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Archive for the ‘wait… what?’ Category

If you’ve been reading this blog regularly, you’ll know that I have a strong connection with El Salvador where I lived during the decade of the 1990s. Every so often I get nostalgic or something triggers me and I get the urge to write about those days or how they still impact on me and my kids. The Central American child migration situation is in the news every day now, with varying explanations and huge amounts of political manipulation, so it’s something that’s been on my mind a lot lately.

I migrated to El Salvador for love in 1991 and back into the US with my kids in 2001 to get out of a country that was increasingly sinking into terrifying violence and where I could not envision a future for myself or my kids. The very week we left El Salvador, the 9-year-old son of a man who owned a small mechanic shop (eg, not someone who was uber wealthy) was kidnapped and then killed by his captors when the police attempted to rescue him. My son Daniel was also 9 at the time.

Still, leaving El Salvador was the hardest decision I’ve ever made — and I had a plane ticket, family support in the US, spoke the language, had a job, and already had US citizenship, as did my kids. I cannot imagine sending my children on their own, by foot. I cannot imagine having to make the choice between the known day-to-day violence of one kind and the potential yet very real violence of another.

My ex-husband made the journey into the US in the early 1980s when he was 18. It took him four months to make it. He tells of hunger, of sleeping outside, of looking for short-term work in Mexico to replace the money that the police had stolen from him, and being chased through the fields by a man with a machete. He traveled with the clothes on his back and not much else. The heartbreak and fear involved in a decision to send a child on that journey alone is something I can’t fathom. But I know that El Salvador is no place to try to raise children right now either. Even in the 1990s, every time I left the house I wondered if I would return that evening or if I might be caught up somehow in the senseless violence that runs wild in the country. It’s something you learn to live with, and you don’t realize how stressful it is until you wake up somewhere where you feel safe.

Our decision to migrate back to the US continues to be difficult sometimes, as I wrote in this post about my daughter’s experiences dealing with family separation. It’s never easy for families to be separated, and it enrages me when the family bonds, of “others” or of “the poor” are imagined to be less strong or less meaningful than those of more privileged people or of the current citizens of a particular country. Sending a child to walk across a desert is not a decision parents make lightly. Why do people seem to understand that when it’s the “Lost Boys of Sudan” and not when it’s children of Central America?

Yesterday, my son Daniel wrote about his experiences for a newspaper called Brasil do Fato, where he’s interning for the next 3 months as part of a human rights grant he received from his university. He doesn’t elaborate about his childhood in El Salvador in this version, but his original version talked about the joy of growing up in the Barrio where we lived, playing in the alley and the rubble of an abandoned building down the road, and how things have changed since then.

Daniel’s piece gives a quick history of the US’ involvement in Central America and why it’s not an isolated issue, free of history and a broader global context. He also reflects on “how much a person’s fate is determined by the country and family into which they are born and where they fall in the order of social forces that structure the world.” It’s something he understands well, because he’s had the best of his two worlds.

Here’s the original article published on July 24, 2014, in Brasil do Fato (in Portuguese), and I’ve pasted in an English translation here:

Human Rights here and in the wider world

by Daniel Ramirez

I am Salvadoran, on my father’s side. Which means that I share, at the very least, a common history and memories of life in a Salvadoran barrio. In the barrio, I grew up alongside many children living in very difficult circumstances, just like the children who are seeking to flee the country today.

Our lives, however, turned out very differently. I am privileged to be a college student at the University of Chicago, and currently in São Paulo working as an intern for Brasil de Fato thanks to a grant from my school’s Human Rights program. This highlights for me how much a person’s fate is determined by the country and family into which they are born and where they fall in the order of social forces that structure the world.

Throughout the 20th century — especially after 1932 when the Salvadoran government put down an attempted peasant insurrection led by the Partido Socialista Centroamericano, killing up to 40,000 indigenous people in a massacre known as “La Matanza” — economic tension between the Salvadoran oligarchy and its working classes continually increased.

This conflict hit a high point during the global economic crisis of the 1970s, and in 1979 an attempted coup d’etat sparked the Salvadoran Civil War. The United States saw this as an opportunity to ensure communism would not take root in El Salvador, as it already had in Nicaragua, and funded the Salvadoran military’s campaign against popular resistance. On the left, the guerrilla militia named Frente Farabundo Martí para la Liberación Nacional (in honor of Farabundo Martí, the leader of the 1932 insurrection) was organized to fight for the Salvadoran people.

It was a brutal war that lasted until 1992. Thousands were killed and human rights were grossly abused on a massive scale. To escape this, many Salvadorans migrated to the United States, including my dad who escaped to the US in the early 1980’s. In 1990, my dad was deported back to El Salvador, and my mom went with him.

I lived in El Salvador until I was nine, then I moved to the United States with my mom and sister.

Since I left, I’ve gone back to visit El Salvador once every couple of years. Now, my old friends have grown up. They work hard for little pay and already have families, and we’ve grown apart. There are still kids hanging out outside, but they’re older, and it seems to me like the character of their activities has become more serious.

The barrio has changed. It now “belongs” to the 18th Street gang. There’s more violence around, some of it between rival gangs, and my dad tells me to be careful who I talk to. The kid who lived directly across from us back in the day was shot and killed along with his mother right in the alley in front of my old house. If I’d been born ten years later, my childhood would not have been the carefree, playful existence that it was.

Violence, Hope and Reality

This is the type of social climate that is causing children to leave for the United States. And if we follow the chain (if not totally causal, then at least telling) from US military funding, to an intensified civil war, to refugee migration, to Los Angeles gangs, to deportation and finally to the pervasive power of gangs throughout El Salvador, Guatemala and Honduras, we can see how much current migration into the US from Central America has been shaped by the United States’ influence.

Right now, on the United States’ side of the US-Mexico border, thousands of children are arriving at immigration detention centers, most looking to escape violent conditions in their home countries. Meanwhile, President Obama is looking for the power to deport them as quickly as possible, intending to send Central Americans the message that the US will not aid immigrants arriving en masse to its borders, even if they are children.

