will show what was done, discuss the experience, and debate the value of such an intervention in a very unequal world: 2pm, Wednesday 27th September 2017, Kilburn Building, room LT 1.5, Oxford Road, University of Manchester.

Categories: Teaching ICT4D Tags: ,

The Affordances and Impacts of Data-Intensive Development

What is special about “data-intensive development”: the growing presence and application of data in the processes of international development?

We can identify three levels of understanding: qualities, affordances, and development impacts.

A. Data Qualities

Overused they may be but it still helps to recall the 3Vs.  Data-intensive development is based on a greater volume, velocity and variety of data than previously seen.  These are the core differentiating qualities of data from which affordances and impacts flow.

B. Data Affordances

The qualities are inherent functionalities of data.  From these qualities, combined with purposive use by individuals or organisations, the following affordances emerge[1]:

  • Datafication: an expansion of the phenomena about which data are held. A greater breadth: holding data about more things. A greater depth: holding more data about things.  And a greater granularity: holding more detailed data about things.  This is accelerated by the second affordance . . .
  • Digitisation: not just the conversion of analogue to digital data but the same conversion for all parts of the information value chain. Data processing and visualisation for development becomes digital; through growth of algorithms, development decision-making becomes digital; through growth of automation and smart technology, development action becomes digital.  Digitisation means dematerialisation of data (its separation from physical media) and liquification of data (its consequent fluidity of movement across media and networks), which underlie the third affordance . . .
  • Generativity: the use of data in ways not planned at the origination of the data. In particular, data’s reprogrammability (i.e. using data gathered for one purpose for a different purpose); and data’s recombinability (i.e. mashing up different sets of data to get additional, unplanned value from their intersection).

C. Data-Intensive Development Impacts

In turn, these affordances give rise to development impacts.  There are many ways in which these could be described, with much written about the (claimed) positive impacts.  Here I use a more critical eye to select four that can be connected to the concept of data (in)justice for development[2]:

i. (In)Visibility. The affordances of data create a far greater visibility for those development entities – people, organisations, processes, things, etc. – about which data is captured. They can more readily be part of development activity and decision making.  And they can also suffer loss of privacy and growth in surveillance from the state and private sector[3].

Conversely, those entities not represented in digital data suffer greater invisibility, as they are thrown further into shadow and exclusion from development decision-making.

Dematerialisation and generativity also make the whole information value chain increasingly invisible.  Data is gathered without leaving a physical trace.  Data is processed and decisions are made by algorithms whose code is not subject to external scrutiny.  The values, assumptions and biases inscribed into data, code and algorithms are unseen.

ii. Abstraction. A shift from primacy of the physical representation of development entities to their abstract representation: what Taylor & Broeders (2015) call the “data doubles” of entities, and the “shadow maps” of physical geographies. This abstraction typically represents a shift from qualitative to quantitative representation (and a shift in visibility from the physical to the abstract; from the real thing to its data imaginary).

iii. Determinism.  Often thought of in terms of solutionism: the growing use of data- and technology-driven approaches to development.  Alongside this growth in technological determinism of development, there is an epistemic determinism that sidelines one type of knowledge (messy, local, subjective) in favour of a different type of knowledge (remote, calculable and claiming-to-be-but-resolutely-not objective).  We could also identify the algorithmic determinism that increasingly shapes development decisions.

iv. (Dis)Empowerment. As the affordances of data change the information value chain, they facilitate change in the bases of power. Those who own and control the data, information, knowledge, decisions and actions of the new data-intensive value chains – including its code, visualisations, abstractions, algorithms, terminologies, capabilities, etc – are gaining in power.  Those who do not are losing power in relative terms.

D. Review

The idea of functionalities leading to affordances leading to impacts is too data-deterministic.  These impacts are not written, and they will vary through the different structural inscriptions imprinted into data systems, and through the space for agency that new technologies always permit in international development.  Equally, though, we should avoid social determinism.  The technology of data systems is altering the landscape of international development.  Just as ICT4D research and practice must embrace the affordances of its digital technologies, so data-intensive development must do likewise.

