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Archive for the ‘mobile and technology’ Category

For our Tuesday, July 27th Salon, we discussed partnerships and interoperability in global health systems. The room housed a wide range of perspectives, from small to large non-governmental organizations to donors and funders to software developers to designers to healthcare professionals to students. Our lead discussants were Josh Nesbit, CEO at Medic Mobile; Jonathan McKay, Global Head of Partnerships and Director of the US Office of Praekelt.org; and Tiffany Lentz, Managing Director, Office of Social Change Initiatives at ThoughtWorks

We started by hearing from our discussants on why they had decided to tackle issues in the area of health. Reasons were primarily because health systems were excluding people from care and organizations wanted to find a way to make healthcare inclusive. As one discussant put it, “utilitarianism has infected global health. A lack of moral imagination is the top problem we’re facing.”

Other challenges include requests for small scale pilots and customization/ bespoke applications, lack of funding and extensive requirements for grant applications, and a disconnect between what is needed on the ground and what donors want to fund. “The amount of documentation to get a grant is ridiculous, and then the system that is requested to be built is not even the system that needs to be made,” commented one person. Another challenge is that everyone is under constant pressure to demonstrate that they are being innovative. [Sidenote: I’m reminded of this post from 2010….] “They want things that are not necessarily in the best interest of the project, but that are seen to be innovations. Funders are often dragged along by that,” noted another person.

The conversation most often touched on the unfulfilled potential of having a working ecosystem and a common infrastructure for health data as well as the problems and challenges that will most probably arise when trying to develop these.

“There are so many uncoordinated pilot projects in different districts, all doing different things,” said one person. “Governments are doing what they can, but they don’t have the funds,” added another, “and that’s why there are so many small pilots happening everywhere.” One company noted that it had started developing a platform for SMS but abandoned it in favor of working with an existing platform instead. “Can we create standards and protocols to tie some of this work together? There isn’t a common infrastructure that we can build on,” was the complaint. “We seem to always start from scratch. I hope donors and organizations get smart about applying pressure in the right areas. We need an infrastructure that allows us to build on it and do the work!” On the other hand, someone warned of the risks of pushing everyone to “jump on a mediocre software or platform just because we are told to by a large agency or donor.”

The benefits of collaboration and partnership are apparent: increased access to important information, more cooperation, less duplication, the ability to build on existing knowledge, and so on. However, though desirable, partnerships and interoperability is not easy to establish. “Is it too early for meaningful partnerships in mobile health? I was wondering if I could say that…” said one person. “I’m not even sure I’m actually comfortable saying it…. But if you’re providing essential basic services, collecting sensitive medical data from patients, there should be some kind of infrastructure apart from private sector services, shouldn’t there?” The question is who should own this type of a mediator platform: governments? MNOs?

Beyond this, there are several issues related to control and ownership. Who would own the data? Is there a way to get to a point where the data would be owned by the patients and demonetized? If the common system is run by the private sector, there should be protections surrounding the patients’ sensitive information. Perhaps this should be a government-run system. Should it be open source?

Open source has its own challenges. “Well… yes. We’ve practiced ‘hopensource’,” said one person (to widespread chuckles).

Another explained that the way we’ve designed information systems has held back shifts in health systems. “When we’re comparing notes and how we are designing products, we need to be out ahead of the health systems and financing shifts. We need to focus on people-centered care. We need to gather information about a person over time and place. About the teams who are caring for them. Many governments we’re working with are powerless and moneyless. But even small organizations can do something. When we show up and treat a government as a systems owner that is responsible to deliver health care to their citizens, then we start to think about them as a partner, and they begin to think about how they could support their health systems.”

One potential model is to design a platform or system such that it can eventually be handed off to a government. This, of course, isn’t a simple idea in execution. Governments can be limited by their internal expertise. The personnel that a government has at the time of the handoff won’t necessarily be there years or months later. So while the handoff itself may be successful in the short term, there’s no firm guarantee that the system will be continually operational in the future. Additionally, governments may not be equipped with the knowledge to make the best decisions about software systems they purchase. Governments’ negotiating capacity must be expanded if they are to successfully run an interoperable system. “But if we can bring in a snazzy system that’s already interoperable, it may be more successful,” said one person.

Having a common data infrastructure is crucial. However, we must also spend some time thinking about what the data itself should look like. Can it be standardized? How can we ensure that it is legible to anyone with access to it?

These are only some of the relevant political issues, and at a more material level, one cannot ignore the technical challenges of maintaining a national scale system. For example, “just getting a successful outbound dialing rate is hard!” said one person. “If you are running servers in Nigeria it just won’t always be up! I think human centered design is important. But there is also a huge problem simply with making these things work at scale. The hardcore technical challenges are real. We can help governments to filter through some of the potential options. Like, can a system demonstrate that it can really operate at massive scale?” Another person highlighted that “it’s often non-profits who are helping to strengthen the capacity of governments to make better decisions. They don’t have money for large-scale systems and often don’t know how to judge what’s good or to be a strong negotiator. They are really in a bind.”

This is not to mention that “the computers have plastic over them half the time. Electricity, computers, literacy, there are all these issues. And the TelCo infrastructure! We have layers of capacity gaps to address,” said one person.

There are also donors to consider. They may come into a project with unrealistic expectations of what is normal and what can be accomplished. There is a delicate balance to be struck between inspiring the donors to take up the project and managing expectations so that they are not disappointed.” One strategy is to “start hopeful and steadily temper expectations.” This is true also with other kinds of partnerships. “Building trust with organizations so that when things do go bad, you can try to manage it is crucial. Often it seems like you don’t want to be too real in the first conversation. I think, ‘if I lay this on them at the start it can be too real and feel overwhelming.…'” Others recommended setting expectations about how everyone together is performing. “It’s more like, ‘together we are going to be looking at this, and we’ll be seeing together how we are going to work and perform together.”

Creating an interoperable data system is costly and time-consuming, oftentimes more so than donors and other stakeholders imagine, but there are real benefits. Any step in the direction of interoperability must deal with challenges like those considered in this discussion. Problems abound. Solutions will be harder to come by, but not impossible.

So, what would practitioners like to see? “I would like to see one country that provides an incredible case study showing what good partnership and collaboration looks like with different partners working at different levels and having a massive impact and improved outcomes. Maybe in Uganda,” said one person. “I hope we see more of us rally around supporting and helping governments to be the system owners. We could focus on a metric or shared cause – I hope in the near future we have a view into the equity measure and not just the vast numbers. I’d love to see us use health equity as the rallying point,” added another. From a different angle, one person felt that “from a for-profit, we could see it differently. We could take on a country, a clinic or something as our own project. What if we could sponsor a government’s health care system?”

A participant summed the Salon up nicely: “I’d like to make a flip-side comment. I want to express gratitude to all the folks here as discussants. This is one of the most unforgiving and difficult environments to work in. It’ SO difficult. You have to be an organization super hero. We’re among peers and feel it as normal to talk about challenges, but you’re really all contributing so much!”

Salons are run under Chatham House Rule so not attribution has been made in this post. If you’d like to attend a future Salon discussion, join the list at Technology Salon.

 

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Our latest Technology Salon, at the African Evaluation Association (AfrEA) Conference in Uganda on March 29th, focused on how mobile and social media platforms are being used in monitoring and evaluation processes. Our lead discussants were Jamie Arkin from Human Network International (soon to be merging with VotoMobile) who spoke about interactive voice response (IVR); John Njovu, an independent consultant working with the Ministry of National Development Planning of the Zambian government, who shared experiences with technology tools for citizen feedback to monitor budgets and support transparency and accountability; and Noel Verrinder from Genesis who talked about using WhatsApp in a youth financial education program.

