Can ICT4D Have a Cambridge Analytica-Facebook Moment? Your Weekend Long Reads

Facebook currently has a Cambridge Analytica problem. It is under severe pressure to explain how 87 million users had their personal data leaked and offer assurances of how it will not happen again. Beyond the US, Cambridge Analytica has been a player in multiple elections in Kenya and Nigeria.

This month Mark Zuckerberg testified before the US Congress and the biggest revelation of that episode was that America’s lawmakers have very little understanding of how Facebook works, and missed a key opportunity to engage deeply with the problems at the heart of Facebook’s business model and practices.

Thanks to the overall weak line of questioning, Zuckerberg’s net worth rose $3 billion during the testimony.

Deleting Isn’t An Option
Users are outraged, some deleting their accounts in the #DeleteFacebook movement. It seems, though, that in general even while many people get angry, they don’t do much more than utter a tut tut.

It’s worth remembering that to actually delete your Facebook account is a privilege, as New York Times reporter Sheera Frenkel tweeted. “For much of the world, Facebook is the internet and only way to connect to family/friend/business.”

From an ICT4D perspective the people we serve, who count on us for knowing how the tech and the data works, need Facebook. And indeed, so do we in our ICT4D offerings through WhatsApp, Messenger and Groups.

Many ICT4D orgs continue to ride the wave of the stellar uptake of Facebook and its owned services, utilising the reach, communication and engagement opportunities these offer, for example, through Facebook Basics.

We Do No Harm, Right?
Can the ICT4D movement have its own Facebook-Cambridge Analytica moment? The answer is yes, of course, and to prevent, or at least delay it from happening we need to vigilantly focus on data privacy and interrogate the choices we make in the offering of our services.

Knowing that using external platforms that vacuum up data can be potentially hazardous, the ICT4D community needs to reaffirm its commitment to do no harm, to ensure data privacy and security.

We’re the good guys: we are transparent with individuals whose data are collected by explaining how our initiatives will use and protect their data; we protect their data; our consent forms are written in the local language and are easily understood by the individuals whose data are being collected.

Nice words, but do we really implement them?

How Careful Are We?
Below are a few questions to ponder in the context of Cambridge Analytica-Facebook.

Access: WIRED magazine shows you how to download and read your Facebook data. Does your app or service allows users to do the same?
Clarity: Come 25 May 2018, the General Data Protection Regulation (GDPR) will require any company serving EU citizens to be very clear about what data they are collecting and what it will be used for. Users will be able to have their data removed or changed, or demand an explanation of how its being used to profile them. This is a major law for the rights of the user (well done European Commission!): How do we do comply? How clear are our ethics research forms, or terms of use on websites? How about comics to explain Ts&Cs?
Recourse: Again, drawing on the GDPR (you can tell I’m a big fan), how easy is it for our users to contact us, request their data to be removed, ask for the algorithm that profiles them to be explained? Do we have the capacity to meet these demands?
Protection: Where is the data that you collect about users? What measures have you put in place to safeguard it?

Terms and conditions are long documents. If US users were to read every privacy policy on every website they visited in a year, it would take them 25 days to complete. Unsurprisingly, most people don’t read the damned things. How much less than can we expect someone who signs with their thumbprint to read such documents?

We really need to be very creative in solving these challenges.

How Are You Transparent and Safe?
So, how is your project practicing radical transparency? Have you had to explain your actions to your users, have you been requested to delete data? Pre-emptively, in what ways have you engaged the community to explain exactly what you are doing?

Please do share your experiences.

There is value in creating templates for radically understandable ethics forms, processes for data download and explanations.

While the scale of risk is lower for us than for Facebook, based on sheer number of affected users, the issues are no less grave. Perhaps in ICT4D, by often coming as non-profits and development agents and not as commercial entities, the issues of data protection are even more important than with Facebook. We come as people who are there to help. If we fail in doing no harm, how terrible is that!?

We need to make sure our house is in order before it’s too late.

UNESCO Request for Input on Guidelines for Digital Inclusion – Your Weekend Long Reads

In 2018 around half the world’s population will be online, which is a major achievement. It also means there is still much work to be done to include the other half.

The next four billion users look different to those already benefiting from digital opportunities for livelihoods, life and work. New and diverse strategies are needed for their digital inclusion. (As this becomes more recognised it may herald the golden age of ICT4D, which already practises inclusive strategies.)

Studies show that, in general, the offline population is disproportionately rural, poor, elderly and female. When it comes to digital skills, women are 1.6 times more likely than men to report it as a factor limiting their use of the internet. Offline people often have limited education, low literacy and typically hold informal sector jobs.

In an increasingly online world, people without the required digital skills and literacy – the 750 million people who cannot read or write and the many more who have low literacy – now face a double exclusion, not only from full participation in the real world but also from opportunities in the digital one.

There is a need to both develop the digital skills and literacy amongst this group, as well as create inclusive digital solutions that are suitable for the digital skills they have today in order to ensure inclusion and equal participation for all.

UNESCO Guidelines for Digital Inclusion for Low-skilled and Low-literate People

Recognising that apps and services, if designed appropriately, can provide an entry point for low-skilled and low-literate people into digital usage and can support improved livelihoods and skills development, UNESCO is currently drafting a set of guidelines for more inclusive design of digital solutions. The work is though UNESCO’s partnership with Pearson.