[1] Developed from: Lycett, M. (2013) ‘Datafication’: making sense of (big) data in a complex world. European Journal of Information Systems, 22(4), 381-386; Nambisan, S. (2016) Digital entrepreneurship: toward a digital technology perspective of entrepreneurship, Entrepreneurship Theory and Practice, advance online publication

[2] Developed from: Johnson, J.A. (2014) From open data to information justice. Ethics And Information Technology, 16(4), 263-274; Taylor, L. & Broeders, D. (2015) In the name of development: power, profit and the datafication of the global South. Geoforum, 64, 229-237; Sengupta, R., Heeks, R., Chattapadhyay, S. & Foster, C. (2017) Exploring Big Data for Development: An Electricity Sector Case Study from India, GDI Development Informatics Working Paper no.66, University of Manchester, UK; Shaw, J. & Graham, M. (2017) An informational right to the city? Code, content, control, and the urbanization of information. Antipode, advance online publication http://onlinelibrary.wiley.com/doi/10.1111/anti.12312/full; Taylor, L. (2017) What Is Data Justice? The Case for Connecting Digital Rights and Freedoms on the Global Level, TILT, Tilburg University, Netherlands  http://dx.doi.org/10.2139/ssrn.2918779

[3] What Taylor & Broeders (2015) not entirely convincingly argue is a change from overt and consensual “legibility” to tacit and contentious “visibility” of citizens (who now morph into data subjects).

 

ICT4D Course Curriculum and Teaching Materials

The draft materials below are for use in conjunction with the textbook, “Information and Communication Technology for Development (ICT4D)” under publication as part of the Routledge Perspectives on Development series.

They are designed for use in a ten-session teaching module consisting of nine teaching sessions plus one external visit / speaker / lab session.  For each teaching session, a set of PowerPoint slides is provided including notes on session content and class exercises.

ICT4D Course Introduction

Session 1: Understanding ICT4D

Session 2: Foundations of ICT4D

Session 3: Implementing ICT4D

Session 4: ICTs and Economic Growth

Session 5: ICTs, Poverty and Livelihoods

Session 6: ICTs and Social Development

Session 7: e-Governance and Development

Session 8: ICTs and Environmental Sustainability

Session 9: The Future of ICT4D

If used as presented, the material is suitable for a two/three-hour interactive session including a mix of presentation, class questions and class exercises.  Alternatively, the presentation material only can be presented in a c.one-hour lecture session with exercises and discussion left for a separate c.one-/two-hour tutorial session.

Categories: Teaching ICT4D Tags: ,

The Demographics of Digital Development

13 April 2017 2 comments

Any emergent digital development paradigm will be shaped by three changing demographics of ICT usage: geographical, maturational and experiential.

Geographically, we have already moved from domination of the old Internet world (the US and Europe) to domination of the new Internet world (emerging nations of the global East and South), as summarised in the table below[1].  Use of digital technology in developing countries[2] now represents the majority not minority global experience.

 

Region % Share in 2001 % Share in 2017
RISING SHARE
Africa 1% 9%
Middle East 1% 4%
Latin America/Caribbean 5% 10%
Asia 32% 50%
FALLING SHARE
North America 30% 9%
Oceania 2% 1%
Europe 29% 17%

Regional Share of Global Internet Users (2001, 2017)

 

Maturationally, there are growing numbers of digital natives: defined as those 15-24 year olds with five or more years of online experience[3].  While only around one-fifth of the youth cohort in developing countries are digital natives (compared to four-fifths in the global North), youth in the global South as twice as likely to be digital natives as the total population, and so they have a disproportionate role which might be worth specific encouragement.  Given they see ICTs as more important and more beneficial than others do, and given they make proportionately greater use of digital technologies and of social networks, then engagement of digital natives – for example in education or politics – may be enhanced by ensuring there are effective digital channels in these sectors.

