Archive for the ‘ICTs, mobile and technology’ Category

Traditional development evaluation has been characterized as ‘backward looking’ rather than forward looking and too focused on proving over improving. Some believe applying an ‘agile’ approach in development would be more useful — the assumption being that if you design a program properly and iterate rapidly and constantly based on user feedback and data analytics, you are more likely achieve your goal or outcome without requiring expensive evaluations. The idea is that big data could eventually allow development agencies to collect enough passive data about program participants that there would no longer be a need to actively survey people or conduct a final evaluation, because there would be obvious patterns that would allow implementers to understand behaviors and improve programs along the way.

The above factors have made some evaluators and data scientists question whether big data and real-time availability of multiple big data sets, along with the technology that enables their collection and analysis, will make evaluation as we know it obsolete. Others have argued that it’s not the end of evaluation, but rather we will see a blending of real-time monitoring, predictive modeling, and impact evaluation, depending on the situation. Big questions remain, however, about the feasibility of big data in some contexts. For example, are big data approaches useful when it comes to people who are not producing very much digital data? How will the biases in big data be addressed to ensure that the poorest, least connected, and/or most marginalized are represented?

The Technology Salon on Big Data and Evaluation hosted during November’s  American Evaluation Association Conference in Chicago opened these questions up for consideration by a roomful of evaluators and a few data scientists. We discussed the potential role of new kinds and quantities of data. We asked how to incorporate static and dynamic big data sources into development evaluation. We shared ideas on what tools, skills, and partnerships we might require if we aim to incorporate big data into evaluation practice. This rich and well-informed conversation was catalyzed by our lead discussants: Andrew Means, Associate Director of the Center for Data Science & Public Policy at the University of Chicago and Founder of Data Analysts for Social Good and The Impact Lab; Michael Bamberger, Independent Evaluator and co-author of Real World Evaluation; and Veronica Olazabal from The Rockefeller Foundation. The Salon was supported by ITAD via a Rockefeller Foundation grant.

What do we mean by ‘big data’?

The first task was to come up with a general working definition of what was understood by ‘big data.’ Very few of the organizations present at the Salon were actually using ‘big data’ and definitions varied. Some talked about ‘big data sets’ as those that could not be collected or analyzed by a human on a standard computer. Others mentioned that big data could include ‘static’ data sets (like government census data – if digitized — or cellphone record data) and ‘dynamic’ data sets that are being constantly generated in real time (such as streaming data input from sensors or ‘cookies’ and ‘crumbs’ generated through use of the Internet and social media). Others considered big data to be real time, socially-created and socially-driven data that could be harvested without having to purposely collect it or budget for its collection. ‘It’s data that has a life of its own. Data that just exists out there.’ Yet others felt that for something to be ‘big data’ multiple big data sets needed to be involved, for example, genetic molecular data crossed with clinical trial data and other large data sets, regardless of static or dynamic nature. Big data, most agreed, is data that doesn’t easily fit on a laptop and that requires a specialized skill set that most social scientists don’t have. ‘What is big data? It’s hard to define exactly, but I know it when I see it,’ concluded one discussant.

Why is big data a ‘thing’?

As one discussant outlined, recent changes in technology have given rise to big data. Data collection, data storage and analytical power are becoming cheaper and cheaper. ‘We live digitally now and we produce data all the time. A UPS truck has anywhere from 50-75 sensors on it to do everything from optimize routes to indicate how often it visits a mechanic,’ he said. ‘The analytic and computational power in my iPhone is greater than what the space shuttle had.’ In addition, we have ‘seamless data collection’ in the case of Internet-enabled products and services, meaning that a person creates data as they access products or services, and this can then be monetized, which is how companies like Google make their money. ‘There is not someone sitting at Google going — OK, Joe just searched for the nearest pizza place, let me enter that data into the system — Joe is creating the data about his search while he is searching, and this data is a constant stream.’

What does big data mean for development evaluation?

Evaluators are normally tasked with making a judgment about the merit of something, usually for accountability, learning and/or to improve service delivery, and usually looking back at what has already happened. In the wider sense, the learning from evaluation contributes to program theory, needs assessment, and many other parts of the program cycle.

This approach differs in some key ways from big data work, because most of the new analytical methods used by data scientists are good at prediction but not very good at understanding causality, which is what social scientists (and evaluators) are most often interested in. ‘We don’t just look at giant data sets and find random correlations,’ however, explained one discussant. ‘That’s not practical at all. Rather, we start with a hypothesis and make a mental model of how different things might be working together. We create regression models and see which performs better. This helps us to know if we are building the right hypothesis. And then we chisel away at that hypothesis.’

Some challenges come up when we think about big data for development evaluation because the social sector lacks the resources of the private sector. In addition, data collection in the world of international development is not often seamless because ‘we care about people who do not live in the digital world,’ as one person put it. Populations we work with often do not leave a digital trail. Moreover, we only have complete data about the entire population in some cases (for example, when it comes to education in the US), meaning that development evaluators need to figure out how to deal with bias and sampling.

Satellite imagery can bring in some data that was unavailable in the past, and this is useful for climate and environmental work, but we still do not have a lot of big data for other types of programming, one person said. What’s more, wholly machine-based learning, and the kind of ‘deep learning’ made possible by today’s computational power is currently not very useful for development evaluation.

Evaluators often develop counterfactuals so that they can determine what would have happened without an intervention. They may use randomized controlled trials (RCTs), differentiation models, statistics and economics research approaches to do this. One area where data science may provide some support is in helping to answer questions about counterfactuals.

More access to big data (and open data) could also mean that development and humanitarian organizations stop duplicating data collection functions. Perhaps most interestingly, big data’s predictive capabilities could in the future be used in the planning phase to inform the kinds of programs that agencies run, where they should be run, and who should be let into them to achieve the greatest impact, said one discussant. Computer scientists and social scientists need to break down language barriers and come together more often so they can better learn from one another and determine where their approaches can overlap and be mutually supportive.

Are we all going to be using big data?

Not everyone needs to use big data. Not everyone has the capacity to use it, and it doesn’t exist for offline populations, so we need to be careful that we are not forcing it where it’s not the best approach. As one discussant emphasized, big data is not magic, and it’s not universally applicable. It’s good for some questions and not others, and it should be considered as another tool in the toolbox rather than the only tool. Big data can provide clues to what needs further examination using other methods, and thus most often it should be part of a mixed methods approach. Some participants felt that the discussion about big data was similar to the one 20 years ago on electronic medical records or to the debate in the evaluation community about quantitative versus qualitative methods.

What about groups of people who are digitally invisible?

There are serious limitations when it comes to the data we have access to in the poorest communities, where there are no tablets and fewer cellphones. We also need to be aware of ‘micro-exclusion’ (who within a community or household is left out of the digital revolution?) and intersectionality (how do different factors of exclusion combine to limit certain people’s digital access?) and consider how these affect the generation and interpretation of big data. There is also a question about the intensity of the digital footprint: How much data and at what frequency is it required for big data to be useful?

Some Salon participants felt that over time, everyone would have a digital presence and/or data trail, but others were skeptical. Some data scientists are experimenting with calibrating small amounts of data and comparing them to human-collected data in an attempt to make big data less biased, a discussant explained. Another person said that by digitizing and validating government data on thousands (in the case of India, millions) of villages, big data sets could be created for those that are not using mobiles or data.

Another person pointed out that generating digital data is a process that involves much more than simple access to technology. ‘Joining the digital discussion’ also requires access to networks, local language content, and all kinds of other precursors, she said. We also need to be very aware that these kinds of data collection processes impact on people’s participation and input into data collection and analysis. ‘There’s a difference between a collective evaluation activity where people are sitting around together discussing things and someone sitting in an office far from the community getting sound bites from a large source of data.’

Where is big data most applicable in evaluation?