Using IVR for surveys

Jamie shared how HNI deploys IVR surveys to obtain information about different initiatives or interventions from a wide public or to understand the public’s beliefs about a particular topic. These surveys come in three formats: random dialing of telephone numbers until someone picks up; asking people to call in, for example, on a radio show; or using an existing list of phone numbers. “If there is an 80% phone penetration or higher, it is equal to a normal household level survey,” she said. The organization has list of thousands of phone numbers and can segment these to create a sample. “IVR really amplifies people’s voices. We record in local language. We can ask whether the respondent is a man or a woman. People use their keypads to reply or we can record their voices providing an open response to the question.” The voice responses are later digitized into text for analysis. In order to avoid too many free voice responses, the HNI system can cut the recording off after 30 seconds or limit voice responses to the first 100 calls. Often keypad responses are most effective as people are not used to leaving voice mails.

IVR is useful in areas where there is low literacy. “In Rwanda, 80% of women cannot read a full sentence, so SMS is not a silver bullet,” Jamie noted. “Smartphones are coming, and people want them, but 95% of people in Uganda have a simple feature phone, so we cannot reach them by Facebook or WhatsApp. If you are going with those tools, you will only reach the wealthiest 5% of the population.”

In order to reduce response bias, the survey question order can be randomized. Response rates tend to be ten times higher on IVR than on SMS surveys, Jamie said, in part, because IVR is cheaper for respondents. The HNI system can provide auto-analysis for certain categories such as most popular response. CSV files can also be exported for further analysis. Additionally, the system tracks length of session, language, time of day and other meta data about the survey exercise.

Regulatory and privacy implications in most countries are unclear about IVR, and currently there are few legal restrictions against calling people for surveys. “There are opt-outs for SMS but not for IVRs, if you don’t want to participate you just hang up.” In some case, however, like Rwanda, there are certain numbers that are on “do not disturb” lists and these need to be avoided, she said.

Citizen-led budget monitoring through Facebook

John shared results of a program where citizens were encouraged to visit government infrastructure projects to track whether budget allocations had been properly done. Citizens would visit a health center or a school to inquire about these projects and then fill out a form on Facebook to share their findings. A first issue with the project was that voters were interested in availability and quality of service delivery, not in budget spending. “”I might ask what money you got, did you buy what you said, was it delivered and is it here. Yes. Fine. But the bigger question is: Are you using it? The clinic is supposed to have 1 doctor, 3 nurses and 3 lab technicians. Are they all there? Yes. But are they doing their jobs? How are they treating patients?”

Quantity and budget spend were being captured but quality of service was not addressed, which was problematic. Another challenge with the program was that people did not have a good sense of what the dollar can buy, thus it was difficult for them to assess whether budget had been spent. Additionally, in Zambia, it is not customary for citizens to question elected officials. The idea that the government owes the people something, or that citizens can walk into a government office to ask questions about budget is not a traditional one. “So people were not confident in asking question or pushing government for a response.”

The addition of technology to the program did not resolve any of these underlying issues, and on top of this, there was an apparent mismatch with the idea of using mobile phones to conduct feedback. “In Zambia it was said that everyone has a phone, so that’s why we thought we’d put in mobiles. But the thing is that the number of SIMs doesn’t equal the number of phone owners. The modern woman may have a good phone or two, but as you go down to people in the compound they don’t have even basic types of phones. In rural areas it’s even worse,” said John, “so this assumption was incorrect.” When the program began running in Zambia, there was surprise that no one was reporting. It was then realized that the actual mobile ownership statistics were not so clear.

Additionally, in Zambia only 11% of women can read a full sentence, and so there are massive literacy issues. And language is also an issue. In this case, it was assumed that Zambians all speak English, but often English is quite limited among rural populations. “You have accountability language that is related to budget tracking and people don’t understand it. Unless you are really out there working directly with people you will miss all of this.”

As a result of the evaluation of the program, the Government of Zambia is rethinking ways to assess the quality of services rather than the quantity of items delivered according to budget.

Gathering qualitative input through WhatsApp 

Genesis’ approach to incorporating WhatsApp into their monitoring and evaluation was more emergent. “We didn’t plan for it, it just happened,” said Noel Verrinder. Genesis was running a program to support technical and vocational training colleges in peri-urban and rural areas in the Northwest part of South Africa. The young people in the program are “impoverished in our context, but they have smartphones, WhatsApp and Facebook.”

Genesis had set up a WhatsApp account to communicate about program logistics, but it morphed into a space for the trainers to provide other kinds of information and respond to questions. “We started to see patterns and we could track how engaged the different youth were based on how often they engaged on WhatsApp.” In addition to the content, it was possible to gain insights into which of the participants were more engage based on their time and responses on WhatsApp.

Genesis had asked the youth to create diaries about their experiences, and eventually asked them to photograph their diaries and submit them by WhatsApp, given that it made for much easier logistics as compared to driving around to various neighborhoods to track down the diaries. “We could just ask them to provide us with all of their feedback by WhatsApp, actually, and dispense with the diaries at some point,” noted Noel.

In future, Genesis plans to incorporate WhatsApp into its monitoring efforts in a more formal way and to consider some of the privacy and consent aspects of using the application for M&E. One challenge with using WhatsApp is that the type of language used in texting is short and less expressive, so the organization will have to figure out how to understand emoticons. Additionally, it will need to ask for consent from program participants so that WhatsApp engagement can be ethically used for M&E purposes.

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Our Tech Salon on Thursday March 9th focused on the potential of Microwork to support youth economic empowerment. Joining us as lead discussants were Lis Meyers, Banyan Global; Saul Miller, Samasource; and Elena Matsui, The Rockefeller Foundation. Banyan Global recently completed a report on “The Nexus of Microwork and Impact Sourcing: Implications for Youth Employment,” supported by the Global Center for Youth Employment and RTI, who also sponsored this Salon. (Disclosure: I worked on the report with the team at Banyan)

Definitions: To frame the discussion, we provided some core definitions and an explanation of the premise of microwork and its role within Impact sourcing.

  • Business Process Outsourcing (BPO): the practice of reducing business costs by transferring portions of work to outside suppliers rather than completing it internally.
  • Online Outsourcing: Contracting a third-party provider (often in a different country) to supply products or services that are delivered and paid for via the Internet. The third party is normally an individual (e-lancing), an online community(crowdsourcing) or a firm.
  • Microwork: a segment of online outsourcing where projects or complex tasks are broken into simple tasks that can be completed in seconds or minutes. Workers require numeracy and understanding of internet and computer technology, and advanced literacy, and are usually paid small amounts of money for each completed task.
  • Impact sourcing: (also known as socially responsible outsourcing), is a business practice in which companies outsource to suppliers that employ individuals from the lowest economic segments of the population.

The premise: It is believed that if microwork is done within an impact sourcing framework, it has the potential to create jobs for disadvantaged youth and disconnected, vulnerable populations and to provide them with income opportunities to support themselves and their families. Proponents of microwork believe it can equip workers with skills and experience that can enable them to enhance their employability regardless of gender, age, socio-economic status, previous levels of employment, or physical ability. Microwork is not always intentionally aimed at vulnerable populations, however. It is only when impact sourcing is adopted as the business strategy that microwork directly benefits the most disadvantaged.

The ecosystem: The microwork industry includes a variety of stakeholders, including: clients (looking to outsource work), service providers (who facilitate the outsourcing by liaising with these clients, breaking tasks down into micro tasks, employing and managing micro workers, and providing overall management and quality control), workers (individual freelancers, groups of people, direct employees, or contractors working through a service provider on assigned micro tasks), donors/investors, government, and communities.

Models of Microwork: The report identifies three main models for microwork (as shown below); micro-distribution (e.g., Amazon Mechanical Turk or CrowdFlower); the direct model (e.g., Digital Divide Data or iMerit) and the indirect model (e.g., Samasource or Rural Shores).