United States foreign policy in Latin America extended and fueled a brutal civil war in El Salvador. Its domestic treatment of immigrants, refugees and low income communities bred gangs who then committed crimes and who then were deported back to a Central American economy and society that had no room or place for them to reintegrate in a healthy manner.

The United States is a major historical cause of the current influx of child immigrants. It would be just for United States society to take collective responsibility for the harm it inflicted in the past, and do what it can to help remedy the crisis in Central America. But, as can be seen by looking at how United States society treats its African-American community, as a country, it is not very good at taking responsibility for past crimes.

Why I’m Here

Now, I’ve come to Brazil with a critical eye in order to understand the interconnections between my Salvadoran barrio, my experiences in the United States, and the periphery and the social movements in Brazil, specifically in São Paulo, where I’ve come to live these three months.

I hope to see how diverse groups of people organize to fight for themselves. My goal is to consistently articulate my insights, and track the progress of my thinking on the theme of human rights. I’m not sure where this project will go, but I’m excited to go along with it and take it wherever it leads.

 

 

 

 

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I spent last week in Berlin at the Open Knowledge Festival – a great place to talk ‘open’ everything and catch up on what is happening in this burgeoning area that crosses through the fields of data, science, education, art, transparency and accountability, governance, development, technology and more.

One session was on Power, politics, inclusion and voice, and it encouraged participants to dig deeper into those 4 aspects of open data and open knowledge. The organizers kicked things off by asking us to get into small groups and talk about power. Our group was assigned the topic of “feeling powerless” and we shared personal experiences of when we had felt powerless. There were several women in my group, many of whom, unsurprisingly, recounted experiences that felt gendered.

Screen Shot 2014-07-22 at 5.24.53 AMThe concept of ‘mansplaining‘ came up. Mansplaining (according to Wikipedia) is a term that describes when a man speaks to a woman with the assumption that she knows less than he does about the topic being discussed because she is female. ‘Mansplaining is different from other forms of condescension because mansplaining is rooted in the assumption that, in general, a man is likely to be more knowledgeable than a woman.’

From there, we got into the tokenism we’d seen in development programs that say they want ‘participation’ but really don’t care to include the viewpoints of the participants. One member of our group talked about the feelings of powerlessness development workers create when they are dismissive of indigenous knowledge and assume they know more than the poor in general. “Like when they go out and explain climate change to people who have been farming their entire lives,” she said.

A lightbulb went off. It’s the same attitude as ‘mansplaining,’ but seen in development workers. It’s #devsplaining.

So I made a hashtag (of course) and tried to come up with a definition.

Devsplaining – when a development worker, academic, or someone who generally has more power within the ‘development industry’ speaks condescendingly to someone with less power. The devsplainer assumes that he/she knows more and has more right to an opinion because of his/her position and power within the industry. Devsplaining is rooted in the assumption that, in general, development workers are likely to be more knowledgeable about the lives and situations of the people who participate in their programs/research than the people themselves are.

What do people think? Any good examples?

 

 

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Screen Shot 2014-06-05 at 7.10.25 AMPlan International’s Finnish office has just published a thorough user-friendly guide to using ICTs in community programs. The guide has been in development for over a year, based on experiences and input from staff working on the ground with communities in Plan programs in several countries.

It was authored and facilitated by Hannah Beardon, who also wrote two other great ICT4D guides for Plan in the past: Mobiles for Development (2009) and ICT Enabled Development (2010).

The guide is written in plain language and comes from the perspective of folks working together with communities to integrate ICTs in a sustainable way.

It’s organized into 8 sections, each covering a stage of project planning, with additional practical ideas and guidance in the annexes at the end.

Chapters include:

1 Assessing the potential of ICTs

2 Assessing the social context for ICTs

3 Assessing the physical context for ICTs

4 Reviewing

5 Choosing the ICT

6 Planning for sustainability

7 Building capacity

8 Monitoring, evaluation and sharing learning

Screen Shot 2014-06-05 at 7.27.32 AMThe sections are not set up as a linear process, and depending on each situation and the status of a project the whole guide can be used, or smaller sections can be pulled out to offer some guidance. Each section includes steps to follow and questions to ask. There are detailed orientations in the annexes as well, for example, how to conduct a participatory communications assessment at the community level, how to map information and communication flows and identify bottlenecks where ICTs might help, how to conduct a feasibility study, how to budget and consider ‘total cost of ownership.’

One thing I especially like about the guide is that it doesn’t push ICTs or particular ‘ICT solutions’ (I really hate that term for some reason!). Rather, it helps people to look at the information and communication needs in a particular situation and to work through a realistic and contextually appropriate process to resolve them, which may or may not involve digital technology. It also assumes that people in communities, district offices and country offices know the context best, and simply offers a framework for pulling that knowledge together and applying it.

Screen Shot 2014-06-05 at 7.07.45 AM99% of my hands-on experience using ICTs in development programming comes from my time at Plan International, much of it spent working alongside and learning from the knowledgeable folks who put this guide together. So I’m really happy to see that now other people can benefit from their expertise as well!

Let @vatamik and @tuuliavirhia know if you have questions, or if you have feedback for them and the team!

Download “A practical guide to using ICTs” here.

 

 

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Last week’s Technology Salon New York City touched on ethics in technology for democracy initiatives. We heard from lead discussants Malavika Jayaram, Berkman Center for Internet and SocietyIvan Sigal, Global Voices; and Amilcar Priestley, Afrolatin@ Project. Though the topic was catalyzed by the Associated Press’ article on ‘Zunzuneo’ (a.k.a. ‘Cuban Twitter’) and subsequent discussions in the press and elsewhere, we aimed to cover some of the wider ethical issues encountered by people and organizations who implement technology for democracy programs.