One discussant laid out areas where big data would likely be the most applicable to development evaluation:

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It would appear that big data has huge potential in the evaluation of complex programs, he continued. ‘It’s fairly widely accepted that conventional designs don’t work well with multiple causality, multiple actors, multiple contextual variables, etc. People chug on valiantly, but it’s expected that you may get very misleading results. This is an interesting area because there are almost no evaluation designs for complexity, and big data might be a possibility here.’

In what scenarios might we use big data for development evaluation?

This discussant suggested that big data might be considered useful for evaluation in three areas:

  1. Supporting conventional evaluation design by adding new big data generated variables. For example, one could add transaction data from ATMs to conventional survey generated poverty indicators
  2. Increasing the power of a conventional evaluation design by using big data to strengthen the sample selection methodology. For example, satellite images were combined with data collected on the ground and propensity score matching was used to strengthen comparison group selection for an evaluation of the effects of interventions on protecting forest cover in Mexico.
  3. Replacing a conventional design with a big data analytics design by replacing regression based models with systems analysis. For example, one could use systems analysis to compare the effectiveness of 30 ongoing interventions that may reduce stunting in a sample of villages. Real-time observations could generate a time-series that could help to estimate the effectiveness of each intervention in different contexts.

It is important to remember construct validity too. ‘If big data is available, but it’s not quite answering the question that you want to ask, it might be easy to decide to do something with it, to run some correlations, and to think that maybe something will come out. But we should avoid this temptation,’ he cautioned. ‘We need to remember and respect construct validity and focus on measuring what we think we are measuring and what we want to measure, not get distracted by what a data set might offer us.’

What about bias in data sets?

We also need to be very aware that big data carries with it certain biases that need to be accounted for, commented several participants; notably, when working with low connectivity populations and geographies or when using data from social media sites that cater to a particular segment of the population. One discussant shared an example where Twitter was used to identify patterns in food poisoning, and suddenly the upscale, hipster restaurants in the city seemed to be the problem. Obviously these restaurants were not the sole source of the food poisoning, but rather there was a particular kind of person that tended to use Twitter.

‘People are often unclear about what’s magical and what’s really possible when it comes to big data. We want it to tell us impossible things and it can’t. We really need to engage human minds in this process; it’s not a question of everything being automated. We need to use our capacity for critical thinking and ask: Who’s creating the data? How’s it created? Where’s it coming from? Who might be left out? What could go wrong?’ emphasized one discussant. ‘Some of this information can come from the metadata, but that’s not always enough to make certain big data is a reliable source.’ Bias may also be introduced through the viewpoints and unconscious positions, values and frameworks of the data scientists themselves as they are developing algorithms and looking for/finding patterns in data.

What about the ethical and privacy implications?

Big Data has a great deal of ethical and privacy implications. Issues of consent and potential risk are critical considerations, especially when working with populations that are newly online and/or who may not have a good understanding of data privacy and how their data may be used by third parties who are collecting and/or selling it. However, one participant felt that a protectionist mentality is misguided. ‘We are pushing back and saying that social media and data tracking are bad. Instead, we should realize that having a digital life and being counted in the world is a right and it’s going to be inevitable in the future. We should be working with the people we serve to better understand digital privacy and help them to be more savvy digital citizens.’ It’s also imperative that aid and development agencies abandon our slow and antiquated data collection systems, she said, and to use the new digital tools that are available to us.

How can we be more responsible with the data we gather and use?

Development and humanitarian agencies do need be more responsible with data policies and practices, however. Big data approaches may contribute to negative data extraction tendencies if we mine data and deliver it to decision-makers far away from the source. It will be critical for evaluators and big data practitioners to find ways to engage people ‘on the ground’ and involve more communities in interpreting and querying their own big data. (For more on responsible data use, see the Responsible Development Data Book. Oxfam also has a responsible data policy that could serve as a reference. The author of this blog is working on a policy and practice guide for protecting girls digital safety, security and privacy as well.)

Who should be paying for big data sets to be made available?

One participant asked about costs and who should bear the expense of creating big data sets and/or opening them up to evaluators and/or data scientists. Others asked for examples of the private sector providing data to the social sector. This highlighted additional ethical and privacy issues. One participant gave an example from the healthcare space where there is lots of experience in accessing big data sets generated by government and the private sector. In this case, public and private data sets needed to be combined. There were strict requirements around anonymization and the effort ended up being very expensive, which made it difficult to build a business case for the work.

This can be a problem for the development sector, because it is difficult to generate resources for resolving social problems; there is normally only investment if there is some kind of commercial gain to be had. Some organizations are now hiring ‘data philanthropist’ positions that help to negotiate these kinds of data relationships with the private sector. (Global Pulse has developed a set of big data privacy principles to guide these cases.)

So, is big data going to replace evaluation or not?

In conclusion, big data will not eliminate the need for evaluation. Rather, it’s likely that it will be integrated as another source of information for strengthening conventional evaluation design. ‘Big Data and the underlying methods of data science are opening up new opportunities to answer old questions in new ways, and ask new kinds of questions. But that doesn’t mean that we should turn to big data and its methods for everything,’ said one discussant. ‘We need to get past a blind faith in big data and get more practical about what it is, how to use it, and where it adds value to evaluation processes,’ said another.

Thanks again to all who participated in the discussion! If you’d like to join (or read about) conversations like this one, visit Technology Salon. Salons run under Chatham House Rule, so no attribution has been made in this summary post.

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Last month I joined a panel hosted by the Guardian on the contribution of innovation and technology to the Sustainable Development Goals (SDGs). Luckily they said that it was fine to come from a position of ‘skeptical realism.’

To drum up some good skeptical realist thoughts, I did what every innovative person does – posted a question on Facebook. A great discussion among friends who work in development, innovation and technology ensued. (Some might accuse me of ‘crowdsourcing’ ideas for the panel, but I think of it as more of a group discussion enabled by the Internet.) In the end, I didn’t get to say most of what we discussed on Facebook while on the panel, so I’m summarizing here.

To start off, I tend to think that the most interesting thing about the SDGs is that they are not written for ‘those developing countries over there.’ Rather, all countries are supposed to meet them. (I’m still not sure how many people or politicians in the US are aware of this.)

Framing them as global goals forces recognition that we have global issues to deal with — inequality and exclusion happen within countries and among countries everywhere. This opens doors for a shift in the narrative and framing of  ‘development.’ (See Goal 10: Reduce inequality within and among countries; and Goal 16: Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels.)

These core elements of the SDGs — exclusion and inequality – are two things that we also need to be aware of when we talk about innovation and technology. And while innovation and technology can contribute to development and inclusion…by connecting people and providing more access to information; helping improve access to services; creating space for new voices to speak their minds; contributing in some ways to improved government and international agency accountability; improving income generation; and so on… it’s important to be aware of who is excluded from creating, accessing, using and benefiting from tech and tech-enabled processes and advances.

Who creates and/or controls the tech? Who is pushed off platforms because of abuse or violence? Who is taken advantage of through tech? Who is using tech to control others? Who is seen as ‘innovative’ and who is ignored? For whom are most systems and services designed? Who is an entrepreneur by choice vs. an informal worker by necessity? There are so many questions to ask at both macro and micro levels.

But that’s not the whole of it. Even if all the issues of access and use were resolved, there are still problems with framing innovation and technology as one of the main solutions to the world’s problems. A core weakness of the Millennium Development Goals (MDGs) was that they were heavy on quantifiable goals and weak on reaching the most vulnerable and on improving governance. Many innovation and technology solutions suffer the same problem.

Sometimes we try to solve the wrong problems with tech, or we try to solve the wrong problems altogether, without listening to and involving the people who best understand the nature of those problems, without looking at the structural changes needed for sustainable impact, and without addressing exclusion at the micro-level (within and among districts, communities, neighborhoods or households).

Often a technological solution is brought in for questionable reasons. There is too little analysis of the political economy in development work as DE noted on the discussion thread. Too few people are asking who is pushing for a technology solution. Why technology? Who gains? What is the motivation? As Ory Okollah asked recently, Why are Africans expected to innovate and entrepreneur our way out of our problems? We need to get past our collective fascination with invention of products and move onward to a more holistic understanding of innovation that involves sustainable implementation, change, and improvement over the longer term.