 

Implementer Case Study. With the framework settled, we moved over to hearing from our first discussant, from Samasource, who provided the “implementer” point of view. Samasource has been operating since 2008. Their goal is to connect marginalized women and/or youth with dignified work through the Internet. The organization sees itself as an intermediary or a bridge and believes that work offers the best solution to the complex problem of poverty. The organization works through 3 key programs: SamaSchools, Microwork and SamaHub. At the Samaschool, potential micro workers are trained on the end-to-end process.

The organization puts potential micro workers through an assessment process (former employment history, level of education, context) to predict and select which of the potential workers will offer the highest impact. Most of Samasources’ workers were underemployed or unemployed before coming to Samasource. At Samaschool they learn digital literacy, soft skills, and the technical skills that will enable them to succeed on the job and build their resumes. Research indicates that after 4 years with Samasource, these workers show a 4-fold increase in income.

The organization has evolved over the past couple of years to opening its own delivery center in Nairobi with 650 agents (micro workers). They will also launch in Mumbai, as they’ve learned that hands-on delivery center. Samasource considers that their model (as opposed to the micro-distribution model) offers more control over recruitment and training, quality control, worker preparation, and feedback loops to help workers improve their own performance. This model also offers workers wrap-around programs and benefits like full-time employment with financial literacy training, mentorship, pensions and healthcare.

In closing, it was highlighted that Impact measurement has been a top priority for Samaource. The organization was recently audited with 8 out of 9 stars in terms of quality of impact, evidence and M&E systems. Pending is an RCT that will aim to address the counterfactual (what would happen if Samasource was not operating here?). The organization is experiencing substantial growth, doubling its revenue last year and projecting to grow another 50%. The organization achieved financial sustainability for the first time in the last quarter of 2016. Growth in the industries that require data processing and cleaning and the expansion of AI has driven this growth.

Questions on sustainability. One participant asked why the organization took 8 years to become sustainable. Samasource explained that they had been heavily subsidized by donors, and part of the journey has been to reduce subsidies and increase paid clients. A challenge is keeping costs down and competing with other service providers while still offering workers dignified work. As one of our other discussants noted, this is a point of contention with some local service providers who are less well-known to donors. Because they are not heavily subsidized, they have not been able to focus as much on the “impact” part.

For Digital Divide Data (DDD), who was also present at the Salon, the goal was not quickly getting to profit. Rather the initial objective was social. Now that the organization is maturing it has begun thinking more about profitability and sustainability. It remains a non-profit organization however.

Retention and scale. Both Samasource and DDD noted that workers are staying with them for longer periods of time (up to 4 years). This works well for individual employees (who then have stable work with benefits). It also works well for clients, because employees learn the work, meaning it will be of higher quality – and because the BPO industry has a lot of turnover, and if micro workers are stable it benefits the BPO. This, however, is less useful for achieving scale, because workers don’t move through the program quickly, opening up space for new recruits. For Samasource, the goal would be for workers to move on within 2 years. At DDD, workers complete university while working for DDD, so 4 years is the norm. Some stay for 6 years, which also impacts scaling potential. DDD is looking at a new option for workers to be credentialed and certified, potentially through a 6 month or 1-year program.

The client perspective. One perspective highlighted in the Banyan report is the client perspective. Some loved microwork and impact sourcing. Others said it was challenging. Many are interested in partnering with microwork service providers like iMerit and Daiprom because it offers more data security (you can sign an NDA with service provider, whereas you can’t with individual workers who are coming in through micro-distribution and crowdsourcing). Working with a service provider also means that you have an entity that is responsible for quality control. Experiences with service providers have varied, however, and some companies had signed on to jobs that they were unprepared to train workers on and this resulted in missed deadlines and poor quality work. Clients were clear that their top priority was business – they cared first about quality, cost, and timeliness. “Impact was the cherry on top,” as one discussant noted.

The worker perspective. An aspect missing from the study and the research is that of worker experiences. (As Banyan noted, this would require additional resources for a proper in-depth study). Do workers really seek career growth? Or are they simply looking for something flexible that can help them generate some income in a pinch or supplement their incomes during hard times. In Venezuela, for example, the number of micro workers on CrowdFlower has jumped astronomically during the current political and economic crisis, demonstrating that these type of platforms may serve as supplemental income for those in the most desperate situations. What is the difference in what different workers need?

One small study of micro workers in Kenya noted that when trying to work on their own through the micro-distribution model, they had major challenges: they were not able to collect electronic payments; they got shut out of the system because there were several youth using the same IP address and it was flagged as fraud; language and time zones affected the work was available to them; some companies only wanted workers from certain countries whom they trusted or felt could align culturally; and young women were wary of scams and sexual harassment if accessing work online, as this was their experience with work offline. Some participants wondered what the career path was for a micro worker. Did they go back to school? Did they move ahead to a higher level, higher paying job? Samasource and DDD have some evidence that micro workers in their programs do go on to more dignified, higher paying, more formal jobs, however much of this is due to the wraparound programming that they offer.

The role of government was questioned by Salon participants. Is there a perfect blend of private sector, government and an impact sourcing intermediary? Should government be using micro workers and purposefully thinking about impact sourcing? Could government help to scale microwork and impact sourcing? To date the role of government has been small, noted one discussant. Others wondered if there would be touch points through existing government employment or vocational programs, but it was pointed out that most of the current micro workers are those that have already fallen through the cracks on education and vocational training programming.

A participant outlined her previous experiences with a local municipality in India that wanted to create local employment. The contracting process excluded impact sourcing providers for inexplicable reasons. There were restrictions such as having been in operation for at least 3 years, having a certain minimal level of turnover, number of employees in the system, etc. “So while the government talked about work that needed to be digitized and wanted rural employees, and we went on a three year journey with them to make it inclusive of impact sourcers, it didn’t really work.”

What about social safeguards? One Salon participant raised concerns about the social services and legal protections in place for micro workers. In the absence of regulations, are these issues being swept under the carpet, she wondered. Another noted that minimum standards would be a positive development, but that this will be a long process, as currently there is not even a standard definition of impact sourcing, and it’s unclear what is meant by ‘impact’ and how it’s measured.

This is one area where government could and should play a role. In the past, for example, government has pushed procurement from women-owned or minority owned businesses. Something similar could happen with impact sourcing, but we need standards in order for it to happen. Not all clients who use micro workers are doing it within a framework of impact sourcing and social impact goals. For example, some clients said they were doing “impact sourcing” simply because they were sourcing work from a developing country. In reality, they were simply working with a normal BPO, and so the risk of “impact washing” is real.

Perhaps, noted another participant, the focus should be on drumming up quality clients who actually want to have an impact. “A mandated standard will mean that you lose the private sector.” Some suggested that there would be some type of a ‘certified organic’ or ‘good housekeeping’ seal of approval from a respected entity. Some felt that business were not interested and government would never move something like this. Others disagreed, saying that some large corporation really wanted to be perceived as ethical players.

Definitions proved a major challenge – for example at what point does an ‘impact worker’ cease being an impact worker and how do you count them? Should someone be labeled for life as an impact worker? There was disagreement in the room on this point.

A race to the bottom? Some wondered if microwork was just the same re-hashing of the ‘gig economy’ debate. Would it drive down prices and create extremely unstable work for the most disadvantaged populations? Were there ways that workers could organize if they were working via the micro-distribution model and didn’t even know where to find each other, and if the system was set up to make them bid against each other. It was noted that there was one platform that had been identified that aimed to support workers on Amazon Mechanical Turk, that workers there helped each other with tips on how to get contracts. However as with Uber and other gig economy players, it appeared that all the costs for learning and training were then being pawned off onto the workers themselves.