The draft guidelines have been developed in consultation with an international expert group, and are informed by a landscape review Digital Inclusion for Low- skilled and Low-literate People and a set of fourteen case studies.

There are many excellent guides to effective digital development and how to practise user-centred design. In a way that complements and extends existing resources, UNESCO aims to focus the lens on low-skilled and low-literate users as much as possible with the guidelines.

The Target Audience

The primary target audience for the guidelines are digital solution providers – from large providers such as Google and Facebook, to start-ups – as well as implementation and development partners, such as FAO, GIZ, UNICEF and USAID, who can shape the terms of reference for digital solution development.

The secondary audience includes policy makers – for using the guidelines to create inclusive policies and regulatory frameworks, and mobile network operators and technology providers – for creating enabling environments for greater digital inclusion for all.

Seeking Public Input

In order for UNESCO to create guidelines that are informed, valuable and balanced, it is seeking input from the public. So this week there is one long read — the draft guidelines.

Please review and provide input on the document. When reviewing the guidelines, consider these broad questions:

Is the language and messaging clear?
Is anything missing? Are there parts that should be further developed? Should anything be removed?
What would be the ideal way to raise awareness of the guidelines and have them implemented by as many organisations as possible?

UNESCO is also creating a list of external resources to accompany the guidelines. Please feel free to suggest additional resources to the draft document.

Feedback should be sent by email to ICTliteracy@unesco.org by 30 April 2018.

All input is valuable and will be reviewed by UNESCO. Please note, however, that it is not possible to include all input in the final version.

Drawing on the collective feedback from a range of stakeholders, UNESCO will release a final version of the guidelines on 7 September 2018 in celebration of World Literacy Day.

Thank you in advance for your valuable feedback!

Image © Jayalaxmi Agrotech/Anil Kumar

3 New Reports on Edtech for Refugees, Displaced Populations and Deprived Settings – Your Weekend Long Reads

There are over half a billion children living in countries affected by conflict and disasters, making them three times more likely to be out of school than children living in stable, but low-income countries. 51% of all refugees in the world are children, and refugee girls at secondary level are only half as likely to enrol in school as their male peers. How do we provide quality and inclusive education in these contexts?

To help answer this question three reports on edtech for refugees, displaced populations and those living in deprived contexts have recently been published. Two of them certainly add to the body of knowledge of what works and what doesn’t when providing education in emergencies. They offer a clear-eyed view of edtech possibilities, based on evidence and removed from hype. The third offers predictions on the future of learning and technology in low-resource contexts.

Each report is rich in content and worth reading. Below is a brief description of each and a sample of highlights that caught my eye.

What Works and What’s Missing in Edtech in Emergencies and Displaced Settings

EdTech for Learning in Emergencies and Displaced Settings: A rigorous review and narrative synthesis, by Save the Children, set out to answer the question: How can the utilisation of edtech (at home or at school) for teaching and learning best facilitate the learning process of children in crisis-affected settings?

The report found that while there is little applicable evidence that is relevant for those engaging in education in emergencies, there is nearly three decades worth of research into ‘what works’ in edtech in general. Save the Children felt that if it “cautiously cast the net a little wider, there were areas where research from more stable contexts could be used to inform practice in emergency settings as well.” The authors reviewed over 130 academic papers on edtech’s impact on learning outcomes.

Some of the main findings include:

The mere access of ICT in schools or at home is not sufficient to improve learning outcomes. A number of factors must be in place for learning outcomes to improve. This confirms what most have seem in edtech implementations. And yet the report does not include the recent evaluations of the two EduApp4Syria games, which found a small, but positive, impact on literacy levels and psychosocial wellbeing for children playing the games unassisted by parents or teachers. (Sugata Mitra’s hole in the wall project also springs to mind.)
Edtech must be implemented in line with the local curriculum. This has serious implications for initiatives relying heavily on open content such as Khan Academy, Wikipedia, etc. Not to say those resources are not valuable, but sooner or later there needs to be alignment with the local curriculum.
Scaffolded, appropriate, and adaptive software can be extremely useful in classroom settings. Edtech can indeed support teachers and free them up to engage in greater student-teacher interaction. Yay!
Adult/teacher led scaffolding is key to productive learner engagement with technology. In short, the report says that in-app scaffolding is not enough without an adult or teacher there to help. Controversial.
Poor teacher training leads to poor results. Continued teacher development positively correlates with successful edtech take up. Hear hear!

Education Possibilities for Refugees

The second report A lifeline to learning: Leveraging technology to support education for refugees is from UNESCO. Drawing on a review of over 117 relevant papers and reports and analysis of 52 distinct projects, the report seeks to better understand how mobiles can open educational opportunities for refugees.