Innovation is a process, not a product. As MBC said on the discussion thread, “Don’t confuse doing it first with doing it best.” Innovation is not an event, a moment, a one-time challenge, a product, a simple solution. Innovation is technology agnostic, noted LS. So we need to get past the goal of creating and distributing more products. We need to think more about innovating and tweaking processes, developing new paradigms and adjusting and improving on ways of doing things that we already know work. Sometimes technology helps, but that is not always the case.

We need more practical innovation. We should be looking at old ideas in a new context (citing from Stephen Johnson’s Where Good Ideas Come From) said AM. “The problem is that we need systems change and no one wants to talk about that or do it because it’s boring and slow.”

The heretical IT dared suggest that there’s too much attention to high profile innovation. “We could do with more continual small innovation and improvements and adaptations with a strong focus on participants/end users. This doesn’t make big headlines but it does help us get to actual results,” he said.

Along with that, IW suggested we need more innovative thinking and listening, and less innovative technology. “This might mean senior aid officials spending a half a day per week engaging with the people they are supposed to be helping.”

One innovative behavior change might be that of overcoming the ‘expert knowledge’ problem said DE. We need to ensure that the intended users or participants in an innovation or a technology or technological approach are involved and supported to frame the problem, and to define and shape the innovation over time. This means we also need to rely on existing knowledge – immediate and documented – on what has worked, how and when and where and why and what hasn’t, and to make the effort to examine how this knowledge might be relevant and useful for the current context and situation. As Robert Chambers said many years ago: the links of modern scientific knowledge with wealth, power, and prestige condition outsiders to despise and ignore rural peoples’ own knowledge. Rural people’s knowledge and modern scientific knowledge are complementary in their strengths and weaknesses.

Several people asked whether the most innovative thing in the current context is simply political will and seeing past an election cycle, a point that Kentaro Toyama often makes. We need renewed focus on political will and capacity and a focus on people rather than generic tech solutions.

In addition, we need paradigm shifts and more work to make the current system inclusive and fit for purpose. Most of our existing institutions and systems, including that of ‘development’ carry all of the old prejudices and ‘isms’. We need more questioning of these systems and more thinking about realistic alternatives – led and designed by people who have been traditionally excluded and pushed out. As a sector, we’ve focused a LOT on technocratic approaches over the past several years, and we’ve stopped being afraid to get technical. Now we need to stop being afraid to get political.

In summary, there is certainly a place for technology and for innovation in the SDGs, but the innovation narrative needs an overhaul. Just as we’ve seen with terms like ‘social good’ and ‘user centered design’ – we’ve collectively imbued these ideas and methods with properties that they don’t actually have and we’ve fetishized them. Re-claiming the term innovation, said HL, and taking it back to a real process with more realistic expectations might do us a lot of good.



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I had the privilege (no pun intended) of participating in the Art-a-Hack program via ThoughtWorks this past couple of months. Art-a-Hack is a creative space for artists and hackers to get together for 4 Mondays in June and work together on projects that involve art, tech and hacking. There’s no funding involved, just encouragement, support, and a physical place to help you carve out some time out for discovery and exploration.

I was paired up by the organizers with two others (Dmytri and Juan), and we embarked on a project. I had earlier submitted an idea of the core issues that I wanted to explore, and we mind-melded really well to come up with a plan to create something around them.

Here is our press release with links to the final product – WhiteSave.me. You can read our Artist Statement here and follow us on Twitter @whitesave.me. Feedback welcome, and please share if you think it’s worth sharing. Needless to say full responsibility for the project falls with the team, and it does not represent the views of any past, present or future employers or colleagues.


Announcing WhiteSave.me

WhiteSave.me is a revolutionary new platform that enables White Saviors to deliver privilege to non-Whites whenever and wherever they need it with the simple tap of a finger.

Today’s White guy is increasingly told “check your privilege.” He often asks himself “What am I supposed to do about my privilege? It’s not my fault I was born white! And really, I’m not a bad person!”

Until now, there has been no simple way for a White guy to be proactive in addressing the issue of his privilege. He’s been told that he benefits from biased institutions and that his privilege is related to historically entrenched power structures. He’s told to be an ally but advised to take a back seat and follow the lead from people of color. Unfortunately this is all complex and time consuming, and addressing privilege in this way is hard work.

We need to address the issue of White privilege now however – we can’t wait. Changing attitudes, institutions, policies and structures takes too damn long! What’s more, we can’t expect White men or our current systems to go through deep changes in order to address privilege and inequality at the roots. What we can do is leapfrog over what would normally require decades of grassroots social organizing, education, policy work, and behavior change and put the solution to White privilege directly into White men’s hands so that everyone can get back to enjoying the American dream.

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WhiteSave.me – an innovative solution that enables White men to quickly and easily deliver privilege to the underprivileged, requiring only a few minutes of downtime, at their discretion and convenience.

Though not everyone realizes it, White privilege affects a large number of White people, regardless of their age or political persuasion. White liberals generally agree that they are privileged, but most are simply tired of hearing about it and having to deal with it. Conservative White men believe their privilege is all earned, but most also consider it possible to teach people of color about deep-seated American values and traditions and the notion of personal responsibility. All told, what most White people want is a simple, direct way to address their privilege once and for all. Our research has confirmed that most White people would be willing to spend a few minutes every now and then sharing their privilege, as long as it does not require too much effort.

WhiteSave.me is a revolutionary and innovative way of addressing this issue. (Read Our Story here to learn more about our discovery moments!) We’ve designed a simple web and mobile platform that enables White men to quickly and easily deliver a little bit of their excess privilege to non-Whites, all through a simple and streamlined digital interface. Liberal Whites can assuage guilt and concern about their own privilege with the tap of a finger. Conservatives can feel satisfied that they have passed along good values to non-Whites. Libertarians can prove through direct digital action that tech can resolve complex issues without government intervention and via the free market. And non-White people of any economic status, all over the world, will benefit from immediate access to White privilege directly through their devices. Everyone wins – with no messy disruption of the status quo!

How it Works

Visit our “how it works” page for more information, or simply “try it now” and your first privilege delivery session is on us! Our patented Facial Color Recognition Algorithm (™) will determine whether you qualify as a White Savior, based on your skin color. (Alternatively it will classify you as a non-White ‘Savee’). Once we determine your Whiteness, you’ll be automatically connected via live video with a Savee who is lacking in White privilege so that you can share some of your good sense and privileged counsel with him or her, or periodically alleviate your guilt by offering advice and a one-off session of helping someone who is less privileged.

Our smart business model guarantees WhiteSave.me will be around for as long as it’s needed, and that we can continue innovating with technology to iterate new solutions as technology advances. WhiteSave.me is free for White Saviors to deliver privilege, and non-Whites can choose from our Third World Freemium Model (free), our Basic Model ($9/month), or our Premium Model ($29/month). To generate additional revenue, our scientific analysis of non-White user data will enable us to place targeted advertisements that allow investors and partners to extract value from the Base of the Pyramid. Non-Profit partners are encouraged to engage WhiteSave.me as their tech partner for funding proposals, thereby appearing innovative and guaranteeing successful grant revenue.

See our FAQs for additional information and check out our Success Stories for more on how WhiteSave.me, in just its first few months, has helped thousands to deliver privilege all over the world.

Try It Now and you’ll be immediately on your way to delivering privilege through our quick and easy digital solution!

Contact help@whitesave.me for more information. And please help us spread the word. Addressing the issue of White privilege has never been so easy!


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The July 7th Technology Salon in New York City focused on the role of Information and Communication Technologies (ICTs) in Public Consultation. Our lead discussants were Tiago Peixoto, Team Lead, World Bank Digital Engagement Unit; Michele Brandt, Interpeace’s Director of Constitution-Making for Peace; and Ravi Karkara, Co-Chair, Policy Strategy Group, World We Want Post-2015 Consultation. Discussants covered the spectrum of local, national and global public consultation.