Working through the direct or indirect models can help to protect individual workers in this aspect, as Samasource, for example, does offer workers contracts and benefits and has a termination policy. The organization is also in a position to negotiate contracts that may be more beneficial to workers, such as extending a 3-week contract with lots of workers over a longer period of time with fewer workers so that income is steadier. Additionally, evaluations have shown that these jobs are pulling in workers who have never had formal jobs before, and that there is an increase in income over time for Samasource workers.

What can donors do? Our third discussant noted that the research is mixed in terms of how different kinds of microwork without any intermediary or wraparound services can actually build a career pathway. Some who are active in the space are still working hard to identify the right partnerships and build support for impact sourcing. It has been difficult to find a “best of breed” or a “gold standard” to date as the work is still evolving. “We’re interested in learning from others what partners need from donors to help scale the work that is effective.” It’s been difficult to evaluate, as she noted, because there has been quite a lot of secrecy involved, as often people do not want to share what is working for fear of losing the competitive edge.

What does the future hold? One Salon participant felt that something very bold was required, given how rapidly economies and technologies are changing. Some of the current microwork will be automated in the near future, he said. The window is closing quickly. Others disagreed, saying that the change in technology was opening up new growth in the sector and that some major players were even delaying their projections because of these rapid shifts and changes in robotics and automation. The BPO sector is fickle and moves quickly – for example voice has shifted rapidly from India to The Philippines. Samasource felt that human components were still required to supplement and train AI and DDD noted that their workers are actually training machines to take over their current jobs. It was also noted that most of the current micro workers are digital natives and a career in data entry is not highly enticing. “We need to find something that helps them feel connected to the global economy. We need to keep focused on relevant skills. The data stuff has a timestamp and it’s on its way out.” DDD is working with universities to bring in courses that are focused on some of the new and emerging skills sets that will be needed.

Conclusions. In short, there are plenty of critical questions remaining in the area of microwork, impact sourcing and around the broader question of the future of youth employment at the global level. How to stay abreast of the rapid changes in economy, business, and technology? What skill sets are needed? A recent article in India’s Business Standard notes constant efforts at re-skilling IT workers. These question are facing not only ‘developing countries’ but the US is also in a similar crisis. Will online work with no wraparound services be a stopgap solution? Will holistic models be pushed so that young people develop additional life skills that will help them in the longer term? Will we learn how to measure and understand the ‘impact’ in ‘impact sourcing?’ Much remains to explore and test!

Thanks to the Global Center for Youth Employment and RTI for supporting this Salon, to our lead discussants and participants, and to ThoughtWorks for hosting us! If you’d like to join us for a future Technology Salon, sign up here!

 

 

 

 

 

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This post was written with input from Maliha Khan, Independent Consultant; Emily Tomkys, Oxfam GB; Siobhan Green, Sonjara and Zara Rahman, The Engine Room.

A friend reminded me earlier this month at the MERL Tech Conference that a few years ago when we brought up the need for greater attention to privacy, security and ethics when using ICTs and digital data in humanitarian and development contexts, people pointed us to Tor, encryption and specialized apps. “No, no, that’s not what we mean!” we kept saying. “This is bigger. It needs to be holistic. It’s not just more tools and tech.”

So, even if as a sector we are still struggling to understand and address all the different elements of what’s now referred to as “Responsible Data” (thanks to the great work of the Engine Room and key partners), at least we’ve come a long way towards framing and defining the areas we need to tackle. We understand the increasing urgency of the issue that the volume of data in the world is increasing exponentially and the data in our sector is becoming more and more digitalized.

This year’s MERL Tech included several sessions on Responsible Data, including Responsible Data Policies, the Human Element of the Data Cycle, The Changing Nature of Informed Consent, Remote Monitoring in Fragile Environments and plenary talks that mentioned ethics, privacy and consent as integral pieces of any MERL Tech effort.

The session on Responsible Data Policies was a space to share with participants why, how, and what policies some organizations have put in place in an attempt to be more responsible. The presenters spoke about the different elements and processes their organizations have followed, and the reasoning behind the creation of these policies. They spoke about early results from the policies, though it is still early days when it comes to implementing them.

What do we mean by Responsible Data?

Responsible data is about more than just privacy or encryption. It’s a wider concept that includes attention to the data cycle at every step, and puts the rights of people reflected in the data first:

  • Clear planning and purposeful collection and use of data with the aim of improving humanitarian and development approaches and results for those we work with and for
  • Responsible treatment of the data and respectful and ethical engagement with people we collect data from, including privacy and security of data and careful attention to consent processes and/or duty of care
  • Clarity on data sharing – what data, from whom and with whom and under what circumstances and conditions
  • Attention to transparency and accountability efforts in all directions (upwards, downwards and horizontally)
  • Responsible maintenance, retention or destruction of data.

Existing documentation and areas to explore

There is a huge bucket of concepts, frameworks, laws and policies that already exist in various other sectors and that can be used, adapted and built on to develop responsible approaches to data in development and humanitarian work. Some of these are in conflict with one another, however, and those conflicts need to be worked out or at least recognized if we are to move forward as a sector and/or in our own organizations.

Some areas to explore when developing a Responsible Data policy include:

  • An organization’s existing policies and practices (IT and equipment; downloading; storing of official information; confidentiality; monitoring, evaluation and research; data collection and storage for program administration, finance and audit purposes; consent and storage for digital images and communications; social media policies).
  • Local and global laws that relate to collection, storage, use and destruction of data, such as: Freedom of information acts (FOIA); consumer protection laws; data storage and transfer regulations; laws related to data collection from minors; privacy regulations such as the latest from the EU.
  • Donor grant requirements related to data privacy and open data, such as USAID’s Chapter 579 or International Aid Transparency Initiative (IATI) stipulations.

Experiences with Responsible Data Policies

At the MERL Tech Responsible Data Policy session, organizers and participants shared their experiences. The first step for everyone developing a policy was establishing wide agreement and buy-in for why their organizations should care about Responsible Data. This was done by developing Values and Principles that form the foundation for policies and guidance.

Oxfam’s Responsible Data policy has a focus on rights, since Oxfam is a rights-based organization. The organization’s existing values made it clear that ethical use and treatment of data was something the organization must consider to hold true to its ethos. It took around six months to get all of the global affiliates to agree on the Responsible Program Data policy, a quick turnaround compared to other globally agreed documents because all the global executive directors recognized that this policy was critical. A core point for Oxfam was the belief that digital identities and access will become increasingly important for inclusion in the future, and so the organization did not want to stand in the way of people being counted and heard. However, it wanted to be sure that this was done in a way that balanced and took privacy and security into consideration.

The policy is a short document that is now in the process of operationalization in all the countries where Oxfam works. Because many of Oxfam’s affiliate headquarters reside in the European Union, it needs to consider the new EU regulations on data, which are extremely strict, for example, providing everyone with an option for withdrawing consent. This poses a challenge for development agencies who normally do not have the type of detailed databases on ‘beneficiaries’ as they do on private donors. Shifting thinking about ‘beneficiaries’ and treating them more as clients may be in order as one result of these new regulations. As Oxfam moves into implementation, challenges continue to arise. For example, data protection in Yemen is different than data protection in Haiti. Knowing all the national level laws and frameworks and mapping these out alongside donor requirements and internal policies is extremely complicated, and providing guidance to country staff is difficult given that each country has different laws.

Girl Effect’s policy has a focus on privacy, security and safety of adolescent girls, who are the core constituency of the organization. The policy became clearly necessary because although the organization had a strong girl safeguarding policy and practice, the effect of digital data had not previously been considered, and the number of programs that involve digital tools and data is increasing. The Girl Effect policy currently has four core chapters: privacy and security during design of a tool, service or platform; content considerations; partner vetting; and MEAL considerations. Girl Effect looks at not only the privacy and security elements, but also aims to spur thinking about potential risks and unintended consequences for girls who access and use digital tools, platforms and content. One core goal is to stimulate implementers to think through a series of questions that help them to identify risks. Another is to establish accountability for decisions around digital data.