Salons are off the record spaces, so no attribution is made in this post, but I’ve summarized the discussion points here:

First up: Zunzuneo

The media misinterpreted much of the Zunzuneo story. Zunzuneo was not a secret mission, according to one Salon participant, as it’s not in the remit of USAID to carry out covert operations. The AP article conflated a number of ideas regarding how USAID works and the contracting mechanisms that were involved in this case, he said. USAID and the Office of Transition Initiatives (OTI) frequently disguise members, organizations, and contractors that work for it on the ground for security reasons. (See USAID’s side of the story here). This may still be an ethical question, but it is not technically “spying.” The project was known within the OTI and development community, but on a ‘need to know’ basis. It was not a ‘fly by night’ operation; it was more a ‘quietly and not very effectively run project.’

There were likely ethics breaches in Zunzuneo, from a legal standpoint. It’s not clear whether the data and phone numbers collected from the Cuban public for the project were obtained in a legal or ethical way. Some reports say they were obtained through a mid-level employee (a “Cuban engineer who had gotten the phone list” according to the AP article). (Note: I spoke separately to someone close to the project who told me that user opt-in/opt-out and other standard privacy protocols were in place). It’s also not entirely clear whether, as the AP states, the user information collected was being categorized into segments who were loyal or disloyal to the Cuban government, information which could put users at risk if found out.

Zunzuneo took place in a broader historical and geo-political context. As one person put it, the project followed Secretary Clinton’s speeches on Internet Freedom. There was a rush to bring technology into the geopolitical space, and ‘the articulation of why technology was important collided with a bureaucratic process in USAID and the State Department (the ‘F process’) that absorbed USAID into the State Department and made development part of the State Department’s broader political agenda.’ This agenda had been in the works for quite some time, and was part of a wider strategy of quietly moving into development spaces and combining development, diplomacy, intelligence and military (defense), the so-called 3 D’s.

Implementers failed to think through good design, ethics and community aspects of the work. In a number of projects of this type, the idea was that if you give people technology, they will somehow create bottom up pressure for political social change. As one person noted, ‘in the Middle East, as a counter example, the tech was there to enable and assist people who had spent 8-10 years building networks. The idea that we can drop tech into a space and an uprising will just happen and it will coincidentally push the US geopolitical agenda is a fantasy.’ Often these kinds of programs start with a strategic communications goal that serves a political end of the US Government. They are designed with the idea that a particular input equals some kind of a specific result down the chain. The problem comes when the people doing the seeding of the ideas and inputs are not familiar with the context they will be operating in. They are injecting inputs into a space that they don’t understand. The bigger ethical question is: Why does this thought process prevail in development? Much of that answer is found in US domestic politics and the ways that initiatives get funded.

Zunzuneo was not a big surprise for Afrolatino organizations. According to one discussant, Afrolatino organizations were not surprised when the Zunzuneo article came out, given the geopolitical history and the ongoing presence of the US in Latin America. Zunzuneo was seen as a 21st Century version of what has been happening for decades. Though it was criticized, it was not seen as particularly detrimental. Furthermore, the Afrolatino community (within the wider Latino community) has had a variety of relationships with the US over time – for example, some Afrolatino groups supported the Contras. Many Afrolatino groups have felt that they were not benefiting overall from the mestizo governments who have held power. In addition, much of Latin America’s younger generation is less tainted by the Cold War mentality, and does not see US involvement in the region as necessarily bad. Programs like Zunzuneo come with a lot of money attached, so often wider concerns about their implications are not in the forefront because organizations need to access funding. Central American and Caribbean countries are only just entering into a phase of deeper analysis of digital citizenship, and views and perceptions on privacy are still being developed.

Perceptions of privacy

There are differences in perception when it comes to privacy and these perceptions are contextual. They vary within and across countries and communities based on age, race, gender, economic levels, comfort with digital devices, political perspective and past history. Some older people, for example, are worried about the privacy violation of having their voice or image recorded, because the voice, image and gaze hold spiritual value and power. These angles of privacy need to be considered as we think through what privacy means in different contexts and adapt our discourse accordingly.

Privacy is hard to explain, as one discussant said: ‘There are not enough dead bodies yet, so it’s hard to get people interested. People get mad when the media gets mad, and until an issue hits the media, it may go unnoticed. It’s very hard to conceptualize the potential harm from lack of privacy. There may be a chilling effect but it’s hard to measure. The digital divide comes in as well, and those with less exposure may have trouble understanding devices and technology. They will then have even greater trouble understanding beyond the device to data doubles, disembodied information and de-anonymization, which are about 7 levels removed from what people can immediately see. Caring a lot about privacy can get you labeled as paranoid or a crazy person in many places.’

Fatalism about privacy can also hamper efforts. In the developing world, many feel that everything is corrupt and inept, and that there is no point in worrying about privacy and security. ‘Nothing ever works anyway, so even if the government wanted to spy on us, they’d screw it up,’ is the feeling. This is often the attitude of human rights workers and others who could be at greatest risk from privacy breaches or data collection, such as that which was reportedly happening within Zunzuneo. Especially among populations and practitioners who have less experience with new technologies and data, this can create large-scale risk.

Intent, action, context and consequences

Good intentions with little attention to privacy vs data collection with a hidden political agenda. Where are the lines when data that are collected for a ‘good cause’ (for example, to improve humanitarian response) might be used for a different purpose that puts vulnerable people at risk? What about data that are collected with less altruistic intentions? What about when the two scenarios overlap? Data might be freely given or collected in an emergency that would be considered a privacy violation in a ‘development’ setting, or the data collection may lead to a privacy violation post-emergency. Often, slapping the ‘obviously good and unarguably positive’ label of ‘Internet freedom’ on something implies that it’s unquestionably positive when it may in fact be part of a political agenda with a misleading label. There is a long history of those with power collecting data that helps them understand and/or control those with less power, as one Salon participant noted, and we need to be cognizant of that when we think about data and privacy.