We started off by delving into the elements of a high-quality public consultation. Then we moved into whether, when, and how ICTs can help achieve those elements, and what the evidence base has to say about different approaches.

Elements and principles of high quality public participation

Our first discussant started by listing elements that need to be considered, whether a public consultation process is local, national or global, and regardless of whether it incorporates:

  • Sufficient planning
  • Realistic time frames
  • Education for citizens to participate in the process
  • Sufficient time and budget to gather views via different mechanisms
  • Interest in analyzing and considering the views
  • Provision of feedback about what is done with the consultation results

Principles underlying public consultation processes are that they should be:

  • Inclusive
  • Representative
  • Transparent
  • Accountable

Public consultation process should also be accompanied by widespread public education processes to ensure that people are prepared to a) provide their opinions and b) aware of the wider context in which the consultation takes place, she said. Tech and media can be helpful for spreading the news that the consultation is taking place, creating the narrative around it, and encouraging participation of groups who are traditional excluded, such as girls and women or certain political, ethnic, economic or religious groups, a Salon participant added.

Technology increases scale but limits opportunities for empathy, listening and learning

When thinking about integrating technologies into national public consultation processes, we need to ask ourselves why we want to encourage participation and consultation, what we want to achieve by it, and how we can best achieve it. It’s critical to set goals and purpose for a national consultation, rather than to conduct one just to tick a box, continued the discussant.

The pros and cons of incorporating technology into public consultations are contextual. Technology can be useful for bringing more views into the consultation process, however face-to-face consultation is critical for stimulating empathy in decision makers. When people in positions of power actually sit down and listen to their constituencies, it can send a very powerful message to people across the nation that their ideas and voices matter. National consultation also helps to build consensus and capacity to compromise. If done according to the above-mentioned principles, public consultation can legitimize national processes and improve buy-in. When leaders are open to listening, it also transforms them, she said.

At times, however, those with leadership or in positions of power do not believe that people can participate; they do not believe that the people have the capacity to have an opinion about a complicated political process, for example the creation of a new constitution. For this reason there is often resistance to national level consultations from multilateral or bilateral donors, politicians, the elites of a society, large or urban non-governmental organizations, and political leaders. Often when public consultation is suggested as part of a constitution making process, it is rejected because it can slow down the process. External donors may want a quick process for political reasons, and they may impose deadlines on national leaders that do not leave sufficient time for a quality consultation process.

Polls often end up being one-off snapshots or popularity contests

One method that is seen as a quick way to conduct a national consultation is polling. Yet, as Salon participants discussed, polls may end up being more like a popularity contest than a consultation process. Polls offer limited space for deeper dialogue or preparing those who have never been listened to before to make their voices heard. Polling may also raise expectations that whatever “wins” will be acted on, yet often there are various elements to consider when making decisions. So it’s important to manage expectations about what will be done with people’s responses and how much influence they will have on decision-making. Additionally, polls generally offers a snapshot of how people feel at a distinct point in time, but it may be important to understand what people are thinking at various moments throughout a longer-term national process, such as constitution making.

In addition to the above, opinion polls often reinforce the voices of those who have traditionally had a say, whereas those who have been suffering or marginalized for years, especially in conflict situations, may have a lot to say and a need to be listened to more deeply, explained the discussant. “We need to compress the vertical space between the elites and the grassroots, and to be sure we are not just giving people a one-time chance to participate. What we should be doing is helping to open space for dialogue that continues over time. This should be aimed at setting a precedent that citizen engagement is important and that it will continue even after a goal, such as constitution writing, is achieved,” said the discussant.

In the rush to use new technologies, often we forget about more traditional ones like radio, added one Salon participant, who shared an example of using radio and face to face meetings to consult with boys and girls on the Afghan constitution. Another participant suggested we broaden our concept of technology. “A plaza or a public park is actually a technology,” he noted, and these spaces can be conducive to dialogue and conversation. It was highlighted that processes of dialogue between a) national government and the international community and b) national government and citizens, normally happen in parallel and at odds with one another. “National consultations have historically been organized by a centralized unit, but now these kinds of conversations are happening all the time on various channels. How can those conversations be considered part of a national level consultation?” wondered one participant.

Aggregation vs deliberation

There is plenty of research on aggregation versus deliberation, our next discussant pointed out, and we know that the worst way to determine how many beans are in a jar is to deliberate. Aggregation (“crowd sourcing”) is a better way to find that answer. But for a trial, it’s not a good idea to have people vote on whether someone is guilty or not. “Between the jar and the jury trial, however,” he said, “we don’t know much about what kinds of policy issues lend themselves better to aggregation or to deliberation.”

For constitution making, deliberation is probably better, he said. But for budget allocation, it may be that aggregation is better. Research conducted across 132 countries indicated that “technology systematically privileges those who are better educated, male, and wealthier, even if you account for the technology access gaps.” This discussant mentioned that in participatory budgeting, people tend to just give up and let the educated “win” whereas maybe if it were done by a simple vote it would be more inclusive.

One Salon participated noted that it’s possible to combine deliberation and aggregation. “We normally only put things out for a vote after they’ve been identified through a deliberative process,” he said, “and we make sure that there is ongoing consultation.” Others lamented that decision makers often only want to see numbers – how many voted for what – and they do not accept more qualitative consultation results because they usually happen with fewer people participating. “Congress just wants to see numbers.”

Use of technology biases participation towards the elite

Some groups are using alternative methods for participatory democracy work, but the technology space has not thought much about this and relies on self-selection for the most part, said the discussant, and results end up being biased towards wealthier, urban, more educated males. Technology allows us to examine behaviors by looking at data that is registered in systems and to conduct experiments, however those doing these experiments need to be more responsible, and those who do not understand how to conduct research using technology need to be less empirical. “It’s a unique moment to build on what we’ve learned in the past 100 years about participation,” he said. Unfortunately, many working in the field of technology-enabled consultation have not done their research.

These biases towards wealthier, educated, urban males are very visible in Europe and North America, because there is so much connectivity, yet whether online or offline, less educated people participate less in the political process. In ‘developing’ countries, the poor usually participate more than the wealthy, however. So when you start using technology for consultation, you often twist that tendency and end up skewing participation toward the elite. This is seen even when there are efforts to proactively reach out to the poor.

Internal advocacy and an individual’s sense that he or she is capable of making a judgment or influencing an outcome is key for participation, and this is very related to education, time spent in school and access to cultural assets. With those who are traditionally marginalized, these internal assets are less developed and people are less confident. In order to increase participation in consultations, it’s critical to build these internal skills among more marginalized groups.

Combining online and offline public consultations

Our last discussant described how a global public consultation was conducted on a small budget for the Sustainable Development Goals, reaching an incredible 7.5 million people worldwide. Two clear goals of the consultation were that it be inclusive and non-discriminatory. In the end, 49% who voted identified as female, 50% as male and 1% as another gender. Though technology played a huge part in the process, the majority of people who voted used a paper ballot. Others participated using SMS, in locally-run community consultation processes, or via the website. Results from the voting were visualized on a data dashboard/data curation website so that it would be easier to analyze them, promote them, and encourage high-level decision makers to take them into account.

Some of the successful elements of this online/offline process included that transparency was a critical aspect. The consultation technology was created as open source so that those wishing to run their own consultations could open it, modify it, and repackage it however they wanted to suit their local context. Each local partner could manage their own URL and track their own work, and this was motivating to them.

Other key learning was that a conscious effort has to be made to bring in voices of minority groups; investment in training and capacity development was critical for those running local consultations; honesty and transparency about the process (in other words, careful management of expectations); and recognize that there will be highs and lows in the participation cycle (be sensitive to people’s own cycles and available time to participate).

The importance of accountability

Accountability was a key aspect for this process. Member states often did not have time to digest the results of the consultation, and those running it had to find ways to capture the results in short bursts and visually simple graphics so that the consultation results would be used for decision making. This required skill and capacity for not only gathering and generating data but also curating it for the decision-making audience.