Key findings include:

The use of mobile technology can be a strong complement to intensive face-to-face engagement when refugees are experiencing severe trauma and mental health difficulties.
Although low language and literacy skills can be the most pervasive and potentially damaging barrier to educational participation for a refugee learner, to date there is little evidence that documents the efficacy of specific learning and literacy apps in refugee settings. (Again, the EduApp4Syria is relevant here.) Mobile-enhanced conversational and situated learning scenarios deserve further analysis, as some examples in the report indicate.
To date, there are few projects and formal studies on mobile teacher training in refugee contexts. The Teachers for Teachers project in Kakuma camp, Kenya, by Columbia University is a great example of how teacher training and virtual mentoring is possible.
Although some digital content for refugees is available in the form of open educational resources (OER), it is often scattered and unaligned with the education systems in which it is used.
Digital technologies that capture and analyse education data can play an essential role in improving basic operational, planning and controlling functions in education systems in refugee and crisis settings. However, current technological (and political) structures infrequently document, certify or acknowledge refugees’ prior educational achievements or current progress. This is a process, not a technology, problem.
Despite the relevance of cultivating refugees’ job-related and vocational skills, few of the identified projects use mobile media to support vocational training.
A pattern to emerge is the integration of mobile social media and mobile instant messaging spaces in educational designs, although how to obtain big data from instant messaging apps remains a problem.

Both reports highlight the need for more evaluations and exploration of edtech learning possibilities for refugees and displaced populations.

Looking Ahead

The final report, again published by Save the Children, is The Future of Learning and Technology in Deprived Contexts. Looking forward to 2020 and 2025, the report is based on a literature review, interviews with experts, a workshop and consultations with Save the Children staff.

Tim Unwin, one of the authors, offers a useful summary of the key points. Concerning changes in basic education which are likely to be apparent by 2025, some observations include the following:

The pace of change in education is likely to remain slow in most countries. Further, there will be increased diversity and inequality in learning practices and opportunities. Not a rosy outlook.
On the upside: The diversity of content provision will increase and there will be greater emphasis on non-formal and lifelong learning.
The use of technology will be all-pervasive. I hope this will be true, but I’m not that optimistic. Also, the report says “it may well be that by 2025 many traditional literacy skills will also have become replaced by technology, so that children do not have to learn to read and write and will simply speak and listen mediated by ICTs.” Very controversial!

Concerning ICTs for education in crisis-affected areas in 2025, a few predictions include:

Mobile technologies will increasingly enable children fleeing crises to continue to participate in both formal and informal learning.
Much more extensive use will be made of online resources to provide counseling for those traumatised by disasters and war (tying up with the UNESCO report finding).
Online resources will be available specifically to provide children in acute crises with additional information to enable them to be better able to survive.
It is likely that by 2025 numerous different ICT-enhanced school-in-a-box solutions, combining connectivity, electricity, devices and content, will be available that can be set up quickly and effectively wherever in the world there is a need.
There will be much greater use of mobile phones by refugees to find out information about entering other countries, and what they need to know about the different cultures and ways of life there in order to survive.

The focus is clearly on continued learning, psycho-social support and integration into the host setting. These predictions provide great suggestions for where to focus attention in new apps and services.

Photo: (c) S. Sheridan / Mercy Corps

Six Practices for Digital Inclusion – Your Weekend Long Reads

UNESCO, in partnership with Pearson, has released the final batch of case studies of digital solutions that are inclusive for people with low skills and low literacy, helping them to participate in the knowledge society in innovative ways. The case studies, authored by Dr Nathan Castillo and myself, were released during UNESCO’s Mobile Learning Week.

The new case studies are:

MOPA: a citizen reporting and monitoring platform for solid waste management in Maputo, Mozambique.
Hello Hope / Merhaba Umut: a translation, language learning and essential information service for Syrian refugees living in Turkey.
Farmer Training App: a training tool for sustainable farming practices in Guatemala and 23 other countries.
ABALOBI: a digital self-management system for small-scale fishers in South Africa (coming in April).

The latest case studies affirm the six digital insights drawn from the earlier cases in the series. Each has an interesting story to tell and is well worth a read.

For me, MOPA is particularly interesting because it demonstrates how a user-centred design approach and the inclusion of different stakeholder groups can empower citizens and strengthen accountability for public service delivery. It demonstrates six digital practices that are instructive for ICT4D practitioners.

Citizen Monitoring of Municipal Services

Maputo has a serious solid waste management problem. Many of its 1.2 million residents live in informal settlements, hard to reach because of poor road infrastructure and dangerous during flooding because of drains and rivers blocked by trash.

The Maputo Municipality attempted to address the solid waste challenge by outsourcing waste collection to private companies which used waste removal trucks in the urban sectors, and micro-operators using pushcarts for suburban neighbourhoods. Overseeing and quality controlling such a decentralised network of 45 operators proved to be very difficult.

Today, through the participatory digital reporting and monitoring MOPA platform, citizens are encouraged to report waste issues and monitor the public waste management service in the Maputo Municipality via USSD, website and, most recently, via Android app. After a year, 3,500 registered users have contributed almost 7,000 sanitation reports to the MOPA digital system, 96% via USSD.

It’s a really cool project, basically what happens when a UX company – UX Information Technologies – teams up with city government – the Maputo Municipal Council – and gets support from the World Bank. The development process followed is thorough and the solution is wonderfully pragmatic.

Understand the Problem, Engage All the Users

Good product development means we should design with the user and understand the existing ecosystem. The MOPA team decided to do this through four types of workshops to gather user-oriented design insights, validate workflow systems, and collect ideas for improving the service.