US Government approaches to political development often take an input/output approach, when, in fact, political development is not the same as health development. ‘In political work, there is no clear and clean epidemiological goal we are trying to reach,’ noted a Salon participant. Political development is often contentious and the targets and approaches are very different than those of health. When a health model and rhetoric is used to work on other development issues, it is misleading. The wholesale adoption of these kinds of disease model approaches leaves people and communities out of the decision making process about their own development. Similarly, the rhetoric of strategic communications and its inclusion into the development agenda came about after the War on Terror, and it is also a poor fit for political development. The rhetoric of ‘opening’ and ‘liberating’ data is similar. These arguments may work well for one kind of issue, but they are not transferable to a political agenda. One Salon participant pointed out the rhetoric of the privatization model also, and explained that a profound yet not often considered implication of the privatization of services is that once a service passes over to the private sector, the Freedom of Information Act (FOIA) does not apply, and citizens and human rights organizations lose FOIA as a tool. Examples included the US prison system and the Blackwater case of several years ago.

It can be confusing for implementers to know what to do, what tools to use, what funding to accept and when it is OK to bring in an outside agenda. Salon participants provided a number of examples where they had to make choices and felt ethics could have been compromised. Is it OK to sign people up on Facebook or Gmail during an ICT and education project, given these companies’ marketing and privacy policies? What about working on aid transparency initiatives in places where human rights work or crime reporting can get people killed or individual philanthropists/donors might be kidnapped or extorted? What about a hackathon where the data and solutions are later given to a government’s civilian-military affairs office? What about telling LGBT youth about a social media site that encourages LGBT youth to connect openly with one another (in light of recent harsh legal penalties against homosexuality)? What about employing a user-centered design approach for a project that will eventually be overlaid on top of a larger platform, system or service that does not pass the privacy litmus test? Is it better to contribute to improving healthcare while knowing that your software system might compromise privacy and autonomy because it sits on top of a biometric system, for example? Participants at the Salon face these ethical dilemmas every day, and as one person noted, ‘I wonder if I am just window dressing something that will look and feel holistic and human-centered, but that will be used to justify decisions down the road that are politically negative or go against my values.’ Participants said they normally rely on their own moral compass, but clearly many Salon participants are wrestling with the potential ethical implications of their actions.

What we can do? Recommendations from Salon participants

Work closely with and listen to local partners, who should be driving the process and decisions. There may be a role for an outside perspective, but the outside perspective should not trump the local one. Inculcate and support local communities to build their own tools, narratives, and projects. Let people set their own agendas. Find ways to facilitate long-term development processes around communities rather than being subject to agendas from the outside.

Consider this to be ICT for Discrimination and think in every instance and every design decision about how to dial down discrimination. Data lead to sorting, and data get lumped into clusters. Find ways during the design process to reduce the discrimination that will come from that sorting and clustering process. The ‘Do no harm’ approach is key. Practitioners and designers should also be wary of the automation of development and the potential for automated decisions to be discriminatory.

Call out hypocrisy. Those of us who sit at Salons or attend global meetings hold tremendous privilege and power as compared to most of the rest of the world. ‘It’s not landless farmers or disenfranchised young black youth in Brazil who get to attend global meetings,’ said one Salon attendee. ‘It’s people like us. We need to be cognizant of the advantage we have as holders of power.’ Here in the US, the participant added, we need to be more aware of what private sector US technology companies are doing to take advantage of and maintain their stronghold in the global market and how the US government is working to allow US corporations to benefit disproportionately from the current Internet governance structure.

Use a rights-based approach to data and privacy to help to frame these issues and situations. Disclosure and consent are sometimes considered extraneous, especially in emergency situations. People think ‘this might be the only time I can get into this disaster or conflict zone, so I’m going to Hoover up as much data as possible without worrying about privacy.’ On the other hand, sometimes organizations are paternalistic and make choices for people about their own privacy. Consent and disclosure are not new issues; they are merely manifested in new ways as new technology changes the game and we cannot guarantee anonymity or privacy any more for research subjects. There is also a difference between information a person actively volunteers and information that is passively collected and used without a person’s knowledge. Framing privacy in a human rights context can help place importance on both processes and outcomes that support people’s rights to control their own data and that increase empowerment.

Create a minimum standard for privacy. Though we may not be able to determine a ceiling for privacy, one Salon participant said we should at least consider a floor or a minimum standard. Actors on the ground will always feel that privacy standards are a luxury because they have little know-how and little funding, so creating and working within an ethical standard should be a mandate from donors. The standard could be established as an M&E criterion.

Establish an ethics checklist to decide on funding sources and create policies and processes that help organizations to better understand how a donor or sub-donor would access and/or use data collected as part of a project or program they are funding. This is not always an easy solution, however, especially for cash-strapped local organizations. In India, for example, organizations are legally restricted from receiving certain types of funding based on government concerns that external agencies are trying to bring in Western democracy and Western values. Local organizations have a hard time getting funding for anti-censorship or free speech efforts. As one person at the Salon said, ‘agencies working on the ground are in a bind because they can’t take money from Google because it’s tainted, they can’t take money from the State Department because it’s imperialism and they can’t take money from local donors because there are none.’

Use encryption and other technology solutions. Given the low levels of understanding and awareness of these tools, more needs to be done so that more organizations learn how to use them, and they need to be made simpler, more accessible and user-friendly. ‘Crypto Parties’ can help get organizations familiar with encryption and privacy, but better outreach is needed so that organizations understand the relevance of encryption and feel welcome in tech-heavy environments.

Thanks to participants and lead discussants for the great discussions and to ThoughtWorks for hosting us at their offices!

 If you’d like to attend future Salons, sign up here!

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I attended the African Evaluators’ Conference (AfrEA) in Cameroon last week as part of the Technology and Evaluation strand organized by Pact with financial support from The Rockefeller Foundation’s Evaluation Office and The MasterCard Foundation. The strand was a fantastic opportunity for learning, sharing and understanding more about the context, possibilities and realities of using ICTs in monitoring and evaluation (M&E). We heard from a variety of evaluators, development practitioners, researchers, tool-developers, donors, and private sector and government folks. Judging by the well-attended sessions, there is a huge amount of interest in ICTs and M&E.