It was also important to measure the impact of the consultation – were people’s voices included in the decision-making process and did it make a difference? And were those voices representative of a wide range of people? Was the process inclusive?

Going forward, in order to build on the consultation process and to support the principle of accountability, the initiative will shift focus to become a platform for public participation in monitoring and tracking the implementation of the Sustainable Development Goals.

Political will and responsiveness

A question came up about the interest of decision-makers in actually listening. “Leaders often are not at all interested in what people have to say. They are more concerned with holding onto their power, and if leaders have not agreed to a transparent and open process of consultation, it will not work. You can’t make them listen if they don’t want to. If there is no political will, then the whole consultation process will just be propaganda and window dressing,” one discussant commented. Another Salon participant what can be done to help politicians see the value of listening. “In the US, for example, we have lobbyists, issues groups, PACs, etc., so our politicians are being pushed on and demanded from all sides. If consultation is going to matter, you need to look at the whole system.” “How can we develop tools that can help governments sort through all these pressures and inputs to make good decisions?” wondered one participant.

Another person mentioned Rakesh Rajani’s work, noting that participation is mainly about power. If participation is not part of a wider system change, part of changing power structures, then using technology for participation is just a new tool to do the same old thing. If the process is not transparent and accountable, or if you engage and do not deliver anything based on the engagement, then you will lose future interest to engage.

Responsiveness was also raised. How many of these tech-fueled participation processes have led to governments actually changing, doing something different? One discussant said that evidence of impact of ICT-enabled participation processes was found in only 25 cases, and of those only 5 could show any kind of impact. All the others had very unclear impact – it was ambiguous. Did using ICTs make a difference? There was really no evidence of any. Another commented that clearly technology will only help if government is willing and able to receive consultation input and act on it. We need to find ways to help governments to do that, noted another person.

As always, conversation could have continued on for quite some time but our 2 hours was up. For more on ICTs and public consultations, here is a short list of resources that we compiled. Please add any others that would be useful! And as a little plug for a great read on technology and its potential in development and political work overall, I highly recommend checking out Geek Heresy: Rescuing Social Change from the Cult of Technology from Kentaro Toyama. Kentaro’s “Law of Amplification” is quite relevant in the space of technology-enabled participation, in that technology amplifies existing human behaviors and tendencies, and benefits those who are already primed to benefit while excluding those who have been traditionally excluded. Hopefully we’ll get Kentaro in for a Tech Salon in the Fall!

Thanks to our lead discussants, Michele, Tiago and Ravi, and to Thoughtworks for their generous hosting of the Salon! Salons are conducted under Chatham House Rule so no attribution has been made in this post. Sign up here if you’d like to receive Technology Salon invitations.

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by Hila Mehr and Linda Raftree

On March 31, 2015, nearly 40 participants, joined by lead discussants Robert Fabricant, Dalberg Design Team; Despina Papadopoulos, Principled Design; and Roop Pal, PicoSatellite eXploration Lab; came together for Technology Salon New York City where we discussed the future of wearables in international development. As follows is a summary of our discussion.

While the future of wearables is uncertain, major international development stakeholders are already incorporating wearables into their programs. UNICEF Kid Power is introducing wearables into the fight against malnutrition, and is launching a Global Wearables Challenge. The MUAC (mid-upper arm circumference) band already exists in international health. Other participants present were working on startups using wearables to tackle global health and climate change.

As Kentaro Toyama often says “technology is an amplifier of human intent” and the Tech Salon discussion certainly resonated with that sentiment. The future of wearables in international development is one that we–the stakeholders as consumers, makers, and planners–will create. It’s important to recognize the history of technology interventions in international development, and that while wearables enable a new future, technology interventions are not new; there is a documented history of failures and successes to learn from. Key takeaways from the Salon, described below, include reframing our concept of wearables, envisioning what’s possible, tackling behavior change, designing for context, and recognizing the tension between data and privacy.

Reframing our Concept of Wearables

Our first discussant shared historical and current examples of wearables, some from as far back as the middle ages, and encouraged participants to rethink the concept of wearables by moving beyond the Apple Watch and existing, primarily health-related, use cases. While Intel, Arm, and Apple want to put chips on and in our bodies, and we think these are the first cases of wearables, glasses have always been wearable, and watches are wearables that change our notions of time and space. In short, technology has always been wearable. If we stay focused on existing, primarily luxury, use cases like FitBit and Apple Watch, we lose our creativity in new use cases for varying scenarios, he said.

In many cases of technology introduction into a ‘developing world’ context, the technology adds a burden rather than contributing ease. We should be thinking about how wearables can capture data without requiring input, for example. There is also an intimacy with wearables that could eliminate or reframe some of the ingrained paradigms with existing technologies, he noted.

In the most common use cases of wearables and other technology in international development, data is gathered and sent up the chain. Participants should rethink this model and use of wearables and ensure that any data collected benefits people in the moment. This, said the discussant, can help justify the act of wearing something on the body. The information gathered must be better incorporated into a personal-level feedback loop. “The more intimate technology becomes, the greater responsibility you have for how you use it,” he concluded. 

In the discussion of reframing our notion of wearables, our second discussant offered a suggestion as to why people are so fascinated with wearables. “It’s about the human body connected to the human mind,” she explained. “What is it to be human? That’s why we’re so fascinated with wearables. They enlarge the notion of technology, and the relationship between machine, human, and animal.”

Envisioning What’s Possible

In discussing the prominent use of wearables for data collection, one participant asked, “What is possible to collect from the body? Are we tracking steps because that is what we want to track or because that is what’s possible? What are those indicators that we’ve chosen and why?”

We need to approach problems by thinking about both our priorities and what’s possible with wearable technology, was one reply. “As consumers, designers, and strategists, we need to push more on what we want to see happen. We have a 7-year window to create technology that we want to take root,” noted our lead discussant.

She then shared Google Glass as an example of makers forgetting what it is to be human. While Google Glass is a great use case for doctors in remote areas or operators of complex machinery, Google Glass at dinner parties and in other social interactions quickly became problematic, requiring Google to publish guidelines for social uses cases. “It’s great that it’s out there as a blatant failure to teach other designers to take care of this space,” she said. 

Another discussant felt that the greatest opportunity is the hybrid space between specialized and the generalized. The specialized use cases for wearables are with high medical value. And then there are the generalized cases. With expensive and new technology, it becomes cheaper and more accessible as it meets those hybrid use cases in-between specialized and generalized to justify the cost and sophistication of technology. Developing far out and futuristic ideas, such as one lead discussant’s idea for a mind-controlled satellite, can also offer opportunities for those working with and studying technology to unpack and ‘de-scaffold’ the layers between the wearable technology itself and the data and future it may bring with it.

Tackling Behavior Change

One of the common assumptions with wearables is that our brains work in a mechanical way, and that if we see a trend in our data, we will change our behavior. But wearables have proven that is not the case. 

The challenge with wearables in the international development context is making sure that the data collected serves a market and consumer need — what people want to know about themselves — and that wearables are not only focused on what development organizations and researchers want to know. Additionally, the data needs to be valuable and useful to individuals. For example, if a wearable tracks iron levels but the individual doesn’t understand the intricacies of nutrition, their fluctuations in iron levels will be of no use.

Nike Plus and its FuelBand has been one of the most successful activity trackers to date, argued one discussant, because of the online community created around the device. “It wasn’t the wearable device that created behavior change, but the community sharing that went with it.” One participant trained in behavioral economics noted the huge potential for academic research and behavioral economists with the data collected from wearables. A program she had worked on looked closely at test-taking behaviors of boys versus those of girls, and wearables were able to track and detect specific behaviors that were later analyzed and compared.

Designing for Context

Mainstream wearables are currently tailored for the consumer profile of the 35-year-old male fitness buff. But how do we think about the broader population, on the individual and community level? How might wearables serve the needs of those in emergency, low resource, or conflict settings? And what are some of the concerns with wearables?