Insight workshops helped unpack the complex system of solid waste management in the city and the roles of the three main groups: residents (the ones reporting), municipal workers (the ones managing) and private waste collection operators (the ones responding).
Collection (data) workshops emphasized functioning sources of data and gaps that needed to be filled for service optimization. These workshops led to a campaign of mapping physical collection sites in Maputo.
Validation workshops tested design iterations of the platform with an emphasis on suitability for the skills of the intended user base.
Events workshops promoted the MOPA prototype across Maputo to attract local software developers to take an interest in enhancing the software design and features – more on this below.

Talk the User’s Language

Citizens can report on particular rubbish containers to say, for example, it is full or burning. Containers have physical locations, but residents don’t identify containers by address. MOPA found out that they rather refer to them in relation to something, for example, the receptacle in front of the Custodio warehouse is the ‘Custodio’ container.

The MOPA team mapped the city with these peoples’ labels, which improves the reporting quality and better fits the residents’ language. In the background the system can match the peoples’ label with the official address.

Make it Super Easy

To submit a report, the MOPA platform requires three data points for location identification: municipal district, neighbourhood and place. But how do you get citizens to report based on location when they don’t have GPS? Keep it old school with paper and USSD.

As part of its awareness-raising campaign, the UX team produced posters that were distributed in all neighbourhoods with a unique USSD string for each container. Each string captured the essential location data.

By storing the USSD string as a contact under ‘MOPA’, whenever residents want to register a report the key location data is already captured and they go straight to specifying the type of incident.

Use Soft Power

While disruptive innovation is the rallying cry of today, the MOPA team did not try to become the “Uber of” waste management. Instead they decided to work within the current parameters, but bring efficiency to the process. We could call this “soft power innovation”. Soft power is “the ability to attract and co-opt, rather than by coercion (hard power) … to shape the preferences of others through appeal and attraction”.

Local service providers are still contracted to collect the waste and the City still manages the process. Everyone keeps their jobs, but they need to do them better. The residents and the data management tool empowering the City bring an efficiency to the process using simple tools already in their lives.

Open the Platform and Data

The UX team organized Mozambique’s first e-Government hackathon – #apps4maputo – challenging local developers to produce the most innovative digital solution utilising an API into the MOPA platform. MOPA is built on open source software and generates open data.

The winner developed an app called OurMoz, which submits reports to the MOPA platform from any Android-enabled device.

The hackathon allowed the UX team to expand its user base to include smartphone users and practice being collaborative and open in textbook style. It also set the tone for the underlying platform to be used for other civic participation use cases.

Keep the User Informed

SMS notifications allow residents to receive confirmations of their submitted
reports, and update them on the status of the report. In the City’s offices the reports are published on an online map, which the municipality uses along with a dashboard to track, validate and verify with the waste removal companies when each issue has been resolved. The resident is then notified via an SMS sent through the platform. Such a feedback loop shows that the municipality is transparent and responsive.

Overall, the results are impressive: more than 88% of reported issues are resolved, with an average response time of 2.7 days. 186 informal dump sites across the city have also been eradicated. MOPA is an exciting example of simple innovation using the tools that people have. Aside from moving towards a cleaner city, perhaps the biggest impact is the empowerment residents feel by playing their part in this process. That is a key foundation of digital inclusion.

Image: (C) by Municipal Council of Maputo

The Challenges of Being a Sustainable Edtech Venture – Your Weekend Long Reads

Earlier this month I attended FUTUR.E.S in Africa in Casablanca, the first event to connect French, Moroccan and African digital ecosystems. Startups, academics and government shared projects in various sectors, including education. It was refreshing to discuss edtech with Francophones, as usually the Anglo/Franco African divide is wide.

One particularly interesting workshop aimed to discuss the business models of edtech. In the end, it was more a discussion about how challenging it is to run an edtech venture in Africa. While the issues raised are not new, it was useful to be reminded of the frustration that passionate people feel in trying to launch their great idea and keep it sustained. As can be seen below, the issues really apply to most ICT4D initiatives.

Challenges Around Edtech Business Models

In no particular order, here are some of the big challenges:

Expectation of free. Much of edtech is based on great content. Content has value. It takes time and people to develop. Localising it into African languages is expensive. It is also quickly consumed, leaving people hungry for more. What do you do when the market has come to expect it for free?
Payment is difficult. Even when people decide to buy, there are issues. For the user the most friction-less method is to pay with airtime, but then 30-40% can be lost to mobile operators and other service providers. Most people in Africa don’t have credit cards. And let’s face it, m-Pesa only works in seven African countries, none of which where it is as successful as in Kenya.
People get “stuck” on islands. As the GSMA explains, many users are “stuck on ‘application islands’, primarily using only WhatsApp or Facebook, without being aware of the broader potential of the internet.” How do you get them to your app? How do you even get noticed?
Education is a long game. While in some cases grades can be shown to improve quickly, in general the impact of an education intervention takes years to show.
The trouble with MNOs. Mobile network operators (MNOs) have immense reach and power, and yet are notoriously difficult to partner with as a startup. Basically, you need them a lot more than they need you.

The MNO situation is slowly beginning to change, for example, Orange is investing EUR50m in startups in Africa, as are other MNOs, and across Africa a number of MNO APIs are now available. The next round of the GSMA Startup Accelerator Innovation Fund for Africa and Asia-Pacific, which tries to bring MNOs and startups closer together, is open for applications until 15 April.