Rather than repeat what’s I’ve written in other posts (see links at the bottom), I’ll focus here on some of the more relevant, interesting, and/or new information from the AfrEA discussions. This first post will go into institutional issues and the ‘field’ of ICTs and M&E. A second post will talk about design and operational tips I learned /was reminded of at AfrEA.

1) We tend to get stuck on data collection –Like other areas (I’m looking at you, Open Data) conversations tend to revolve around collecting data. We need to get beyond that and think more about why we are collecting data and what we are going to do with it (and do we really need all this data?). The evaluation field also needs to explore all the other ways it could be using ICTs for M&E, going beyond mobile phones and surveys. Collecting data is clearly a necessary part of M&E, but those data still need to be analyzed. As a participant from a data visualization firm said, there are so many ways you can use ICTs – they help you make sense of things, you can tag sentiment, you can visualize data and make data-based decisions. Others mentioned that ICTs can help us to share data with various stakeholders, improve sampling in RCTs (Randomized Control Trials), conduct quality checks on massive data sets, and manage staff who are working on data collection. Using big data, we can do analyses we never could have imagined before. We can open and share our data, and stop collecting the same data from the same people multiple times. We can use ICTs to share back what we’ve learned with evaluation stakeholders, governments, the public, and donors. The range of uses of ICTs is huge, yet the discussion tends to get stuck on mobile surveys and data collection, and we need to start thinking beyond that.

2) ICTs are changing how programs are implemented and how M&E is done — When a program already uses ICTs, data collection can be built in through the digital device itself (e.g., tracking user behavior, cookies, and via tests and quizzes), as one evaluator working on tech and education programs noted. As more programs integrate digital tools, it may become easier to collect monitoring and evaluation data with less effort. Along those lines, an evaluator looking at a large-scale mobile-based agricultural information system asked about approaches to conducting M&E that do not rely on enumerators and traditional M&E approaches. In his program, because the farmers who signed up for the mobile information service do not live in the same geographical community, traditional M&E approaches do not seem plausible and ICT-based approaches look like a logical answer. There is little documentation within the international development evaluation community, however, on how an evaluator might design an evaluation in this type of a situation. (I am guessing there may be some insights from market research and possibly from the transparency and accountability sectors, and among people working on “feedback loops”).

3) Moving beyond one-off efforts — Some people noted that mobile data gathering is still done mostly at the project level. Efforts tend to be short-term and one-off. The data collected is not well-integrated into management information systems or national level processes. (Here we may reference the infamous map of mHealth pilots in Uganda, and note the possibility of ICT-enabled M&E in other sectors going this same route). Numerous small pilots may be problematic if the goal is to institutionalize mobile data gathering into M&E at the wider level and do a better job of supporting and strengthening large-scale systems.

4) Sometimes ICTs are not the answer, even if you want them to be – One presenter (who considered himself a tech enthusiast) went into careful detail about his organization’s process of deciding not to use tablets for a complex evaluation across 4 countries with multiple indicators. In the end, the evaluation itself was too complex, and the team was not able to find the right tool for the job. The organization looked at simple, mid-range and highly complex applications and tools and after testing them all, opted out. Each possible tool presented a set of challenges that meant the tool was not a vast improvement over paper-based data collection, and the up-front costs and training were too expensive and lengthy to make the switch to digital tools worthwhile. In addition, the team felt that face-to-face dynamics in the community and having access to notes and written observations in the margins of a paper survey would enable them to conduct a better evaluation. Some tablets are beginning to enable more interactivity and better design for surveys, but not yet in a way that made them a viable option for this evaluation. I liked how the organization went through a very thorough and in-depth process to make this decision.

Other colleagues also commented that the tech tools are still not quite ‘there’ yet for M&E. Even top of the line business solutions are generally found to be somewhat clunky. Million dollar models are not relevant for environments that development evaluators are working in; in addition to their high cost, they often have too many features or require too much training. There are some excellent mid-range tools that are designed for the environment, but many lack vital features such as availability in multiple languages. Simple tools that are more easily accessible and understandable without a lot of training are not sophisticated enough to conduct a large-scale data collection exercise. One person I talked with suggested that the private sector will eventually develop appropriate tools, and the not-for-profit sector will then adopt them. She felt that those of us who are interested in ICTs in M&E are slightly ahead of the curve and need to wait a few years until the tools are more widespread and common. Many people attending the Tech and M&E sessions at AfrEA made the point that use of ICTs in M&E would get easier and cheaper as the field develops, tools get more advanced/appropriate/user-friendly and widely tested, and networks/ platforms/ infrastructure improves in less-connected rural areas.

5) Need for documentation, evaluation and training on use of ICTs in M&E – Some evaluators felt that ICTs are only suitable for routine data collection as part of an ongoing program, but not good for large-scale evaluations. Others pointed out that the notions of ‘ICT for M&E’ and ‘mobile data collection/mobile surveys’ are often used interchangeably, and evaluation practitioners need to look at the multiple ways that ICTs can be used in the wider field of M&E. ICTs are not just useful for moving from paper surveys to mobile data gathering. An evaluator working on a number of RCTs mentioned that his group relies on ICTs for improving samples, reducing bias, and automatically checking data quality.

There was general agreement that M&E practitioners need resources, opportunities for more discussion, and capacity strengthening on the multiple ways that ICTs may be able to support M&E. One evaluator noted that civil society organizations have a tendency to rush into things, hit a brick wall, and then cross their arms and say, “well, this doesn’t work” (in this case, ICTs for M&E). With training and capacity, and as more experience and documentation is gained, he considered that ICTs could have a huge role in making M&E more efficient and effective.

One evaluator, however, questioned whether having better, cheaper, higher quality data is actually leading to better decisions and outcomes. Another evaluator asked for more evidence of what works, when, with whom and under what circumstances so that evaluators could make better decisions around use of ICTs in M&E. Some felt that a decision tree or list of considerations or key questions to think through when integrating ICTs into M&E would be helpful for practitioners. In general, it was agreed that ICTs can help overcome some of our old challenges, but that they inevitably bring new challenges. Rather than shy away from using ICTs, we should try to understand these new challenges and find ways to overcome/work around them. Though the mHealth field has done quite a bit of useful research, and documentation on digital data collection is growing, use of ICTs is still relatively unexplored in the wider evaluation space.