One participant urged the group to think more creatively. “I’m having trouble envisioning this in the humanitarian space. 5-10 years out, what are concrete examples of someone in Mali, Chad, or Syria with a wearable. How is it valuable? And is there an opportunity to leapfrog with this technology?”

Humanitarian disaster contexts often face massive chaos, low literacy rates, and unreliable Internet connectivity, if Internet exists at all. How can wearables be useful in these cases? One participant suggested they could be used for better ways of coordinating and organizing — such as a warning siren signal wearable for individuals in warzones, or water delivery signal wearable for when water arrives — while keeping in mind real restrictions. For example, there are fears today about vaccines and other development agency interventions. This may escalate with wearable devices or edible tracking devices.

No amount of creativity, however, replaces the realistic and sustainable value of developing technology that addresses real needs in local contexts. That’s where human-centered design and participatory processes play a vital role. Wearable products cannot be built in isolation without users, as various participants highlighted.

As one lead discussant said, we too often look at technology as a magic bullet and we need to avoid doing this again when it comes to wearables. We can only know if wearable technology is an appropriate use case by analyzing the environment and understanding the human body. In Afghanistan, she noted, everyone has an iPhone now, and that’s powerful. But not everyone will have a FitBit, because there is no compelling use case.

Appropriate use cases can be discovered by involving the community of practice from day one, making no assumptions, and showing and sharing methodology and processes. Makers and planners should also be wary of importing resources and materials, creating an entire new ecosystem. If a foreign product breaks with no access to materials and training, it won’t be fixed or sustainable. Designing for context also means designing with local resources and tailored to what the community currently has access to. At the same time, international development efforts and wearable technology should be about empowering people, and not infantilizing them.

The value of interdisciplinary teams and systems maps cannot be overlooked, participants added. Wearables highlight our individual-centric nature, while systems thinking and mapping shows how we relate with ourselves, our community, and the world. Thinking about all of these levels will be important if wearables are to contribute to development in a positive way.

Tensions around Privacy, Data, and Unethical Uses

Wearables exist in tension with identity, intimacy, and privacy. As consumers, users, makers, and planners of wearables, we have to think critically and deeply about how we want our data to be shared. One discussant emphasized that we need to involve VCs, industry, and politicians in discussion around the ethical implications of wearable technology products. The political implications and erosion of trust may be even more complex in developing world contexts, making a consortia and standards even more necessary. 

One participant noted the risks of medical wearable technology and the lack of HIPAA privacy requirements in other countries. The lack of HIPAA should not mean that privacy concerns are glossed over. The ethics of testing apply no matter the environment, and testing completely inappropriate technology in a developing context just for the captive audience is ethically questionable.

Likewise, other participants raised the issue of wearables and other types of technology being used for torture, mind control and other nefarious purposes, especially as the science of ‘mind hacking’ and the development of wearables and devices inserted under the skin becomes more sophisticated.

Participants noted the value in projects like the EU’s Ethics Inside and the pressure for a UN Representative on privacy rights. But there is still much headway to be made as data privacy and ethical concerns only grow.

The Future We Wear

The rapid evolution of technology urges us to think about how technology affects our relationships with our body, family, community, and society. What do we want those relationships to look like in the future? We have an opportunity, as consumers, makers and planners of wearables for the international context to view ourselves as stakeholders in building the future opportunities of this space. Wearables today are where the Internet was during its first five mainstream years. Now is the perfect time to put our stake in the ground and create the future we wish to exist in.


Our Wearables and Development background reading list is available here. Please add articles or other relevant resources or links.

Other posts about the Salon, from Eugenia Lee and Hila Mehr.

Many thanks to our lead discussants and participants for joining us, and a special thank you to ThoughtWorks for hosting us and providing breakfast!

Technology Salons run under Chatham House Rule, therefore no attribution has been made in this summary post. If you’d like to join future Salons to discuss these and related issues at the intersection of technology and development, sign up at Technology Salon.

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panel session photoIn line with my last post (10 myths about girls empowerment and mobile learning), I thought I’d also share what we covered during our panel on ‘Gender Sensitive Content and Pedagogy’ during UNESCO and UN Women’s Mobile Learning Week 2015. This year’s theme was ‘leveraging technology to empower women and girls.’ UN Women did a fantastic job of finding really smart women with varied backgrounds to join the panel, including: Sarah Jaffe, Worldreader;  Andrea Bertone, FHI360; Hongjuan Liu, Beijing Royal School; Catherine King, Global Fund for Women; and Anne Githuku-Shongwe, Afroes. I had the pleasure of moderating the conversation, and here’s some of what we talked about. I’ll put up a few more posts after this one to share the full session.

First, what is ‘gender responsive content?’ Hongjuan sent over a general introduction to include in this post. To begin with, she said, simply having access to schools does not guarantee a proper education and a better future. “Outdated teaching materials silently reinforce girls’ sense of inferiority. Materials rarely picture woman as managers, pilots, doctors or political leaders. The subconscious words neglect the contributions of girls and women to the modern economic world and show women as subordinate to men.” Even worse, she noted, “unless they are trained on gender sensitivity, most teachers and parents are not knowledgeable enough to banish gender bias. Silence in the face of discrimination is the equivalent of allowing lies and distorted facts to continue. And, such blindness is even more dangerous to the gender-bias content itself. As a result, these mistakenly delivered messages will denigrate girls and women from one generation to another.”

According to Hongjuan, teachers are a critical part of efforts to “dig out the seeds of gender-bias in our children’s heart” and they should be paying attention to both content and pedagogy. “Given that boys and girls learn differently, we need to employ diverse pedagogies in order to respond to different learning styles –from small group, individual, lecture, reading, experiences, laboratory work, etc. Diversity in pedagogy matters and increases the opportunities for all students to learn.”

Overturning gender stereotyping must be a collective and universal effort, she said. “Institutions must respond to the call to overturn gender bias discrimination. Some citizens are too weak to resist the strong stereotypes present in their countries and religions. Life is too short to wait to base our actions on a collective worldwide outcry for a harmonious world where woman and man are equally accepted, appreciated and treated. At the very least we should live by our words and deeds so that we are seen as desiring and fighting for equality. We should wish to be painted as believing in not only the potential of women and girls, but the rights they should have. That will inspire women to work to craft their own more promising future.”

Andrea noted that we should pay attention to gender responsive content and pedagogy because “if we don’t prioritize gender responsive content we see the consequences: girls and boys who stay disempowered and miss out on learning opportunities which challenge the unequal gender norms that they are socialized to believe.” In addition, she said, gender-responsive content offers rich tools that we can use to transform unequal gender norms — “those norms that dictate to girls what they can and can’t do, where they can or can’t go, or norms that encourage boys to engage in harmful behaviors against themselves and others.” We have the potential to link two extremely relevant and potentially transformative mechanisms — mobile and gender sensitive content and pedagogy — in the education space, “and that is quite exciting!” Andrea added.

Sarah agreed, noting that what we experience in media and literature shapes us, particularly as children.  “If a girl never sees an example of a woman neuroscientist, in either fiction or non-fiction, how will she know that is a possibility for her?”  We know life gives us all sorts of examples that challenge literary tropes, but “when we are inundated with one-note ideas of what it means to be a boy or a girl, these shape us in subconscious ways,” she said. “This example applies mainly to fiction, but of course, non-fiction and informational gender responsive content is also key.”

Hongjuan shared how she was influenced by gender stereotyping. “I chose to be a teacher, because this is the best thing I found in books. Women were never pictured in other roles. These subconscious words imply that a girl’s sweat is so cheap that it will never win them a higher social status,” she said. “We need to change these gender biases. These mistaken messages poison girls and woman from one generation to another.”

“We need to be a part of combating these persistent stereotypes,” continued Catherine. “A lack of representation and the misrepresentation of women and girls persist in mainstream media.” We see this as well in non-traditional sectors, including in the online environment, she noted. “As content developers, we have an opportunity – a responsibility – to disrupt pervasive stereotypical and counterproductive images.” Catherine explained that the Global Fund for Women has expanded its mission to prioritize raising the voices of women via digital storytelling and advocacy campaigns as an equal lever to grant making to create greater momentum for the change we all want to see in the long term.