The policy has been in process of implementation with one team for a year and will be updated and adapted as the organization learns. It has proven to have good uptake so far from team members and partners, and has become core to how the teams and the wider organization think about digital programming. Cost and time for implementation increase with the incorporation of stricter policies, however, and it is challenging to find a good balance between privacy and security, the ability to safely collect and use data to adapt and improve tools and platforms, and user friendliness/ease of use.

Catholic Relief Services has an existing set of eight organizational principles: Sacredness and Dignity of the human person; Rights and responsibilities; Social Nature of Humanity; The Common Good; Subsidiarity; Solidarity; Option for the Poor; Stewardship. It was a natural fit to see how these values that are already embedded in the organization could extend to the idea of Responsible Data. Data is an extension of the human person, therefore it should be afforded the same respect as the individual. The principle of ‘common good’ easily extends to responsible data sharing. The notion of subsidiarity says that decision-making should happen as close as possible to the place where the impact of the decision will be the strongest, and this is nicely linked with the idea of sharing data back with communities where CRS works and engaging them in decision-making. The option for the poor urges CRS to place a preferential value on privacy, security and safety of the data of the poor over the data demands of other entities.

The organization is at the initial phase of creating its Responsible Data Policy. The process includes the development of the values and principles, two country learning visits to understand the practices of country programs and their concerns about data, development of the policy, and a set of guidelines to support staff in following the policy.

USAID recently embarked on its process of developing practical Responsible Data guidance to pair with its efforts in the area of open data. (See ADS 579). More information will be available soon on this initiative.

Where are we now?

Though several organizations are moving towards the development of policies and guidelines, it was clear from the session that uncertainties are the order of the day, as Responsible Data is an ethical question, often relying on tradeoffs and decisions that are not hard and fast. Policies and guidelines generally aim to help implementers ask the right questions, sort through a range of possibilities and weigh potential risks and benefits.

Another critical aspect that was raised at the MERL Tech session was the financial and staff resources that can be required to be responsible about data. On the other hand, for those organizations receiving funds from the European Union or residing in the EU or the UK (where despite Brexit, organizations will likely need to comply with EU Privacy Regulations), the new regulations mean that NOT being responsible about data may result in hefty fines and potential legal action.

Going from policy to implementation is a challenge that involves both capacity strengthening in this new area as well as behavior change and a better understanding of emerging concepts and multiple legal frameworks. The nuances by country, organization and donor make the process difficult to get a handle on.

Because staff and management are already overburdened, the trick to developing and implementing Responsible Data Policies and Practice will be finding ways to strengthen staff capacity and to provide guidance in ways that do not feel overwhelmingly complex. Though each situation will be different, finding ongoing ways to share resources and experiences so that we can advance as a sector will be one key step for moving forward.

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Over the past 4 years I’ve had the opportunity to look more closely at the role of ICTs in Monitoring and Evaluation practice (and the privilege of working with Michael Bamberger and Nancy MacPherson in this area). When we started out, we wanted to better understand how evaluators were using ICTs in general, how organizations were using ICTs internally for monitoring, and what was happening overall in the space. A few years into that work we published the Emerging Opportunities paper that aimed to be somewhat of a landscape document or base report upon which to build additional explorations.

As a result of this work, in late April I had the pleasure of talking with the OECD-DAC Evaluation Network about the use of ICTs in Evaluation. I drew from a new paper on The Role of New ICTs in Equity-Focused Evaluation: Opportunities and Challenges that Michael, Veronica Olazabal and I developed for the Evaluation Journal. The core points of the talk are below.

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In the past two decades there have been 3 main explosions that impact on M&E: a device explosion (mobiles, tablets, laptops, sensors, dashboards, satellite maps, Internet of Things, etc.); a social media explosion (digital photos, online ratings, blogs, Twitter, Facebook, discussion forums, What’sApp groups, co-creation and collaboration platforms, and more); and a data explosion (big data, real-time data, data science and analytics moving into the field of development, capacity to process huge data sets, etc.). This new ecosystem is something that M&E practitioners should be tapping into and understanding.

In addition to these ‘explosions,’ there’s been a growing emphasis on documentation of the use of ICTs in Evaluation alongside a greater thirst for understanding how, when, where and why to use ICTs for M&E. We’ve held / attended large gatherings on ICTs and Monitoring, Evaluation, Research and Learning (MERL Tech). And in the past year or two, it seems the development and humanitarian fields can’t stop talking about the potential of “data” – small data, big data, inclusive data, real-time data for the SDGs, etc. and the possible roles for ICT in collecting, analyzing, visualizing, and sharing that data.

The field has advanced in many ways. But as the tools and approaches develop and shift, so do our understandings of the challenges. Concern around more data and “open data” and the inherent privacy risks have caught up with the enthusiasm about the possibilities of new technologies in this space. Likewise, there is more in-depth discussion about methodological challenges, bias and unintended consequences when new ICT tools are used in Evaluation.

Why should evaluators care about ICT?

There are 2 core reasons that evaluators should care about ICTs. Reason number one is practical. ICTs help address real world challenges in M&E: insufficient time, insufficient resources and poor quality data. And let’s be honest – ICTs are not going away, and evaluators need to accept that reality at a practical level as well.

Reason number two is both professional and personal. If evaluators want to stay abreast of their field, they need to be aware of ICTs. If they want to improve evaluation practice and influence better development, they need to know if, where, how and why ICTs may (or may not) be of use. Evaluation commissioners need to have the skills and capacities to know which new ICT-enabled approaches are appropriate for the type of evaluation they are soliciting and whether the methods being proposed are going to lead to quality evaluations and useful learnings. One trick to using ICTs in M&E is understanding who has access to what tools, devices and platforms already, and what kind of information or data is needed to answer what kinds of questions or to communicate which kinds of information. There is quite a science to this and one size does not fit all. Evaluators, because of their critical thinking skills and social science backgrounds, are very well placed to take a more critical view of the role of ICTs in Evaluation and in the worlds of aid and development overall and help temper expectations with reality.

Though ICTs are being used along all phases of the program cycle (research/diagnosis and consultation, design and planning, implementation and monitoring, evaluation, reporting/sharing/learning) there is plenty of hype in this space.

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There is certainly a place for ICTs in M&E, if introduced with caution and clear analysis about where, when and why they are appropriate and useful, and evaluators are well-placed to take a lead in identifying and trailing what ICTs can offer to evaluation. If they don’t, others are going to do it for them!

Promising areas

There are four key areas (I’ll save the nuance for another time…) where I see a lot of promise for ICTs in Evaluation:

1. Data collection. Here I’d divide it into 3 kinds of data collection and note that the latter two normally also provide ‘real time’ data:

  • Structured data gathering – where enumerators or evaluators go out with mobile devices to collect specific types of data (whether quantitative or qualitative).
  • Decentralized data gathering – where the focus is on self-reporting or ‘feedback’ from program participants or research subjects.
  • Data ‘harvesting’ – where data is gathered from existing online sources like social media sites, What’sApp groups, etc.
  • Real-time data – which aims to provide data in a much shorter time frame, normally as monitoring, but these data sets may be useful for evaluators as well.

2. New and mixed methods. These are areas that Michael Bamberger has been looking at quite closely. New ICT tools and data sources can contribute to more traditional methods. But triangulation still matters.