Who’s Gotten it Right?

At the event I was asked to talk about sustainable and impactful edtech initiatives in Africa. It was useful to look at initiatives that have been operational for at least six years and think about how they’ve made it. Not all are for-profit, and sometimes their users are different from their paying customers, which could be funders or corporate sponsors.

Siyavula in South Africa (SA) – and soon in Nigeria – decided to embrace not only free content, but to openly license it. It has 10 million open textbooks on desks in SA – 100% penetration in government schools.The paid-for part is Siyavula Practice, a closed-content proprietary assessment service for learners, with a teacher dashboard. Some schools pay (usually private schools), but many are sponsored by external funders. Payment can be made by credit card, airtime or bank transfer. Google.org recently awarded Siyavula $1.5m to sponsor access to 300,000 learners, split between SA and Nigeria.
Eneza, the assessment and content delivery service for school learners in Kenya, Tanzania, Ghana and Zimbabwe has grown thanks to being invested in by Safaricom, which also provides integration and visibility support. They got it right to work with an MNO.
Fundza, the mobile novel library, also has a business model that draws on donor funding and commissioned content. Beyond content, it offers training and skills development for a fee. The content is not only in digital; Fundza’s stories are also printed, a format that is appealing to many donors. In the last year Fundza delivered over 33,000 print books.
Worldreader, another mobile library with a large African footprint, focused its early years on the Amazon Kindle as a delivery channel. In 2013, a mobisite was added to increase reach. The rest is history: thanks to widening the channel options it has reached over seven million readers. Both Fundza and Worldreader have experimented with paid-for content – but with limited success. Donor funding, public donations, sponsored activities like increasing access to reading materials, or services like conducting research, are key sources.
For pure-play commercial edtech consider GetSmarter, a South African startup founded by two brothers that delivers short online courses to students anywhere. Over a ten year period GetSmarter has steadily partnered with top universities around the world, offering courses for them and building both a partner and broad customer base. The courses are not cheap – the eight-week Harvard Cybersecurity course costs $2,800 – but they are good, aimed at professionals. The staff of over 400 includes performance coaches, technologists, video producers and tutors. The key focus areas of partnerships and quality resulted in the company being sold for $103m last year.
The Talking Book, a ruggedized audio player and recorder by Literacy Bridge that offers agricultural, health and livelihoods education to deep rural communities in four African countries, has been going for ten years. It’s been run on a combination of donor funding (as it’s founder said to me, if a stream of donor funding can be sustained then this is a viable model) and commissioned implementations.For the latter it services the likes of UNICEF and CARE International to achieve their goals, for example, helping people to be healthier or better farmers. The key here is to demonstrate value to potential partners. Literacy Bridge has also developed an interesting “affiliate” model, that is worth reading about.

The Talking Book is not strictly an edtech initiative, but it’s aim is to educate and change behaviour. This point was raised in the workshop: unless you’re focused in formal education it may be better not to call yourself an edtech provider. Offer learning in m-Health, m-Agri or Fintech, where there may be more access to funding.

As a parting shot: Injini, Africa’s only incubator dedicated to edtech, is calling for applicants until 3 April to receive $50K in investment and five month’s of incubation.

Thanks to Calixte Tayoro and Lola Laurent for a great workshop.

Image: CC by Trevor Samson / World Bank

Algorithmic Accountability is Possible in ICT4D

As we saw recently, when it comes to big data for public services there needs to be algorithmic accountability. People need to understand not only what data is being used, but what analysis is being performed on it and for what purpose.

Further, complementing big data with thick, adjacent and lean data also helps to tell a more complete story of analysis. These posts piqued much interest and so this third and final instalment on data offers a social welfare case study of how to be transparent with algorithms.

A Predictive Data Tool for a Big Problem

The Allegheny County Department of Human Services (DHS), Pennsylvania, USA, screen calls about the welfare of local children. The DHS receives around 15,000 calls per year for a county of 1.2 million people. With limited resources to deal with this volume of calls, limited data to work with, and each decision a tough and important one to make, it is critical to prioritize the highest need cases for investigation.

To help, the Allegheny Family Screening Tool was developed. It’s a predictive-risk modeling algorithm built to make better use of data already available in order to help improve decision-making by social workers.

Drawing on a number of different data sources, including databases from local housing authorities, the criminal justice system and local school districts, for each call the tool produces a Family Screening Score. The score is a prediction of the likelihood of future abuse.

The tool is there to help analyse and connect a large number of data points to better inform human decisions. Importantly, the algorithm doesn’t replace clinical judgement by social workers – except when the score is at the highest levels, in which case the call must be investigated.

As the New York Times reports, before the tool 48% of the lowest-risk families were being flagged for investigation, while 27% of the highest-risk families were not. At best, decisions like this put an unnecessary strain on limited resources and, at worst, result in severe child abuse.

How to Be Algorithmically Accountable

Given the sensitivity of screening child welfare calls, the system had to be as robust and transparent as possible. Mozilla reports the ways in which the tool was designed, over multiple years, to be like this:

A rigorous public procurement process.
A public paper describing all data going into the algorithm.
Public meetings to explain the tool, where community members could ask questions, provide input and influence the process. Professor Rhema Vaithianathan is the rock star data storyteller on the project.
An independent ethical review of implementing, or failing to implement, a tool such as this.
A validation study.