6) There is no simple answer. One of my takeaways from all the sessions was that many M&E specialists are carefully considering options, and thinking quite a lot about which ICTs for what, whom, when and where rather than deciding from the start that ICTs are ‘good and beneficial’ or ‘bad and not worth considering.’ This is really encouraging, and to be expected of a thoughtful group like this. I hope to participate in more discussions of this nature that dig into the nuances of introducing ICTs into M&E.

Some new resources and forthcoming documentation may help to further set the stage for better learning and application of ICTs in the M&E process. Pact has just released their Mobile Technology Toolkit, and Michael Bamberger and I are finishing up a paper on ICT-enabled M&E that might help provide a starting point and possible framework to move things forward. The “field” of ICTs in M&E is quite broad, however, and there are many ways to slice the cake. Here is the list of toolkits, blog posts and other links that we compiled for AfrEA – please add any that you think are missing!

(Part 2 of this post)

Previous posts on ICTs and M&E:

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The NYC Technology Salon on February 28th examined the connection between bigger, better data and resilience. We held morning and afternoon Salons due to the high response rate for the topic. Jake Porway, DataKind; Emmanuel Letouzé, Harvard Humanitarian Initiative; and Elizabeth Eagen, Open Society Foundations; were our lead discussants for the morning. Max Shron, Data Strategy; joined Emmanuel and Elizabeth for the afternoon session.

This post summarizes key discussions from both Salons.

What the heck do we mean by ‘big data’?

The first question at the morning salon was: What precisely do we mean by the term ‘big data’? Participants and lead discussants had varying definitions. One way of thinking about big data is that it is comprised of small bits of unintentionally produced ‘data exhaust’ (website cookies, cellphone data records, etc.) that add up to a dataset. In this case, the term big data refers to the quality and nature of the data, and we think of non-sampled data that are messy, noisy and unstructured. The mindset that goes with big data is one of ‘turning mess into meaning.’

Some Salon participants understood big data as datasets that are too large to be stored, managed and analyzed via conventional database technologies or managed on normal computers. One person suggested dropping the adjective ‘big,’ forgetting about the size, and instead considering the impact of the contribution of the data to understanding. For example, if there were absolutely no data on something and 1000 data points were contributed, this might have a greater impact than adding another 10,000 data points to an existing set of 10 million.

The point here was that when the emphasis is on big (understood as size and/or volume), someone with a small data set (for example, one that fits into an excel sheet) might feel inadequate, yet their data contribution may be actually ‘bigger’ than a physically larger data set (aha! it’s not the size of the paintbrush…). There was a suggestion that instead of talking about big data we should talk about smart data.

How can big data support development?

Two frameworks were shared for thinking about big data in development. One from UN Global Pulse considers that big data can improve a) real-time awareness, b) early warning and c) real-time monitoring. Another looks at big data being used for three kinds of analysis: a) descriptive (providing a summary of something that has already happened), b) predictive (likelihood and probability of something occurring in the future), and c) diagnostic (causal inference and understanding of the world).

What’s the link between big data and resilience?

‘Resilience’ as a concept is contested, difficult to measure and complex. In its most simple definition, resilience can be thought of as the ability to bounce back or bounce forward. (For an interesting discussion on whether we should be talking about sustainability or resilience, see this piece). One discussant noted that global processes and structures are not working well for the poor, as evidenced from continuing cycles of poverty and glaring wealth inequalities. In this view, people are poor as a result of being more exposed and vulnerable to shocks, at the same time, their poverty increases their vulnerability, and it’s difficult to escape from the cycle where over time, small and large shocks deplete assets. An assets-based model of resilience would help individuals, families and communities who are hit by a shock in one sphere — financial, human, capital, social, legal and/or political — to draw on the assets within another sphere to bounce back or forward.

Big data could help this type of an assets-based model of resilience by predicting /helping poor and vulnerable people predict when a shock might happen and preparing for it. Big data analytics, if accessible to the poor, could help them to increase their chances of making better decisions now and for the future. Big data then, should be made accessible and available to communities so that they can self-organize and decrease their own exposure to shocks and hazards and increase their ability to bounce back and bounce forward. Big data could also help various actors to develop a better understanding of the human ecosystem and contribute to increasing resilience.

Can ivory tower big data approaches contribute to resilience?

The application of big data approaches to efforts that aim to increase resilience and better understand human ecosystems often comes at things from the wrong angle, according to one discussant. We are increasingly seeing situations where a decision is made at the top by people who know how to crunch data yet have no way of really understanding the meaning of the data in the local context. In these cases, the impact of data on resilience will be low, because resilience can only truly be created and supported at the local level. Instead of large organizations thinking about how they can use data from afar to ‘rescue’ or ‘help’ the poor, organizations should be working together with communities in crisis (or supporting local or nationally based intermediaries to facilitate this process) so that communities can discuss and pull meaning from the data, contextualize it and use it to help themselves. They can also be more informed what data exist about them and more aware of how these data might be used.

For the Human Rights community, for example, the story is about how people successfully use data to advocate for their own rights, and there is less emphasis on large data sets. Rather, the goal is to get data to citizens and communities. It’s to support groups to define and use data locally and to think about what the data can tell them about the advocacy path they could take to achieve a particular goal.

Can data really empower people?

To better understand the opportunities and challenges of big data, we need to unpack questions related to empowerment. Who has the knowledge? The access? Who can use the data? Salon participants emphasized that change doesn’t come by merely having data. Rather it’s about using big data as an advocacy tool to tell the world to change processes and to put things normally left unsaid on the table for discussion and action. It is also about decisions and getting ‘big data’ to the ‘small world,’ e.g., the local level. According to some, this should be the priority of ‘big data for development’ actors over the next 5 years.