Finally, Anne noted that “today, even in Africa, we live in a connected world that is more transparent, where oppression, harassment or discrimination are not cool and are in fact are exposed because of our connectedness.” She referred to stories we’ve all become aware of — rape in India, pedophiles, the Arab Spring. “On the other hand, gendered relationships at home, at work and in public spaces have changed forever as women’s choices open up more and more.” In the meantime, however, “we old school parents and teachers continue to enforce old stereotypes that are close to dead to the world – confusing our young ones.” Anne emphasized that it is critical to equip young men and women – our future leaders – for a new reality. “In our work building motivated learning products on mobile — using games and gamification rules — we are at pains in our engaged user-based design and testing processes to challenge gender stereotypes and offer a platform to shape new ones. Gender-responsive content is not a nicety, it is imperative!!”

Tune in over the next week or two for summaries of the other areas covered on the panel, including: combating unconscious gender bias; the role of mobile in creation/implementation of gender-responsive content and pedagogy; challenges in the area of gender-sensitive mobile learning; and thoughts on where we can expect mobile technology and gender-responsive content and pedagogy to head in the future.


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Cameroon - realizing phone takes videoI had the chance to share some thoughts at UNESCO’s recent Mobile Learning Week. My presentation explored some myths about girls empowerment and mobile learning and offered suggestions of things to think about when designing and implementing programs. Ideas for the presentation were drawn from research and practitioner experiences (mine and those of others that I’ve talked with and worked with over the past few years). Here’s what I talked about below. Since realities are subjective and complex, and contexts differ immensely around the world, I’m putting these out mainly as discussion starters. Some seem super obvious and some contradict each other (which may speak to the point that there is no universal truth!), so I’m curious to know what other people think…

Myth 1: Mobile as a stand-alone solution.

Reality: The mobile phone is just one part of the informational and cultural ecosystem. There is a lot of hype about mobile. I think as a sector we are mostly past the idea of mobile as a stand-alone solution, but in case not, it’s the first myth I’d challenge. There is not a lot that a mobile phone can do as a stand-alone tool to empower girls or improve their education and learning. 

Things to consider: The mobile phone is the device that is most likely to already be in the hands of your target user — but the possibilities and channels don’t start and end with mobile phones. It’s important to think of the mobile phone as just one part of a much wider informational, social, cultural and educational ecosystem and see where it might fit in to support girls’ learning. It’s likely that mobile phones will be used more outside of the classroom than in – in my experience, I’ve found that schools often don’t allow mobiles to be brought into class. So, it’s more about integrating mobiles as a tool that supports rather than as the sole channel for learning and information sharing.

Myth 2: It’s the technology that’s mobile.

Reality: In most cases, the learner is mobile, too. This is one of the exciting things about technology and learning. It’s something I heard John Traxler say a few years ago, and I thought it was really smart. John said we should really be thinking about mobile learners, not just mobile technology. Learners access and share information in all kinds of ways, at different locations, using different devices or not using devices at all.

Things to consider: Rather than starting with the mobile phone, think about design based on a clear understanding of ’digital repertoires’ – in other words, user behaviors or patterns that span places and devices based on factors like data capacity, cost, purpose. These repertoires will differ according to culture, sex, economic status, and availability of information points and sources. For example, maybe some girls use Google search to do homework at an Internet café but use their own phone or a borrowed phone for quick, short text reminders or questions to friends about schoolwork. Maybe other girls are not allowed to go to Internet cafés or they feel uncomfortable doing so, and they rely more on their mobile phone and their friends. This was the case in one community near Jakarta that I was in last month. One of the girls talked about her 15-year-old friend:


“She’s too shy to go to the Internet shop…. Boys are always sitting out, calling you to ask ‘where are you going?’ or whistling. She feels too embarrassed to go into the shop because everyone will look at her.”

In a consultation conducted by Plan in 2011, girls in some countries said it was too dangerous to travel to the Internet café, especially at night. When men and boys watch porn and play video games in Internet cafes, girls tend to feel quite uncomfortable. Libraries, if available, may be places where girls go to access Internet because they feel safer. Girls may face reputation risk if they go too often to the Internet café. So in this case, girls may rely on phones. In some parts of East and West Africa, however, girls with mobile phones may be accused of having ‘sugar daddies’ or selling sex for airtime or nice phones, so the phone also carries reputation risk. All of these situations impact on girls’ communication repertoires, and program designers need to take them into consideration. And perhaps most importantly, ‘girls’ are not a homogeneous group so we always need to unpack which girls, where, when, what, at what age, living where, with what kinds of social or cultural restrictions, etc.

Myth 3: Vulnerable girls don’t have access to mobiles.

Reality: Many girls with phones are more vulnerable than we think, and more girls that we consider vulnerable are accessing mobiles. This is something that Colman Chamberlain from the Girl Effect’s mobile initiative pointed out. “We often hear that the most vulnerable girls don’t have access to mobile phones,” he says, “but this depends on how we understand and define vulnerability. Many girls with phones are vulnerable, and many vulnerable girls are starting to access mobile. This means we have a real chance to reach and engage with them.”

Things to consider: Age does normally play a role in access to mobiles. Younger girls from lower income families in most countries do not have their own mobile phones. Upper class children may, however, have phones. It really varies. Recent research (unpublished) found that it was common for 14-15 yr olds in Indonesia to have their own phones. In India and Bangladesh, that age was closer to 18. Girls who were no longer in school often had a mobile — some had even dropped out to get jobs in order to purchase a mobile. Sometimes married girls’ husbands purchase them a phone, yet it may be primarily to control and monitor their whereabouts.

When designing programs, it’s really important to take the time to learn whether the girls you’d like to work with own or borrow mobile phones and whether their access is controlled by someone else or if they are free to use a mobile however they’d like. Design for different scenarios and ‘user repertoires’ based on girls’ access and use habits. Don’t make assumptions on which girls access mobiles for what and how based on perceived vulnerability, do the research and you may be surprised when you get into the weeds.

Myth 4: Cost is the biggest barrier to girls’ mobile phone access and use. 

Reality: Cost is a barrier, but perhaps not the biggest one. Clearly cost is still a big barrier for the poorest girls. But the unwillingness to invest in a girl’s access to mobile or to information and learning is linked to other aspects like a girl’s position in her family or society. Mobiles are also becoming cheaper, so the cost barrier has been reduced in some ways. Overall, compared to landlines, as Katie Ramsay at Plan Australia notes, mobile is cheaper and that opens up access to information for even the poorest families.

Research conducted this past year in India, Bangladesh and Indonesia, found that in some communities girls have much greater access than assumed, and cost was a lower barrier than originally thought. Parents and gatekeepers were actually a bigger barrier in some countries. For many of us this is a total no-brainer, but I still think it’s worth bringing up.

Things to consider: As already mentioned, the key when developing programs is to dig deep and talk with girls directly to understand and help them to overcome different barriers, whether those are personal, familiar, economic, societal or institutional.

In order to help get past these barriers, mobile-enabled programming or product/service offerings need to have real value to girls as well as their gatekeepers, so that girls’ participation in programs and use of mobiles is seen by gatekeepers as positive. This was shown clearly in a UNESCO girls’ literacy program in Pakistan, where 87% of parents changed from a negative opinion about girls using a mobile phone to a positive perspective by the end of the program, because they saw the utility of the phone for girls’ literacy.

It’s important to do work on educating and changing behaviors of parents. Katie Ramsay also notes that in places where men own the tech, there is a huge opportunity for targeting them to gain their support for girls’ education. So it’s worth re-thinking the role of mobiles in girl-focused programs, especially where girls’ access to mobile is low or controlled. The best use of mobiles for learning may not be ‘delivering content’ to girls via a mobile device. Instead it might be using mobile and other media to target gatekeepers to change their behavior and beliefs around girls’ education and girls’ empowerment.