  • Improving construct validity – enabling a greater number of data sources at various levels that can contribute to better understanding of multi-dimensional indicators (for example, looking at changes in the volume of withdrawals from ATMs, records of electronic purchases of agricultural inputs, satellite images showing lorries traveling to and from markets, and the frequency of Tweets that contain the words hunger or sickness).
  • Evaluating complex development programs – tracking complex and non-linear causal paths and implementation processes by combining multiple data sources and types (for example, participant feedback plus structured qualitative and quantitative data, big data sets/records, census data, social media trends and input from remote sensors).
  • Mixed methods approaches and triangulation – using traditional and new data sources (for example, using real-time data visualization to provide clues on where additional focus group discussions might need to be done to better understand the situation or improve data interpretation).
  • Capturing wide-scale behavior change – using social media data harvesting and sentiment analysis to better understand wide-spread, wide-scale changes in perceptions, attitudes, stated behaviors and analyzing changes in these.
  • Combining big data and real-time data – these emerging approaches may become valuable for identifying potential problems and emergencies that need further exploration using traditional M&E approaches.

3. Data Analysis and Visualization. This is an area that is less advanced than the data collection area – often it seems we’re collecting more and more data but still not really using it! Some interesting things here include:

  • Big data and data science approaches – there’s a growing body of work exploring how to use predictive analytics to help define what programs might work best in which contexts and with which kinds of people — (how this connects to evaluation is still being worked out, and there are lots of ethical aspects to think about here too — most of us don’t like the idea of predictive policing, and in some ways you could end up in a situation that is not quite what was aimed at.) With big data, you’ll often have a hypothesis and you’ll go looking for patterns in huge data sets. Whereas with evaluation you normally have particular questions and you design a methodology to answer them — it’s interesting to think about how these two approaches are going to combine.
  • Data Dashboards – these are becoming very popular as people try to work out how to do a better job of using the data that is coming into their organizations for decision making. There are some efforts at pulling data from community level all the way up to UN representatives, for example, the global level consultations that were done for the SDGs or using “near real-time data” to share with board members. Other efforts are more focused on providing frontline managers with tools to better tweak their programs during implementation.
  • Meta-evaluation – some organizations are working on ways to better draw conclusions from what we are learning from evaluation around the world and to better visualize these conclusions to inform investments and decision-making.

4. Equity-focused Evaluation. As digital devices and tools become more widespread, there is hope that they can enable greater inclusion and broader voice and participation in the development process. There are still huge gaps however — in some parts of the world 23% less women have access to mobile phones — and when you talk about Internet access the gap is much much bigger. But there are cases where greater participation in evaluation processes is being sought through mobile. When this is balanced with other methods to ensure that we’re not excluding the very poorest or those without access to a mobile phone, it can help to broaden out the pool of voices we are hearing from. Some examples are:

  • Equity-focused evaluation / participatory evaluation methods – some evaluators are seeking to incorporate more real-time (or near real-time) feedback loops where participants provide direct feedback via SMS or voice recordings.
  • Using mobile to directly access participants through mobile-based surveys.
  • Enhancing data visualization for returning results back to the community and supporting community participation in data interpretation and decision-making.

Challenges

Alongside all the potential, of course there are also challenges. I’d divide these into 3 main areas:

1. Operational/institutional

Some of the biggest challenges to improving the use of ICTs in evaluation are institutional or related to institutional change processes. In focus groups I’ve done with different evaluators in different regions, this was emphasized as a huge issue. Specifically:

  • Potentially heavy up-front investment costs, training efforts, and/or maintenance costs if adopting/designing a new system at wide scale.
  • Tech or tool-driven M&E processes – often these are also donor driven. This happens because tech is perceived as cheaper, easier, at scale, objective. It also happens because people and management are under a lot of pressure to “be innovative.” Sometimes this ends up leading to an over-reliance on digital data and remote data collection and time spent developing tools and looking at data sets on a laptop rather than spending time ‘on the ground’ to observe and engage with local organizations and populations.
  • Little attention to institutional change processes, organizational readiness, and the capacity needed to incorporate new ICT tools, platforms, systems and processes.
  • Bureaucracy levels may mean that decisions happen far from the ground, and there is little capacity to make quick decisions, even if real-time data is available or the data and analysis are provided frequently to decision-makers sitting at a headquarters or to local staff who do not have decision-making power in their own hands and must wait on orders from on high to adapt or change their program approaches and methods.
  • Swinging too far towards digital due to a lack of awareness that digital most often needs to be combined with human. Digital technology always works better when combined with human interventions (such as visits to prepare folks for using the technology, making sure that gatekeepers; e.g., a husband or mother-in-law is on-board in the case of women). A main message from the World Bank 2016 World Development Report “Digital Dividends” is that digital technology must always be combined with what the Bank calls “analog” (a.k.a. “human”) approaches.

B) Methodological

Some of the areas that Michael and I have been looking at relate to how the introduction of ICTs could address issues of bias, rigor, and validity — yet how, at the same time, ICT-heavy methods may actually just change the nature of those issues or create new issues, as noted below:

  • Selection and sample bias – you may be reaching more people, but you’re still going to be leaving some people out. Who is left out of mobile phone or ICT access/use? Typical respondents are male, educated, urban. How representative are these respondents of all ICT users and of the total target population?
  • Data quality and rigor – you may have an over-reliance on self-reporting via mobile surveys; lack of quality control ‘on the ground’ because it’s all being done remotely; enumerators may game the system if there is no personal supervision; there may be errors and bias in algorithms and logic in big data sets or analysis because of non-representative data or hidden assumptions.
  • Validity challenges – if there is a push to use a specific ICT-enabled evaluation method or tool without it being the right one, the design of the evaluation may not pass the validity challenge.
  • Fallacy of large numbers (in cases of national level self-reporting/surveying) — you may think that because a lot of people said something that it’s more valid, but you might just be reinforcing the viewpoints of a particular group. This has been shown clearly in research by the World Bank on public participation processes that use ICTs.
  • ICTs often favor extractive processes that do not involve local people and local organizations or provide benefit to participants/local agencies — data is gathered and sent ‘up the chain’ rather than shared or analyzed in a participatory way with local people or organizations. Not only is this disempowering, it may impact on data quality if people don’t see any point in providing it as it is not seen to be of any benefit.
  • There’s often a failure to identify unintended consequences or biases arising from use of ICTs in evaluation — What happens when you introduce tablets for data collection? What happens when you collect GPS information on your beneficiaries? What risks might you be introducing or how might people react to you when you are carrying around some kind of device?

C) Ethical and Legal

This is an area that I’m very interested in — especially as some donors have started asking for the raw data sets from any research, studies or evaluations that they are funding, and when these kinds of data sets are ‘opened’ there are all sorts of ramifications. There is quite a lot of heated discussion happening here. I was happy to see that DFID has just conducted a review of ethics in evaluationSome of the core issues include:

  • Changing nature of privacy risks – issues here include privacy and protection of data; changing informed consent needs for digital data/open data; new risks of data leaks; and lack of institutional policies with regard to digital data.
  • Data rights and ownership: Here there are some issues with proprietary data sets, data ownership when there are public-private partnerships, the idea of data philanthropy’ when it’s not clear whose data is being donated, personal data ‘for the public good’, open data/open evaluation/ transparency, poor care taken when vulnerable people provide personally identifiable information; household data sets ending up in the hands of those who might abuse them, the increasing impossibility of data anonymization given that crossing data sets often means that re-identification is easier than imagined.
  • Moving decisions and interpretation of data away from ‘the ground’ and upwards to the head office/the donor.
  • Little funding for trialing/testing the validity of new approaches that use ICTs and documenting what is working/not working/where/why/how to develop good practice for new ICTs in evaluation approaches.

Recommendations: 12 tips for better use of ICTs in M&E

Despite the rapid changes in the field in the 2 years since we first wrote our initial paper on ICTs in M&E, most of our tips for doing it better still hold true.