Though some participants at the Salon felt that data on their own do not empower individuals; others noted that knowing your credit score or tracking how much you are eating or exercising can indeed be empowering to individuals. In addition, the process of gathering data can help communities understand their own realities better, build their self-esteem and analytical capacities, and contribute to achieving a more level playing field when they are advocating for their rights or for a budget or service. As one Salon participant said, most communities have information but are not perceived to have data unless they collect it using ‘Western’ methods. Having data to support and back information, opinions and demands can serve communities in negotiations with entities that wield more power. (See the book “Who Counts, the power of participatory statistics” on how to work with communities to create ‘data’ from participatory approaches).

On the other hand, data are not enough if there is no political will to make change to respond to the data and to the requests or demands being made based on the data. As one Salon participant said: “giving someone a data set doesn’t change politics.”

Should we all jump on the data bandwagon?

Both discussants and participants made a plea to ‘practice safe statistics!’ Human rights organizations wander in and out of statistics and don’t really understand how it works, said one person. ‘You wouldn’t go to court without a lawyer, so don’t try to use big data unless you can ensure it’s valid and you know how to manage it.’ If organizations plan to work with data, they should have statisticians and/or data scientists on staff or on call as partners and collaborators. Lack of basic statistical literacy is a huge issue amongst the general population and within many organizations, thought leaders, and journalists, and this can be dangerous.

As big data becomes more trendy, the risk of misinterpretation is growing, and we need to place more attention on the responsible use of statistics and data or we may end up harming people by bad decisions. ‘Everyone thinks they are experts who can handle statistics – bias, collection, correlation’ these days. And ‘as a general rule, no matter how many times you say the data show possible correlation not causality, the public will understand that there is causality,’ commented one discussant. And generally, he noted, ‘when people look at data, they believe them as truth because they include numbers, statistics, science.’ Greater statistical literacy could help people to not just read or access data and information but to use them wisely, to understand and question how data are interpreted, and to detect political or other biases. What’s more, organizations today are asking questions about big data that have been on statisticians’ minds for a very long time, so reaching out to those who understand these issues can be useful to avoid repeating mistakes and re-learning lessons that have already been well-documented.

This poor statistical literacy becomes a serious ethical issue when data are used to determine funding or actions that impact on people’s lives, or when they are shared openly, accidentally or in ways that are unethical. In addition, privacy and protection are critical elements in using and working with data about people, especially when the data involve vulnerable populations. Organizations can face legal action and liability suits if their data put people at harm, as one Salon participant noted. ‘An organization could even be accused of manslaughter… and I’m speaking from experience,’ she added.

What can we do to move forward?

Some potential actions for moving forward included:

  • Emphasis with donors that having big data does not mean that in order to cut costs, you should eliminate community level processes related to data collection, interpretation, analysis, and ownership;
  • Evaluations and literature/documentation on the effectiveness of different tools and methods, and when and in which contexts they might be applicable, including things like cost-benefit analyses of using big data and evaluation of its impact on development/on communities when combined with community level processes vs used alone/without community involvement — practitioner gut feelings are that big data without community involvement is irresponsible and ineffective in terms of resilience, and it would be good to have evidence to help validate or disprove this;
  • More and better tools and resources to support data collection, visualization and use and to help organizations with risk analysis, privacy impact assessments, strategies and planning around use of big data; case studies and a place to share and engage with peers, creation of a ‘cook book’ to help organizations understand the ingredients, tools, processes of using data/big data in their work;
  • ‘Normative conventions’ on how big data should be used to avoid falling into tech-driven dystopia;
  • Greater capacity for ‘safe statistics’ among organizations;
  • A community space where frank and open conversations around data/big data can occur in an ongoing way with the right range of people and cross-section of experiences and expertise from business, data, organizations, etc.

In conclusion?

We touched upon all types of data and various levels of data usage for a huge range of purposes at the two Salons. One closing thought was around the importance of having a solid idea of what questions we trying to answer before moving on to collecting data, and then understanding what data collection methods are adequate for our purpose, what ICT tools are right for which data collection and interpretation methods, what will done with the data/what is the purpose of collecting data, how we’ll interpret them, and how data will be shared, with whom, and in what format.

See this growing list of resources related to Data and Resilience here and add yours!

Thanks to participants and lead discussants for the fantastic exchange, and a big thank you to ThoughtWorks for hosting us at their offices for this Salon. Thanks also to Hunter Goldman, Elizabeth Eagen and Emmanuel Letouzé for their support developing this Salon topic, and to Somto Fab-Ukozor for support with notes and the summary. Salons are held under Chatham House Rule, therefore no attribution has been made in this post. If you’d like to attend future Salons, sign up here!

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Screen Shot 2014-03-07 at 3.34.23 AM

As Tom over at Humanosphere wrote a few days ago, there’s a cool initiative happening at Sheffield University that seeks to develop a global research agenda related to the post-2015 sustainable development goals process. (Disclaimer, I’m part of the steering committee.)

ID100: The Hundred Most Important Questions in International Development asks individuals and organizations from across policy, practice and academia to submit questions that address the world’s biggest environmental, political and socioeconomic problems. These will then be shortlisted down to a final set of 100 questions following a debate and voting process with representatives from development organizations and academia who will meet in July 2014. 

The final list of questions will be published as policy report and in a leading academic journal. More on the consultation methodology here. Similar crowdsourced priority-setting exercises have worked in biodiversity conservation, food security and other areas, and they have been instrumental in framing global research priorities for policy development and implementation.

Screen Shot 2014-03-07 at 3.36.06 AMAnyone can submit up to five questions related to key issues in international development that require more exploration. You are encouraged to involve colleagues in the formulation of these questions.

Please submit your questions by March 25th – and check the submission guidelines before formulating questions. More information on the project can be accessed on the ID100 website. Hashtag: #ID100.

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This is a guest post from Jamie Narkunski, who works as a UX consultant at ThoughtWorks NYC.

by Jamie Narkunski

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Photo from ThoughtWorks.

I recently attended a Tech Salon where the subject of grant applications came up.  Part of the conversation revolved around the issue that the complexity, format, and investment required in the traditional grant application process acts as a barrier for organizations that lack the resources or experience needed to complete the process in a competitive manner, leading to the exclusion or weeding out of potential target applicants in some cases.

