The presentation slides accompanying the following paper - Moorosi N., Thinyane M., Marivate V. (2017) A Critical and Systemic Consideration of Data for Sustainable Development in Africa. In: Choudrie J., Islam M., Wahid F., Bass J., Priyatma J. (eds) Information and Communication Technologies for Development. ICT4D 2017. IFIP Advances in Information and Communication Technology, vol 504. Springer, Cham https://doi.org/10.1007/978-3-319-59111-7_20

1. A Critical and Systemic
Consideration of Data for
Sustainable Development in Africa
Nyalleng Moorosi*, Mamello Thinyane**, Vukosi Marivate*
*Council for Scientific and Industrial Research, South Africa
**United Nations University institute on Computing and Society, Macau SAR

2. Next ~15 mins…
• Data for Development, Data Centric Development, Data in
Development, Data Intensive Development, Big Data for Development, Data ? Development
• Systemic consideration
• Critical consideration
• Opportunities and challenges
• Wrap-up

3. Data for Development
● Data has always been used in development projects,
in developing countries, ...
● 2030 Agenda for Sustainable Development
– Technology as an explicit Means of Implementation
(SDG17)
– “Leave no one behind”
– Data for monitoring the SDGs
● Traditionally within the ambit of NSOs
● Technology-driven opportunities e.g. AI, Big Data
– Data for development action

4. Social indicators monitoring
1. Aggregate, macro-level, meso-level
2. Data for development Planning
Monitoring & Evaluation
3. Obligation perspective
4. Statistics community, UN Statistics
Division
5. SDGs indicators, development
metrics
6. Brushstroke info
Human development and
well-being
1. Individual, community,
micro-level
2. Data for everyday decisions and
living
3. Enjoyment perspective
4. Development community, UNDP
5. Individual wellbeing goals and
targets
6. Diverse and nuanced insights

5. Data for Social/SDG Indicators
● 169 targets, 241 indicators, 180+ indicators in Tier III for
which no data and no robust methodologies exist.
● “What gets measured gets done”?
● The greatest challenge within the statistics community
is not only need for proxy indicators... but also quality
assurance, alignment with the 10 UN principles of
official statistics
– From data to official statistics?
● More and better social indicators data DOES NOT
deterministically lead to better policy and improved
development outcomes

6. Social Indicators to Development
● Lessons from Cobb & Rixford (1998):
– The goals are not likely to be reached if production of social
indicators is confined to a descriptive approach (vs.
analytical approach)
– Description → analysis : understanding the dynamics/causes
behind the indicators
– Don't conflate indicators with reality
– Need for a democratic indicators programme
– Measurement does not induce appropriate action
– Connection between indicator development and policy
development is critical

7. Data for Development Action
• Different dynamics, different requirements,
and different motivations for
– Individuals and Communities
●
Data for everyday living
– Public Sector
• Improved service delivery
• Transparency and accountability (open data)
– Private Sector
• Improve profitability from improved decision
making

8. Data for Development
Big Data Open Data Citizen
generated
Data
Small
Data,Real-
time Data,*
Individuals and
Communities
Source – CDR,
financial records,
surveillence,
privacy, data
ownership
Govt visibility +
accountability;
awareness;
Source and data
generation;
engagement; data
ownership
...
Private
Industry
Collection;
processing;
business insights;
profitability
Innovation on
open data; data
philanthropy;
infomediaries
Market evaluation; ...
Public Sector Collection;
processing;
reporting;
Opening up of
data; data
provisioning
Augmenting
existing datasets;
awareness
...

9. From Data to Development

10. Data ecosystem
● Information /
data flows
● Functional
dependencies
● Actors
interaction

11. Data ecosystem considerations for
Africa
● Connectivity and data availability
– 81% mobile subscription, 29% Internet penetration
● More nuanced situation?
– 5 High HDI: Mauritius, Seychelles, Algeria, Libya,
Tunisia
– 5 Medium HDI: Botswana, Egypt, Gabon, South
Africa, Cape Verde
– 5 Low HDI: Kenya, Swaziland, Angola, Tanzania,
Cameroon
– 5 Lowest HDI: Burundi, Eritrea, Chad, CAR, Niger

12. Active Internet Users

13. International Bandwidth per
User - Availability

14. Active social media users

15. Some Observations
● The paradox : the countries in most need of
development are the countries with the minimal
data repositories – data ecosystems not mature
● The voice of the excluded
● Not representative of the population
● Data for Development ?
– Are the inequalities amplified or changed?
– Are the voices of the unconnected ignored and marginalized?

16. Data ecosystem considerations for
Africa
● Privacy and governance
– Various countries are only starting to develop
policies and legislation around data use
– e.g. AU Convention on Cyber Security and
Personal Data Protection
– The lack of legislative frameworks hamper
effective use of data and expose individuals to
risks

18. Data ecosystem considerations for
Africa
● Empowered and engaged citizenry
– Empowerment (e.g. skills, awareness) of citizens to
participate within the data ecosystem
– Rights and recourse
● Big data analytics skills
– Global demand for Data Science skills
● Computing infrastructure
– Data warehousing and processing infrastructure
● Transparency and Data availability

19. Open Data Barometer

20. Critical perspective
• Informed from critical theory of technology
– What power dynamics does Big Data entrench?
– What dis-empowerment does Big Data perpertuate?
– Does D4D challenge or amplify the existing
inequalities?
– The tyranny of benevolent technocrats
●
~“In some countries, donors still provide 80%
of NSO budgets, it is not surprising that donor
interests still prevail over national interests”*
●
Impact of opaque ML algorithms
*The Africa Data Revolution Report 2016

21. Critical considerations (from 4 principles
of CCAT)
● Human-centered Technology Development
– Human development as the goal/end, and data as the means
– Protecting individuals rights (to privacy) and freedoms (from
surveillance) wrt data
● Human Diversity
– Capability and maturity of different countries (and individuals) to
convert data to development imperatives
– Allowing for the pursuit of the different priorities, goals, targets
● Protecting Human Agency
– Without limiting choices (e.g. datafication and ML
profiling/discrimination, structuring effects)
● Democratic discourse
– Encouraging openness, transparency, accountability

22. Diffusion of Hype
● Diffusion of
innovation from first
world private sector
to developmental
contexts (third
world)
● Need for empirical
evidence for the
impact of various
data technologies for
development

23. Data Opportunities for Africa
● Open data
– Increased democratization of data ecosystems
– Increased transparency and accountability
● Citizen generated data – increased
participation and empowerment of
individuals
– e.g. Geo-spatial annotation of data

24. Recommendations - Plateau of
empowered productivity
● Need for maturity of the technologies,
tools, platforms, frameworks, processes, ...
● Context-sensitive use of data to inform
development action
● Holistic and systemic perspective
– To guide broad systemic investments (e.g.
infrastructure, skills, legislation)
● Accurate and transparent data
● Democratic data ecosystems

25. Thank you!
mamello@unu.edu
…
Where is the Life we have lost in living?
Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information?
...
(“The Rock”, T.S. Elliot, 1934)