  1. Start with a high-quality M&E plan (not with the tech).
    • But also learn about the new tech-related possibilities that are out there so that you’re not missing out on something useful!
  2. Ensure design validity.
  3. Determine whether and how new ICTs can add value to your M&E plan.
    • It can be useful to bring in a trusted tech expert in this early phase so that you can find out if what you’re thinking is possible and affordable – but don’t let them talk you into something that’s not right for the evaluation purpose and design.
  4. Select or assemble the right combination of ICT and M&E tools.
    • You may find one off the shelf, or you may need to adapt or build one. This is a really tough decision, which can take a very long time if you’re not careful!
  5. Adapt and test the process with different audiences and stakeholders.
  6. Be aware of different levels of access and inclusion.
  7. Understand motivation to participate, incentivize in careful ways.
    • This includes motivation for both program participants and for organizations where a new tech-enabled tool/process might be resisted.
  8. Review/ensure privacy and protection measures, risk analysis.
  9. Try to identify unintended consequences of using ICTs in the evaluation.
  10. Build in ways for the ICT-enabled evaluation process to strengthen local capacity.
  11. Measure what matters – not what a cool ICT tool allows you to measure.
  12. Use and share the evaluation learnings effectively, including through social media.

 

 

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Photo: Duncan Edwards, IDS.

A 2010 review of impact and effectiveness of transparency and accountability initiatives, conducted by Rosie McGee and John Gaventa of the Institute of Development Studies (IDS), found a prevalence of untested assumptions and weak theories of change in projects, programs and strategies. This week IDS is publishing their latest Bulletin titled “Opening Governance,” which offers a compilation of evidence and contributions focusing specifically on Technology in Transparency and Accountability (Tech for T&A).

It has a good range of articles that delve into critical issues in the Tech for T&A and Open Government spaces; help to clarify concepts and design; explore gender inequity as related to information access; and unpack the ‘dark side’ of digital politics, algorithms and consent.

In the opening article, editors Duncan Edwards and Rosie McGee (both currently working with the IDS team that leads the Making All Voices Count Research, Learning and Evidence component) give a superb in-depth review of the history of Tech for T&A and outline some of the challenges that have stemmed from ambiguous or missing conceptual frameworks and a proliferation of “buzzwords and fuzzwords.”

They unpack the history of and links between concepts of “openness,” “open development,” “open government,” “open data,” “feedback loops,” “transparency,” “accountability,” and “ICT4D (ICT for Development)” and provide some examples of papers and evidence that could help to recalibrate expectations among scholars and practitioners (and amongst donors, governments and policy-making bodies, one hopes).

The editors note that conceptual ambiguity continues to plague the field of Tech for T&A, causing technical problems because it hinders attempts to demonstrate impact; and creating political problems “because it clouds the political and ideological differences between projects as different as open data and open governance.”

The authors hope to stoke debate and promote the existing evidence in order to tone down the buzz. Likewise, they aim to provide greater clarity to the Tech for T&A field by offering concrete conclusions stemming from the evidence that they have reviewed and digested.

Download the Opening Governance report here.

 

 

 

 

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Our December 2015 Technology Salon discussion in NYC focused on approaches to girls’ digital privacy, safety and security. By extension, the discussion included ways to reduce risk for other vulnerable populations. Our lead discussants were Ximena BenaventeGirl Effect Mobile (GEM) and Jonathan McKay, Praekelt Foundation. I also shared a draft Girls’ Digital Privacy, Safety and Security Policy and Toolkit I’ve been working on with both organizations over the past year.

Girls’ digital privacy, safety and security risks

Our first discussant highlighted why it’s important to think specifically about girls and digital security. In part, this is because different factors and vulnerabilities combine, exacerbating girls’ levels of risk. For example, girls living on less than $2 per day likely only have access to basic mobile phones, which are often borrowed from parents or siblings. The organization she works with always starts with deep research on aspects like ownership vs. borrowship and whether girls’ mobile usage is free/unlimited and un-supervised or controlled by gatekeepers such as parents, brothers, or other relatives. This helps to design better tools, services and platforms and to design for safety and security, she said. “Gatekeepers are very restrictive in many cases, but parental oversight is not necessarily a bad thing. We always work with parents and other gatekeepers as well as with girls themselves when we design and test.” When girls are living in more traditional or conservative societies, she said, we also need to think about how content might affect girls both online and offline. For example, “is content sufficiently progressive in terms of girls’ rights, yet safe for girls to read, comment on or discuss with friends and family without severe retaliation?”

Research suggests that girls who are more vulnerable offline (due to poverty or other forms of marginalization), are likely also more vulnerable to certain risks online, so we design with that in mind, she said. “When we started off on this project, our team members were experts in digital, but we had less experience with the safety and privacy aspects when it comes to girls living under $2/day or who were otherwise vulnerable. “Having additional guidance and developing a policy on this aspect has helped immensely – but has also slowed our processes down and sometimes made them more expensive,” she noted. “We had to go back to everything and add additional layers of security to make it as safe as possible for girls. We have also made sure to work very closely with our local partners to be sure that everyone involved in the project is aware of girls’ safety and security.”

Social media sites: Open, Closed, Private, Anonymous?

One issue that came up was safety for children and youth on social media networks. A Salon participant said his organization had thought about developing this type of a network several years back but decided in the end that the security risks outweighed the advantages. Participants discussed whether social media networks can ever be safe. One school of thought is that the more open a platform, the safer it is, as “there is no interaction in private spaces that cannot be constantly monitored or moderated.” Some worry about open sites, however, and set up smaller, closed, private groups that were closely monitored. “We work with victims of violence to share their stories and coping mechanisms, so, for us, private groups are a better option.”

Some suggested that anonymity on a social media site can protect girls and other vulnerable groups, however there is also research showing that Internet anonymity contributes to an increase in activities such as bullying and harassment. Some Salon participants felt that it was better to leverage existing platforms and try to use them safely. Others felt that there are no existing social media platforms that have enough security for girls or other vulnerable groups to use with appropriate levels of risk. “We sometimes recruit participants via existing social media platforms,” said one discussant, “but we move people off of those sites to our own more secure sites as soon as we can.”

Moderation and education on safety

Salon participants working with vulnerable populations said that they moderate their sites very closely and remove comments if users share personal information or use offensive language. “Some project budgets allow us to have a moderator check every 2 hours. For others, we sweep accounts once a day and remove offensive content within 24 hours.” One discussant uses moderation to educate the community. “We always post an explanation about why a comment was removed in order to educate the larger user base about appropriate ways to use the social network,” he said.

Close moderation becomes difficult and costly, however, as the user base grows and a platform scales. This means individual comments cannot be screened and pre-approved, because that would take too long and defeat the purpose of an engaging platform. “We need to acknowledge the very real tension between building a successful and engaging community and maintaining privacy and security,” said one Salon participant. “The more you lock it down and the more secure it is, the harder you find it is to create a real and active community.”

Another participant noted that they use their safe, closed youth platform to educate and reinforce messaging about what is safe and positive use of social media in hopes that young people will practice safe behaviors when they use other platforms. “We know that education and awareness raising can only go so far, however,” she said, “and we are not blind to that fact.” She expressed concern about risk for youth who speak out about political issues, because more and more governments are passing laws that punish critics and censor information. The organization, however, does not want to encourage youth to stop voicing opinions or participating politically.

Data breaches and project close-out

One Salon participant asked if organizations had examples of actual data breaches, and how they had handled them. Though no one shared examples, it was recommended that every organization have a contingency plan in place for accidental data leaks or a data breach or data hack. “You need to assume that you will get hacked,” said one person, “and develop your systems with that as a given.”