Experientially, ICT users are experiencing changes that include[4]:

  • Time-space compression: a shortening of timespans for activities moving towards Castells’ notion of “timeless time” in which biological and clock time are replaced by compressed, desequenced notions of time; and a new geography that replaces physical distance with virtual space so that individual experience moves from a “space of places” to a “space of flows”[5].
  • Public to private: moving from shared-use to individual-use models of ICT interaction. Voice communication is moving from public payphones to shared mobile phones to individually-owned mobile phones.  Internet access is moving from public access telecentres and cybercafés to semi-public home or work computers to personal mobile devices.  The digital experience thus becomes increasingly private and personal.
  • Fixed to mobile: as mobile devices become the dominant means of access to digital infrastructure and content.
  • Text/audio to audio-visual: while it may be premature to call the emergence of a post-literate society, increasing bandwidth and technical capabilities mean digital experiences can increasingly resemble rich, natural real-life experiences rather than the artificial restrictions of just text or just audio.

One can argue that all four cases, represent an increasing presence yet decreasing visibility of the digital as its mediation merges more seamlessly into everyday life and activities.  This growth-but-disappearance of mediation thus represents a final experiential trend – that digital technologies more-and-more intercede between us and our experiences, and yet we notice them doing this less-and-less.  If the medium is the message, our conscious awareness of the message may be diminishing.

All three of these trends – geographical, maturational and experiential – form the emerging background underlying digital development, which is the subject of a Development Informatics working paper: “Examining “Digital Development”: The Shape of Things to Come?”, and will be the topic for future blog entries.

[1] IWS (2017) Internet Usage Statistics, Internet World Stats http://www.internetworldstats.com/stats.htm

[2] http://www.oecd.org/dac/stats/daclist.htm

[3] ITU (2013) Measuring the Information Society 2013, International Telecommunication Union, Geneva http://www.itu.int/en/ITU-D/Statistics/Pages/publications/mis2013.aspx

[4] Barney, D. (2004) The Network Society, Polity Press, Cambridge, UK; Boettiger, S., Toyama, K. & Abed, R. (2012) Natural obsolescence of Village Phone, in: ICTD’12, ACM, New York, NY, 221-229; Molony, T. (2012) ICT and human mobility: cases from developing countries and beyond, Information Technology for Development, 18(2), 87-90; Ridley, M. (2009) Beyond literacy, in: Pushing the Edge, D.M. Mueller (ed), American Library Association, Chicago, IL, 210-213

[5] Castells, M. (2000) Materials for an exploratory theory of the network society, British Journal of Sociology, 51(1), 5-24

Technology Foundations for Digital Development

If there is to be a coming digital development paradigm, on what technologies will it be based?

Mobile, broadband, and mobile broadband (hence smartphones and tablets) will be a key foundation for the digital development paradigm.  They are already present or rapidly diffusing in developing countries.

As these diffuse, cloud, social media and other Web 2.0 applications necessary for digital platforms will become dominant.  The highest growth rates for cloud are already in the global South[1].  Social media is already dominated by the global South: by 2016 North America and Europe made up just 26% of global social network users, with 52% in Asia (including Oceania), 13% in Central/South America, and 9% in the Middle East and Africa[2].

Looking further ahead, of technologies likely to have a significant impact on development, the Internet of things is a main contender: the online connectivity of increasing numbers of objects.  The main growth area – 50 billion devices predicted by 2020[3] – is seen to be two types of connection.  First, stand-alone sensors – for example providing agricultural readings from fields, or medical readings from health centres.  Second, sensors integrated into mainstream objects from cars and refrigerators to toilets and shoes.

All these applications become smart when they move from a passive ability to collect and transmit data to an active ability to take a decision and action on the basis of that data: smart irrigation systems that automatically water dry crops; smart electricity grids that automatically isolate and re-route around transmission failures.   Even more than cloud, smart systems bring significant potential to increase efficiency and effectiveness of infrastructure and business, alongside significant potential to increase dependency and vulnerabilities to cybercrime and surveillance[4].