The algorithm is open to scrutiny, owned by the county and constantly being reviewed for improvement. According to the Wall Street Journal the trailblazing approach and the tech are being watched with much interest by other counties.

It Takes Extreme Transparency

It takes boldness to build and use a tool in this way. Erin Dalton, a deputy director of the county’s DHS and leader of its data-analysis department, says that “nobody else is willing to be this transparent.” The exercise is obviously an expensive and time-consuming one, but it’s possible.

During recent discussions on AI at the World Bank the point was raised that because some big data analysis methods are opaque, policymakers may need a lot of convincing to use them. Policymakers may be afraid of the media fallout when algorithms get it badly wrong.

It’s not just the opaqueness, the whole data chain is complex. In education Michael Trucano of the World Bank asks: “What is the net impact on transparency within an education system when we advocate for open data but then analyze these data (and make related decisions) with the aid of ‘closed’ algorithms?”

In short, it’s complicated and it’s sensitive. A lot of convincing is needed for those at the top, and at the bottom. But, as Allegheny County DHS has shown, it’s possible. For ICT4D, their tool demonstrates that public-service algorithms can be developed ethically, openly and with the community.

Stanford University is currently examining the impact of the tool on the accuracy of decisions, overall referral rates and workload, and more. Like many others, we should keep a close watch on this case.

3 Data Types Every ICT4D Organization Needs – Your Weekend Long Reads

After five years researching the effectiveness of non-profit organizations (NPOs) in the USA, Stanford University lecturer Kathleen Kelly Janus found that while 75% of NPOs collect data, only 6% feel they are using it effectively. (Just to be clear, these were not all tech organizations.)

She suggests the reason is because they don’t have a data culture. In other words, they need to cultivate “a deep, organization-wide comfort level with using metrics to maximize social impact.” Or, in ICT4D speak, they need to be data-driven.

Perhaps NPOs feel that if they start collecting, analysing and using big data, that need will be satisfied. But one cloud server of big data does not a data culture make. While big data can be a powerful tool for development, there are three other data types that could significantly improve the impact of any ICT4D intervention.

Thick data

Technology ethnographer, Tricia Wang, warns us about the dangers of only looking to big data for the answers, of only trusting large sets of quantitative data without a human perspective. She proposes that big data must be supplemented with “thick data,” which is qualitative data gathered by spending time with people.

Big data excels at quantifying very specific environments – like delivery logistics or genetic code – and doing so at scale. But humans are complex and so are the changing contexts in which they live (especially true for ICT4D constituents). Big data can miss the nuances of the human factor and portray an incomplete picture.

As a real-life example, in 2009 Wang joined Nokia to try to understand the mobile phone market in China. She observed, talked to, and lived amongst low-income people and quickly realised that – despite their financial constraints – they were aspiring to own a smartphone. Some of them would spend half of their monthly income to buy one.

But the sample was small, the data not big, and Nokia was not convinced. Nokia’s own big data was not telling the full story – it was missing thick data, which led to catastrophic consequences for the company.

Adjacent data

Sometimes there is value in overlaying data from other sources onto your own to provide new insights. Let’s call this “adjacent data”. Janus provides the case of Row New York, an organization that pairs rigorous athletic training with tutoring and other academic support to empower youth from under-resourced communities.

To measure success, Row started by tracking metrics like the number of participants, growth, and fitness levels. But how could they track determination or “grit” – attributes of resilient people?

They started recording both attendance and daily weather conditions to show which students were still showing up to row even when it was 4C degrees and raining. “Those indicators of grit tracked with students who were demonstrating academic and life success, proving that [Row’s] intervention was improving those students’ outcomes.”

Pinpointing adjacent data requires thinking outside of the box. Maybe reading Malcom Gladwell or Freakonomics will provide creative inspiration for finding those hidden data connectors.

Lean data

Lastly, there is a real risk in just hoovering up every possible data point in the hope that the answers to increased impact and operational efficiencies will emerge. That’s not referring only to the data security and privacy risks related to the sponge approach. Rather, that’s because it’s easy to drown in data.

Most ICT4D initiatives don’t have the tech or the people to meaningfully process the stuff. Too much data can overwhelm, not reveal insights. The challenge is gathering just enough data, just the data we need – let’s call this the “lean data”. When it comes to data, more is not better, just right is better. In fact, big data can be lean. It’s not about quantity but rather selectiveness.

Lean data is defined by the goals of the initiative and its success metrics. Measure enough to meet those needs. When I was head of mobile at Pearson South Africa’s Innovation Lab, we were developing an assessment app for high school learners called X-kit Achieve Mobile.

With the team we brainstormed the data we needed to serve our goals and those of the student and teacher users. We threw in quite a lot of extra bits based on “Hmm, that would be cool to know, let’s put it in a dashboard.”

The company was also preparing to report publicly on its educational impact, so certain data points were being collected by all digital products. Having a common data dictionary and reporting matrix is something worth considering if you’re implementing more than one product.

After building the app we only really used about 20% of all the reports and dashboards. Only as we iterated did we discover new reports that we actually needed. The fact is that data is seductive, it brings out the hoarder in all of us. We should resist and only take what we need.

So, perhaps the path to building a data culture is to always have thick data, be creative about using adjacent data, and keep all data lean.

