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From ICT4D to D4D?

10 December 2014 13 comments

The UN Secretary General’s Synthesis Report on the Post-2015 Agenda was released on 4th December.  It’s just one document but could be bellwether of future development priorities.

It represents the culmination of a historical trajectory in the relative presence of “ICT” vs “data” in the development discourse.  As discussed in a more detailed post-2015 vs. MDG agenda analysis, ICTs outpolled data at the turn of the century in the Millennium Development Goals.  In early post-2015 development agenda documents, this reversed – data was mentioned three times more than ICTs.  In the Synthesis Report, the ratio is close to 10:1.  Data is mentioned 39 times; ICT just four times.

What would it mean if data replaces ICTs as the core focus for informatics[1] in international development?

For many years there have been concerns about the techno-centricity of ICT4D: the assumption that technology, alone, can be sufficient to generate development; and the failure to recognise the wider contextual factors that govern the impacts of technology.  Moving to a data-centric view helps a bit: it moves us to think about the stuff that technology handles, rather than the technology per se.

But it doesn’t help a lot.  As Information Systems 101 teaches, it is information, not data, that has value and adds value.  And a data-centric view is not inherently better than a techno-centric one at recognising the importance of context.  For both these reasons, as I’ve discussed earlier in this blog, it looks like many “data-for-development (D4D)” initiatives to date are stuck at the very first upstream step of the process – they produce data but only rarely produce results.

For the academic community working in the sub-discipline of development informatics, a relative shift from ICT4D to D4D will mean a requirement for new research focus and skills.  At the least, we will need to add new research projects and research competencies around data and decision sciences.  At the most, these might partly replace – at least in relative weight – technical computing activities and capabilities.

That reorientation will certainly be true of the practitioner community, leading to demand for new postgraduates programmes – MSc Data for Development and the like.  Just as with ICT4D, there will be a key role for practitioner hybrids – those with the ability to bridge between the world of data and the world of development – and a need for training programmes to help develop such roles.  Arguably the most valuable role – to some extent trailled in my work on ICT4D 2.0 – will be the development informatics “tribrid”, that bridges the three worlds of ICT, data systems, and development.

The existing academic wateringholes and channels of development informatics will need to respond.  In particular, the main ICT4D conferences and journals will need to decide whether to make a clear and strong extension of their remit into D4D.  Mark Graham and I have made a first step with the 2015 IFIP WG9.4 conference in Sri Lanka; adding a “Data Revolution in International Development” track.  This is an example of academic tribridisation: ensuring technology, data and development are covered in one place.  It will be interesting to see what the ICTD conference series, and the main journals, do about the coming D4D wave and whether they also tribridise.

Some of the policy and practice wateringholes have already responded.  One well-placed convocation is the World Telecommunication / ICT Indicators Symposium.  This has, for some time, covered data, ICT and development and could grow to become a key tribrid location.  More important but more difficult will be whether the WSIS follow-up process can do the same.  As previously analysed, and unless it takes some decisive action, WSIS runs the risk of seeing the data-for-development bandwagon roll past it.

There are no doubt other implications of the limelight shifting from ICT4D to D4D: do add your own thoughts.  These implications include value judgements.  Data is not the same as technology, and the international development agenda risks taking its eye off ICT just at the moment when a digital development paradigm is emerging; a moment when ICT moves from being a tool for development to the platform for development.

Without a better connection between D4D and ICT4D we also risk losing all the lessons of the latter for the former, and turning the clock back to zero for those now entering the development informatics field riding in the data caravan.  It is the privilege of those new to a field to believe they are reinventing the world.  It is the burden of those experienced in a field to know they are not.

[1] “Informatics” is the complex of data, information, knowledge, information systems, and information and communication technologies.

The Data Revolution Will Fail Without A Praxis Revolution

14 August 2014 6 comments

Pose the following to data-revolution-for-development activists: “Show me an initiative of yours that has led to scaled, sustained development outcomes”.

If – as likely – they struggle, there’s a simple reason.  We have not yet connected the data revolution to a praxis revolution for development.  The data revolution takes advantage of technical changes to deliver new volume, speed, and variety of data.  The praxis revolution makes changes to development processes and structures in order to turn that data into development outcomes.

Perhaps data activists never took, or fell asleep during, Information Systems 101.  Because the very first session of that course teaches you the information value chain.  You’ll find variants of the example below in Chapter 1 of most information systems textbooks.

New Info Value Chain

It explains that data per se is worthless.  Value – and development results – only derive from information used in decisions that are implemented as actions.  To make that happen you also need the intelligence to process the data into information; the imperative that motivates you to run the whole chain through; and the soft capabilities and hard resources to access data and take action[1].

It is – relatively – easy to deliver the new data and to attack the ‘access’ issue by lowering skill and technological barriers for development decision makers, for example via good data analytic and visualisation techniques.  It is much more difficult to address the praxis components of the chain.  That’s not just a question of providing information-, decision-, and action-related skills and other resources for individuals.  It will typically require:

– new, more evidence-based decision-making processes

– new, more agile decision-making structures

– new institutional values and incentives that orient towards these new decision-making modes.

At present, that does not seem to be happening.  If we create a quasi-heatmap of the focus for some key data-revolution-for-development (DReD) sources[2], then we see that almost all the focus lies at the source of the value chain or before (prioritisation, digitisation, standardisation, etc of data).  There is a very little thought given to the development impact of data.  And the “wings” of intelligence and imperative, and the core of praxis (information-decision-action) are missing.

Heatmap Info Value Chain

“Heatmap” of Key Data-Revolution-for-Development Sources

 

Of course that’s partly understandable: there’s a clue in the term data revolution; in the remit set for organisations like Global Pulse; and in the technical profiles of most of those involved.

And the limited incursion of techies into praxis is partly welcome.  As Evgeny Morozov has noted, the techie prescription for praxis is algorithimic regulation – a steady incursion of automation into the downstream stages of the value chain which assumes digital decisions and actions are some apolitical and rational optimum, which denies the importance of politics and thus neuters political debate, and which diverts attention from the causes of society’s ills to their effects with the attitude: “there’s an app for that”.

So, at present, we face two future problematic streams. One in which a great deal of money is wasted on DReD initiatives that make no impact.  One in which a technocentric view of praxis prevails.

Both require the same solution.  First, an explicit recognition of information value chains in the design and implementation of all DReD projects.  Second, a more multidisciplinary approach to these initiatives which incorporates participants capable of both debating and delivering the praxis revolution: those with information systems, organisation development and political economy skills are probably more relevant than decision scientists – to paraphrase Morozov, we’ve got quite enough Kahnemans and could do with a few more Machiavellis.

 

[1] Developed from Heeks & Kanashiro (2009) with a modification courtesy of Omar Malik, University of Nottingham, UK.

[2] Analysis of the content of: http://devinit.org/wp-content/uploads/2013/09/Data-Revolution-DI-briefing.pdf; http://www.opendataresearch.org/content/2014/667/researching-emerging-impacts-open-data-oddc-conceptual-framework; and http://www.unglobalpulse.org/research/projects.  A fuller and more robust analysis will require more sources and co-coding of content.

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