Myth 5: Girls share their phones.

Reality: Phone sharing brings with it a challenging social power dynamic. Many people in ‘the West’ hold the romantic notion that people in ‘developing countries’ like to share everything and live communally. Now, I’m not saying that girls are not generous, but when it comes to girls and phones, we have not really seen a great desire to share.

In some of the unpublished research conducted in Asia (and previously referenced in this post), girls without phones said that they do borrow phones, often from family members or friends, but they don’t necessarily like doing so. They said that borrowing here and there just isn’t enough to do anything substantial on a phone. Girls described girls who do not have mobile phones as sad and unpopular. They drew girls with phones as happy, popular, and successful. Some girls also described girls with phones as stuck up and selfish and said that girls who have phones don’t share them with girls that don’t have phones.


“A girl with a phone would look down on me, and show off what her phone does. She would let me hold it, but only because she would like to take it back from me again.” —Girl, 18, Dhaka

I was at a school in Cameroon last year, when a big fight broke out because one girl had taken another girl’s phone and thrown it in the toilet. The professor said that fighting over mobile phones was common among students. Phones had been prohibited at school in part to reduce conflicts, and sometimes students ratted each other out for having phones at school. This is not specifically a “mobile phone” problem, it’s a wealth or class or equity issue, but it manifests itself with phones because they are an asset that defines haves and have-nots. 

Things to consider: Don’t assume it’s easy for girls to borrow phones. If you find that many of your targeted users for a mobile-enabled initiative are borrowers, then it’s important to design short, to-the-point options for them, because they may have only a few minutes at a time with a mobile. Girls may not share their phones unless there is some kind of incentive for doing so. If you are designing for borrowers, think about rapid communication in bursts, and don’t communicate about anything that would put a girl at social or reputation risk if the person she borrows the phone from should see it.

Myth 6: All girls (& all youth) are tech savvy.

Reality: Many girls are indeed tech savvy, but some are still behind the curve. In many places, girls with phones are way more tech savvy than their parents. And most young people around the world are pretty quick to pick up on technology. But girls’ level of savvy will obviously depend on what they have access to.

Girls I talked with in the urban slums areas of Jakarta were quite tech-adept and had Internet-ready phones, but they still only used Facebook and Google. They also mixed up ‘Facebook’ and ‘Google’ with ‘The Internet’ and did not use email. They were unfamiliar with the concept of an “app”. Girls knew how to search for jobs online (via Google), but they said they had trouble understanding how to fill out online forms to apply for those jobs. So regardless of a girl’s level of tech savvy, in this case, she was still missing certain skills and relevant online content that would have helped her get to the next level of job-seeking.

Things to consider: It’s really important to do your research to understand what technologies and platforms girls are familiar with and be sure to plan for how to engage girls with those that they are unfamiliar with. Basic literacy might also still be a huge issue among adolescent girls in some places.

Basically, the message here again is to avoid making assumptions, to do your research, and to remember that girls are not a homogeneous group. Market research techniques can be helpful to really start understanding nuances regarding which girls do what, where and how on a mobile device.

Myth 7: Girls don’t have time to use mobile phones.

Reality: You might be surprised by which girls find time to spend on a mobile phone. This again really depends on which girls, and where! Girls find the time to use mobile, even if it’s not at the always on-line levels that we find in places like the US and Europe, notes Colman from Girl Effect. Spending time in the communities you’re working with can allow you to find times that girls have free and uncontrolled access. Jessica Heinzelman from DAI told us that in one project she was working on, they had assumed that girls in more traditional communities and rural geographies would have less access to mobiles. In reality, it was common for girls to be sent on errands with mobiles to places where there was connectivity to contact relatives on behalf of the family, leaving the girls with at least some alone time with the mobile.

Schoolgirls in the slum area of Jakarta that I worked in earlier this year said they checked their Facebook every day. Out of school urban girls checked at least a few times per week, and rural out of school girls also usually managed to borrow a phone to check Facebook quickly now and then.

Things to consider: I’m beating the drum again here about the importance of on-the-ground research and user testing to find out what is happening in a particular context. Alexandra Tyers from GSMA points out that user testing is really a critical piece of any girls and mobile learning effort, and that it can actually be done for a reasonable price. She notes that in her case, “Bangladesh user testing cost $5,000 USD for fifty tests in five different locations around the country. And yet the return on investment by making those necessary changes is likely to be large because making sure the product is right will ensure easy adoption and maximum uptake.”

Myth 8: Mobile phones can’t address girls’ real needs.

Reality: Mobile phones can help address girls’ real needs, but probably not as stand-alone devices, and maybe not as ‘content delivery’ channels. There is a lot of hype around mobile learning and mEducation, and as some presenters talked about at Mobile Learning Week, there is little evidence to help us know how to integrate mobiles in ways that could scale (where appropriate) and offer real results. I sometimes think this is because we are expecting mobile and ICTs in general to do more than they feasibly can.

Depending on the context and situation, where I have seen the greatest opportunity for mobiles is:

  • enabling girls to connect with peers and information
  • allowing girls more opportunities for voicing their opinions
  • linking girls to online support and services
  • linking girls with offline support and services.
  • helping organizations to track and monitor their programs (and hopefully then do a better job of adapting them to girls’ real needs).

Things to consider: It’s really important to think through what the best role for mobile is (if any role at all). Here is where you can (and should) be super creative. You may not get the biggest impact by involving girls as the end user. Rather, the best place might be aiming your mobile component at behavior change with gatekeepers. Or sending text messages that link a girl to a service or opportunity that lives offline. It might be getting feedback on the school system or using mobile to remind parents about school meetings.

Myth 9: Mobile phones are dangerous.

Reality: Many girls and women say a mobile helps them feel safer, more independent, and more successful. The 2011 Cherie Blair/GSMA study on women and mobiles noted that 93% of women said a mobile made them feel safer and 84% felt more independent. Tech can also offer a certain level of anonymity for girls that can be beneficial in some cases. “Tech is good for girls because they can be anonymous. If you go to the bank, everyone can see you’re a girl. But if you start a business online, they don’t know that you’re a girl, so you don’t have to deal with the stereotypes,” according to Tuulia Virha, formerly of Plan Finland. Parents may also see mobiles as a tool to help them keep their children safe.

Things to consider: Mobiles can help with an increased sense of security, safety and autonomy, depending on context and situation. However, and this is what I’ll say next, mobiles also bring risk with them, and most girls we talked to for our research were aware of obvious risks – meeting strangers, exposure to pornography, pedophiles and trafficking – but not so aware of other risks like privacy. They were also not very aware of how to reduce their risk levels. So in order to really reap the safety and empowerment rewards that mobiles can bring, initiatives need to find ways to improve girls’ digital literacy and digital safety. Data security is another issue, and organizations should develop responsible data policies so that they are not contributing to putting girls at risk.

And that brings us to the other side of the coin – the myth that mobiles make girls safer.

Myth 10: Mobiles make girls safer.

Reality: Mobiles can put girls at risk. That sense of being safer with a mobile in hand can be a false one, as I noted above. Dirk Slater, from Tactical Technology Collective noted, “A big issue of working with adolescent girls is their lack of awareness of how the information they share can be stored and used. It’s important to educate girls. Look at how much information you find out about a person through social media, and what does that mean about how much information someone else can find about them.”

Things to consider: Institutions should aim to mitigate risks and help to improve girls’ digital security and safety.

Girls face safety risks on mobile at a number of levels, including:

  • Content
  • Contact
  • Data privacy and security
  • Legal and political risk (in some places they may face backlash simply for seeking out an education)
  • Financial risk (spam, hacking, spending money they don’t have on airtime)
  • Reputation risk (if they participate on social networks or speak out)

It’s also key for organizations working with girls and mobile to develop ethical policies and procedures to mitigate risks at various levels.

And that’s that for the top 10 myths! Curious to know what you think about those, and if there are other myths you find in your work with girls, mobile and learning….


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