Image: CC by janholmquist

Every Big Data Algorithm Needs a Storyteller – Your Weekend Long Reads

The use of big data by public institutions is increasingly shaping peoples’ lives. In the USA, algorithms influence the criminal justice system through risk assessment and predictive policing systems, drive energy allocation and change educational system through new teacher evaluation tools.

The belief is that the data knows best, that you can’t argue with the math, and that the algorithms ensure the work of public agencies is more efficient and effective. And, often, we simply have to maintain this trust because nobody can examine the algorithms.

But what happens when – not if – the data works against us? What is the consequence of the algorithms being “black boxed” and outside of public scrutiny? Behind this are two implications for ICT4D.

The Data Don’t Lie, Right?

Data scientist and Harvard PhD in Mathematics, Cathy O’Neill, says that clever marketing has tricked us to be intimidated by algorithms, to make us trust and fear algorithms simply because, in general, we trust and fear math.

O’Neill’s 2016 book, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, shows how when big data goes wrong teachers lose jobs, women don’t get promoted and global financial systems crash. Her key message: the era of blind faith in big data must end, and the black boxes must be opened.

Demand Algorithmic Accountability

It is very interesting, then, that New York City has a new law on the books to do just that and demand “algorithmic accountability” (presumably drawing on the Web Foundation’s report of the same name). According to MIT Technology Review, the city’s council passed America’s first bill to ban algorithmic discrimination in city government. The bill wants a task force to study how city agencies use algorithms and create a report on how to make algorithms more easily understandable to the public.

AI Now, a research institute at New York University focused on the social impact of AI, has offered a framework centered on what it calls Algorithmic Impact Assessments. Essentially, this calls for greater openness around algorithms, strengthening of agencies’ capacities to evaluate the systems they procure, and increased public opportunity to dispute the numbers and the math behind them.

Data Storytellers

So, what does this mean for ICT4D? Two things, based on our commitment to being transparent and accountable for the data we collect. Firstly, organisations that mine big data need to become interpreters of their algorithms. Someone on the data science team needs to be able to explain the math to the public.

Back in 2014 the UN Secretary General proposed that “communities of ‘information intermediaries’ should be fostered to develop new tools that can translate raw data into information for a broader constituency of non-technical potential users and enable citizens and other data users to provide feedback.” You’ve noticed the increase in jobs for data scientists and data visualisation designers, right?

But it goes beyond that. With every report and outcome that draws on big data, there needs to be a “how we got here” explanation. Not just making the data understandable, but the story behind that data. Maybe the data visualiser does this, but maybe there’s a new role of data storyteller in the making.

The UN Global Pulse principle says we should “design, carry out, report and document our activities with adequate accuracy and openness.” At the same time, Forbes says data storytelling is an essential skill. There is clearly a connection here. Design and UI thinking will be needed to make sure the heavy lifting behind the data scenes can be easily explained, like you would to your grandmother. Is this an impossible ask? Well, the alternative is simply not an option anymore.

Data Activists

Secondly, organisations that use someone else’s big data analysis – like many ICT4D orgs these days – need to take an activist approach. They need to ask questions about where the data comes from, what steps were taken to audit it for inherent bias, for an explanation of the “secret sauce” in the analysis. We need to demand algorithmic accountability” We are creators and arbiters of big data.

The issue extends beyond protecting user data and privacy, important as this is. It relates to transparency and comprehension. Now is the time, before it’s too late, to lay down the practices that ensure we all know how big data gets cooked up.

Image: CC by kris krüg

Across Africa the Feature Phone is Not Dead – Your Weekend Long Reads

Quartz Africa reports that last year feature phones took back market share from smartphones in Africa. The market share of smartphones fell to 39% in 2017 (from 45%), while feature phones rose to 61% (from 55%).

Quartz Africa sees the reasons as likely to be twofold: first, the growth of big markets, like Ethiopia and DR Congo, which until recently have had relatively low penetration. Second, low price.

Transsion, a little-known Chinese handset manufacturer, now sells more phones than any other company in Africa. It’s three big brands outnumber Samsung’s market share there. The devices are cheap and appealing for new users.

The FT reports that Transsion’s phones are specifically designed for the African market: they have multiple sim-card slots, camera software adapted to better snap darker skin tones, and speakers with enhanced bass (seriously). Many of the feature phone models have messaging apps. The batteries remain on standby for up to 13 days!

What does this mean? That you should freeze your flashy new app project? No! There’s no need to stop planning and developing for a smartphone-enabled Africa. The trend is clear: smartphones become cheaper over time and their uptake increases.

But we know that in Africa, especially, mobile usage is unevenly distributed and these stats are a good reminder that the non-smartphone user base is still huge. Many of us need to remain true to that reality if we want our ICT to be 4D.

The age old question – which mobile channel should we focus on? – has not gone away. And the answer still remains the same: it depends. What is your service? What devices do your users have? What are their usage preferences? Do they have data coverage and, if yes, can they afford data?

Low tech, like IVR and radio, can be beautiful and extremely effective. In a meta-study of education initiatives in Africa, the Brookings Institute found that most technology-based innovations utilize existing tools in new ways. They give Eneza Education as an example, which built its service on SMS (even though there is now an Android app available).