Digital ICTs have already moved us along the time dimension to a world of 24/7 everywhen connectivity (see Figure 1[5]).  Thanks to telecommunications advances, anywhere can now be connected, and we are slowly erasing the blank spaces on the digital map and moving towards everywhere being connected.  In terms of nodes, pretty well anyone and anything could now be connected thanks to ubiquitous computing.  There is still a very long way to go but within a generation almost everyone will be connected, and we will be steadily moving closer to everything being connected thus vastly multiplying the number of “points of potential control, resistance, and contestation”[6].

Figure 1: The Growing Domain of Digital Connectivity

We can therefore think of three generations of technological infrastructure for digital development (see Figure 2).  The first, already well-rooted, is based largely around mobile devices.  The second, currently emerging, is based around digital platforms and the Internet including Web 2.0 applications.  The third, currently nascent, will be based around a ubiquitous computing model of sensors, embedded processing and near-universal connectivity, and widespread use of smart applications.

Figure 2: The Generations of Digital Infrastructure for Development

Digital development is the subject of a Development Informatics working paper: “Examining “Digital Development”: The Shape of Things to Come?”, and is the topic for other blog entries.

 

[1] UNCSTD (2013) Issues Paper on ICTs for Inclusive Social and Economic Development, UN Commission on Science Technology and Development, Geneva

[2] WAS (2016) Digital in 2016, We Are Social, Singapore

[3] Pew Research Center (2014) The Internet of Things Will Thrive by 2025, Pew Research Center, Washington, DC

[4] UNCSTD (ibid.)

[5] Adapted from ITU (2005) The Internet of Things, International Telecommunication Union, Geneva

[6] p24 of Deibert, R. & Rohozinski, R. (2012) Contesting cyberspace and the coming crisis of authority, in: Access Contested: Security, Identity, and Resistance in Asian Cyberspace, Deibert, R.J., Palfrey, J.G., Rohozinski, R. & Zittrain, J. (eds), MIT Press, Cambridge, MA, 21-41

An Emerging Digital Development Paradigm?

28 February 2017 5 comments

Taking a longer-term view, the relationship between digital ICTs and international development can be divided into three paradigms – “pre-digital”, “ICT4D”, and “digital development” – that rise and fall over time (see Figure below).

ict4d-paradigms

Changing Paradigms of ICTs and Development

 

The pre-digital paradigm dominated from the mid-1940s to mid-1990s, and conceptualised a separation between digital ICTs and development[1].  During this period, digital ICTs were increasingly available but they were initially ignored by the development mainstream.  When, later, digital technologies began to diffuse into developing countries, they were still isolated from the development mainstream.  ICTs were used to support the internal processes of large public and private organisations, or to create elite IT sector jobs in a few countries.  But they did not touch the lives of the great majority of those living in the global South.

The ICT4D paradigm has emerged since the mid-1990s, and conceptualised digital ICTs as a useful tool for development[2].  The paradigm arose because of the rough synchrony between general availability of the Internet – a tool in search of purposes, and the Millennium Development Goals – a purpose in search of tools.  ICTs were initially idolised as the tool for delivery of development but later began to be integrated more into development plans and projects as a tool for delivery of development.

The isolationism of the pre-digital paradigm remains present: we still find policy content and policy structures that segregate ICTs.  But integrationism is progressing, mainstreaming ICTs as a tool to achieve the various development goals.  From the development side, we see this expressed in national policy portfolios, in Poverty Reduction Strategy Papers, in UN Development Assistance Frameworks.  From the ICT side, we see this expressed in national ICT policies and World Summit on the Information Society action lines.

The ICT4D paradigm is currently dominant and will be for some years to come.  Yet just at the moment when it is starting to be widely adopted within national and international development systems, a new form is hoving into view: a digital development paradigm which conceptualises ICT not as one tool among many that enables particular aspects of development, but as the platform that increasingly mediates development.

This is the subject of a Development Informatics working paper: “Examining “Digital Development”: The Shape of Things to Come?”, and will be the topic for future blog entries.

 

[1] Heeks, R. (2009) The ICT4D 2.0 Manifesto: Where Next for ICTs and International Development?, Development Informatics Working Paper no.42, IDPM, University of Manchester, UK

[2] ibid.

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