In addition to the day-to-day security issues, we need to think about project close-out, said one person. “Most development interventions are funded for a short, specific period of time. When a project finishes, you get a report, you do your M&E, and you move on. However, the data lives on, and the effects of the data live on. We really need to think more about budgeting for proper project wind-down and ensure that we are accountable beyond the lifetime of a project.”

Data security, anonymization, consent

Another question was related to using and keeping girls’ (and others’) data safe. “Consent to collect and use data on a website or via a mobile platform can be tricky, especially if we don’t know how to explain what we might do with the data,” said one Salon participant. Others suggested it would be better not to collect any data at all. “Why do we even need to collect this data? Who is it for?” he asked. Others countered that this data is often the only way to understand what people are doing on the site, to make adjustments and to measure impact.

One scenario was shared where several partner organizations discussed opening up a country’s cell phone data records to help contain a massive public health epidemic, but the privacy and security risks were too great, so the idea was scrapped. “Some said we could anonymize the data, but you can never really and truly anonymize data. It would have been useful to have a policy or a rubric that would have guided us in making that decision.”

Policy and Guidelines on Girls Privacy, Security and Safety

Policy guidelines related to aspects such as responsible data for NGOs, data security, privacy and other aspects of digital security in general do exist. (Here are some that we compiled along with some other resources). Most IT departments also have strict guidelines when it comes to donor data (in the case of credit card and account information, for example). This does not always cross over to program-level ICT or M&E efforts that involve the populations that NGOs are serving through their programming.

General awareness around digital security is increasing, in part due to recent major corporate data hacks (e.g., Target, Sony) and the Edward Snowden revelations from a few years back, but much more needs to be done to educate NGO staff and management on the type of privacy and security measures that need to be taken to protect the data and mitigate risk for those who participate in their programs.  There is an argument that NGOs should have specific digital privacy, safety and security policies that are tailored to their programming and that specifically focus on the types of digital risks that girls, women, children or other vulnerable people face when they are involved in humanitarian or development programs.

One such policy (focusing on vulnerable girls) and toolkit (its accompanying principles and values, guidelines, checklists and a risk matrix template); was shared at the Salon. (Disclosure: – This policy toolkit is one that I am working on. It should be ready to share in early 2016). The policy and toolkit take program implementers through a series of issues and questions to help them assess potential risks and tradeoffs in a particular context, and to document decisions and improve accountability. The toolkit covers:

  1. data privacy and security –using approaches like Privacy by Design, setting limits on the data that is collected, achieving meaningful consent.
  2. platform content and design –ensuring that content produced for girls or that girls produce or volunteer is not putting girls at risk.
  3. partnerships –vetting and managing partners who may be providing online/offline services or who may partner on an initiative and want access to data, monetizing of girls’ data.
  4. monitoring, evaluation, research and learning (MERL) – how will program implementers gather and store digital data when they are collecting it directly or through third parties for organizational MERL purposes.

Privacy, Security and Safety Implications

Our final discussant spoke about the implications of implementing the above-mentioned girls’ privacy, safety and security policy. He started out saying that the policy starts off with a manifesto: We will not compromise a girl in any way, nor will we opt for solutions that cut corners in terms of cost, process or time at the expense of her safety. “I love having this as part of our project manifesto, he said. “It’s really inspiring! On the flip side, however, it makes everything I do more difficult, time consuming and expensive!”

To demonstrate some of the trade-offs and decisions required when working with vulnerable girls, he gave examples of how the current project (implemented with girls’ privacy and security as a core principle) differed from that of a commercial social media platform and advertising campaign he had previously worked on (where the main concern was the reputation of the corporation, not that of the users of the platform and the potential risks they might put themselves in by using the platform).

Moderation

On the private sector platform, said the discussant, “we didn’t have the option of pre-moderating comments because of the budget and because we had 800 thousand users. To meet the campaign goals, it was more important for users to be engaged than to ensure content was safe. We focused on removing pornographic photos within 24 hours, using algorithms based on how much skin tone was in the photo.” In the fields of marketing and social media, it’s a fairly well-known issue that heavy-handed moderation kills platform engagement. “The more we educated and informed users about comment moderation, or removed comments, the deader the community became. The more draconian the moderation, the lower the engagement.”

The discussant had also worked on a platform for youth to discuss and learn about sexual health and practices, where he said that users responded angrily to moderators and comments that restricted their participation. “We did expose our participants to certain dangers, but we also knew that social digital platforms are more successful when they provide their users with sense of ownership and control. So we identified users that exhibited desirable behaviors and created a different tier of users who could take ownership (super users) to police and flag comments as inappropriate or temporarily banned users.” This allowed a 25% decrease in moderation. The organization discovered, however, that they had to be careful about how much power these super users had. “They ended up creating certain factions on the platform, and we then had to develop safeguards and additional mechanisms by which we moderated our super users!”

Direct Messages among users

In the private sector project example, engagement was measured by the number of direct or private messages sent between platform users. In the current scenario, however, said the discussant, “we have not allowed any direct messages between platform users because of the potential risks to girls of having places on the site that are hidden from moderators. So as you can see, we are removing some of our metrics by disallowing features because of risk. These activities are all things that would make the platform more engaging but there is a big fear that they could put girls at risk.”

Adopting a privacy, security, and safety policy

One discussant highlighted the importance of having privacy, safety and security policies before a project or program begins. “If you start thinking about it later on, you may have to go back and rebuild things from scratch because your security holes are in the design….” The way a database is set up to capture user data can make it difficult to query in the future or for users to have any control of what information is or is not being shared about them. “If you don’t set up the database with security and privacy in mind from the beginning, it might be impossible to make the platform safe for girls without starting from scratch all over again,” he said.

He also cautioned that when making more secure choices from the start, platform and tool development generally takes longer and costs more. It can be harder to budget because designers may not have experience with costing and developing the more secure options.

“A valuable lesson is that you have to make sure that what you’re trying to do in the first place is worth it if it’s going to be that expensive. It is worth a girls’ while to use a platform if she first has to wade through a 5-page terms and conditions on a small mobile phone screen? Are those terms and conditions even relevant to her personally or within her local context? Every click you ask a user to make will reduce their interest in reaching the platform. And if we don’t imagine that a girl will want to click through 5 screens of terms and conditions, the whole effort might not be worth it.” Clearly, aspects such as terms and conditions and consent processes need to be designed specifically to fit new contexts and new kinds of users.

Making responsible tradeoffs

The Girls Privacy, Security and Safety policy and toolkit shared at the Salon includes a risk matrix where project implementers rank the intensity and probability of risks as high, medium and low. Based on how a situation, feature or other potential aspect is ranked and the possibility to mitigate serious risks, decisions are made to proceed or not. There will always be areas with a certain level of risk to the user. The key is in making decisions and trade-offs that balance the level of risk with the potential benefits or rewards of the tool, service, or platform. The toolkit can also help project designers to imagine potential unintended consequences and mitigate risk related to them. The policy also offers a way to systematically and pro-actively consider potential risks, decide how to handle them, and document decisions so that organizations and project implementers are accountable to girls, peers and partners, and organizational leadership.

“We’ve started to change how we talk about user data in our organization,” said one discussant. “We have stopped thinking about it as something WE create and own, but more as something GIRLS own. Banks don’t own people’s money – they borrow it for a short time. We are trying to think about data that way in the conversations we’re having about data, funding, business models, proposals and partnerships. You don’t get to own your users’ data, we’re not going to share de-anonymized data with you. We’re seeing legislative data in some of the countries we work that are going that way also, so it’s good to be thinking about this now and getting prepared”

Take a look at our list of resources on the topic and add anything we may have missed!

 

Thanks to our friends at ThoughtWorks for hosting this Salon! If you’d like to join discussions like this one, sign up at Technology SalonSalons are held under Chatham House Rule, therefore no attribution has been made in this post.

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