At the same time, apps are certainly rising in the development sector. While not in Africa, the Inventory of Digital Technologies for Resilience in Asia-Pacific found apps to be the dominant channel. From my own experience I’m seeing more apps, often as one part of a mix of delivery channels.

A forthcoming case study in the UNESCO-Pearson initiative is MOPA, a platform for participatory monitoring of waste management services in Maputo, Mozambique. Citizens report issues via USSD, website and, most recently, via Android app.

Usage patterns show that 96% of reports are still sent through USSD, 3% via mobile app, and only 1% through the website. Given that specific user base, and the quick-and-dirty nature of the transaction, it’s not surprising that USSD is a clear winner.

Another example of a channel mix is Fundza, the South African mobile novel library. It started life as a mobisite and now also has an app, which largely provides a window into the same content just in a nice Android skin.

The app is used by less than 1% of users, with the mobisite taking the lion’s share of traffic (via feature phone and smartphone). Fundza is also on Free Basics, where the breakdown is quite different: 65% mobisite, 45% app (perhaps pointing to the benefits of being bundled into someone else’s very well-marketed app).

There are many reasons why individual apps may or may not succeed, and these examples are not meant to downplay their utility. Overall, the world is going to smartphones.

However, the bottom line is that you should not write off the humble feature phone in Africa just yet. It does old tech very well, internet messaging and the mobile web, which for many ICT4D projects is still their bread and butter access channel.

In ICT4D We’re Principled, But Are We Practiced Enough? – Your Weekend Long Reads

Last month CO.DESIGN published the 10 New Principles of Good Design (thanks Air-bel Center for the link). The article, which is based on a set of industrial design principles from the 1970s, makes for important reading.

According to the author, and concerning commercial digital solutions, 2017 was “a year of reckoning for the design community. UX became a weapon, AI posed new challenges, and debate erupted over once rock-solid design paradigms.” What is most interesting — and wonderful to boot — is that many of the “new” principles we, the ICT4D community, have endorsed for years.

Good Design is Transparent

For example, the article calls for transparency in design. Apparently today, “amid a string of high-profile data breaches and opaque algorithms that threaten the very bedrock of democracy, consumers have grown wary of slick interfaces that hide their inner workings.”

We know that user-centered design is participatory and that we should expose the important parts of digital solutions to our users. We believe in telling our users what we’ll do with their data.

Good Design Considers Broad Consequences and is Mindful of Systems

The article warns that in focusing on the immediate needs of users, user-friendly design often fails to consider long-term consequences. “Take Facebook’s echo chamber, Airbnb’s deleterious impact on affordable housing,” as examples. Not for us: we understand the existing ecosystem, are conscious of long-term consequences and design for sustainability.

A Little History Lesson

Today we have principles for sectors — such as refugees, health and government (US or UK version?); for cross-cutting themes — such as identity, gender and mobile money; for research; and the grand daddy of them all, for digital development.

These principles have been developed over a long time. Fifteen years go I wrote a literature survey on the best practices of ICT4D projects. It was based on the work of then research pioneer, Bridges.org, drawing on a range of projects from the early 2000s.

In my paper, Bridges.org put forward seven habits of highly effective ICT-enabled development initiatives. By 2007 the list had grown to 12 habits — many of which didn’t look that different from today’s principles.

Do We Practice What We Preach?

But if these principles are not new to us, are we practicing them enough? Don’t get me wrong, the ICT4D community has come a long way in enlisting tech for social good, and the lessons — many learned the hard way — have matured our various guidelines and recommendations. But should we be further down the line by now?

The principles mostly outline what we should do, and some work has been done on the how side, to help us move from principles to practice. But I think that we need to do more to unpack the why don’t we aspect.

Consider this data point from a recent Brookings Institute report Can We Leapfrog: The Potential of Education Innovations to Rapidly Accelerate Progress (more on this report in a future post). Brookings analysed almost 3,000 education innovations around the world (not all tech-based, just so you know) and found that:

… only 16 percent of cataloged interventions regularly use data to drive learning and program outcomes. In fact, most innovations share no information about their data practices.

We know that we should be data-driven and share our practices. So what is going on here? Do the project managers behind these interventions not know that they should do these things? Do they not have the capacity in their teams? Do they not want to because they believe it exposes their non-compliance with such principles? Or perhaps they feel data is their competitive edge and they should hide their practices?

Time for ‘Fess Faires?

Fail faires are an excellent way to share what we tried and what didn’t work. But what about ‘Fess Faires, where we confess why we can’t or — shock horror — won’t follow certain principles. Maybe it’s not our fault, like funding cycles that ICT4D startups can’t survive. But maybe we should be honest and say we won’t collaborate because the funding pie is too small.

If fail faires are more concerned with operational issues, then ‘fess faires look at structural barriers. We need to ask these big questions in safe spaces. Many ICT4D interventions are concerned with behavior change. If we’re to change our own behavior we need to be open about why we do or don’t do things.

Good Design is Honest

So, on the one hand we really can pat ourselves on the back. We’ve had good design principles for almost twenty years. The level of adherence to them has increased, and they have matured over time.

On the other hand, there is still much work to be done. We need to deeply interrogate why we don’t always practice our principles, honestly and openly. Only in this way will we really pursue a key new principle: good design is honest.