The conversation made me think of a recent grant I was a part of:  The Digital Prototype Opportunity.  ThoughtWorks partnered with Parsons New School and Blue Ridge Foundation to host a grant for $100k in funds + $350k worth of development work. The grant was split across two winners. The grant application was open to organizations who had an existing social impact innovation but wanted to use technology to extend and/or deepen their impact in their social space.

Because there were organizations of varying sizes and capabilities involved, we wanted to try to level the playing field as best we could without negatively impacting the applicants.  We started the process with an announcement and invitation to come to our offices for a two-hour workshop where we helped the organizations explore their current process flows and the users they serve, and to identify where they could make the most impact with the addition of technology.

The interest came to around 120 individual organizations. After the first workshop we had the organizations submit a short proposal based around the work done in the workshop or work they’d done based on the format of the workshop we had introduced to them.  The proposals we received were, for the most part, to the point and included a direct ask and perceived impact.  The workshop had enabled organizations to understand our interest in the “What” and the “Why” over the “How”.  This allowed applicants to focus their efforts around what they know best:  their users and the needs of those users.  It would be misleading to say that every single proposal we received stuck to this format — there were of course the occasional 20+ page proposal from the organizations with the professional grant writer — but that was the exception.

Photo from ThoughtWorks.

Photo from ThoughtWorks.

Next, we narrowed the group down to ten finalists.  Our promise to the finalists was that even if they were not one of the two winners, they would walk away with a fleshed-out proposal with a clear ask, reasoning to back it up, and an understanding of resources, funds and time needed to complete it.  In order to make good on this promise, we held a second workshop for the finalist groups.  They each got 1:1 assistance, and this time the focus was on framing an MVP and rough scoping the tech, resources and time needed to complete.  From there they had the option to refine their proposal, images and diagrams from the workshop.

We ended up with a clear understanding of what was being asked for, why, and what it would take to pull off.  It made for a difficult evaluation on our end, because there were few applicants we could disqualify for technicalities. For me, that proved the success of the application process.  In the end we ended up with two diverse winners and 8 finalists with very strong proposals.

I would love to see and to personally attempt to repurpose the format we did at a local level on a larger scale.  It will be interesting to see the creative use of partnerships and program management most likely required to grow this model.

If there are any questions or interest in the methodologies and tools used in the workshop I am happy to help.  You can reach me at jnarkuns [at] thoughtworks.com.

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Our February 6th Technology Salon in New York City focused on the organizational challenges that development organizations face when trying to innovate or integrate ICTs into their programs and operations. We looked at the idea of “innovation” and different ways to approach it. We asked what “innovation” really means and why “technology” and “innovation” seem to always be used interchangeably. We shared ideas, challenges and good practice around supporting and encouraging staff, managers, and donors to experiment with new and better ways of doing things.

A huge thank you to Somto Fab-Ukozor and Rachana Kumar for their collaboration on writing the summary below!

Mika

Mika Valitalo, Plan Finland. (Photo by Somto Fab-Ukozor)

Our lead discussants were Jessica Heinzelman, DAI’s senior ICT specialist; Chris Fabian, UNICEF’s advisor to the Executive Director on innovation and co-lead of UNICEF’s innovation lab; and Mika Valitalo, Plan Finland’s program manager for ICT4D.

What is innovation?

Different organizations bring in different ideas and definitions of innovation. Is innovation always synonymous with technology? Does it always require technology? For some organizations, “innovation” means doing things faster, better and differently in a way that adds value and has a concrete impact.

One discussant noted that innovation is not necessarily disruptive in nature; it can be categorized into 3 main forms:

  • a totally new context, new problem, new solution
  •  an existing solution that is improved
  •  an existing solution that is adapted to a new context, country or sector

Another lead discussant pointed out that innovation is not necessarily something brand new; it can be something that existed but that is used in a different way or simply different processes or ways of thinking, and innovation does not have to be technology. The concept of innovation is often misunderstood, he said, because “someone can come up with 10 crappy ideas that are new but that does not make them innovative or useful.” He also cautioned that innovation should not only be about replication and scale, yet donors sometimes decide that an idea is innovative and encourage organizations to replicate the idea, without ensuring that it is having a real or relevant impact across different local contexts.

One discussant disagreed and said that there’s no innovation without technology; for example, 60% of kids are stunting in one of the greenest areas in the world because of lack to electrical grid; the provision of electricity is technology. Without the electrical grid, the country will never reach any of its developmental goals. Technology enables the work to happen. A different viewpoint, as another discussant explained, was that the application of the technology is the innovative part, not the technology itself.

What fuels innovation?

A key part of the Salon discussion focused on whether having dedicated resources fueled innovation, or whether the presence of challenges and constraints forces innovation. Some Salon participants felt that when people are faced with challenges such as less time, fewer resources, no office space, etc., they may find themselves being more innovative in order to overcome constraints. Others found that staff often use the excuse of not having time and resources as a reason for not innovating or thinking outside the box. Some felt that innovation is difficult to achieve within large bureaucratic institutions due to their risk averse cultures, whereas others felt that one of the benefits of large-scale organizations is having resources to innovate and then test and scale innovations. Participants did agree that regardless of the outside setting, some people are more inclined to be innovative – these people are easy to identify almost everywhere, as they are always coming up with new ideas and trying/testing things out. The key is to find a way for organizational structures to support and reward innovators.

Encouraging innovation within large development organizations

Different organizations approach the innovation question in different ways. One discussant said that at his organization, the innovation team spends 60% of its time working on problems the organization is facing at the moment; 20% of its time looking towards the future (a 3-5 year horizon) for ideas that have an immediate direct impact on its work; and 20% of its time on organizational redesign, in other words, how to work with users to create solutions that are not top down and that take advantage of the existing ecosystem. His innovations team is only interested in finding/creating innovations that could reach very large scale, such as 10,000,000 people or more.

The innovation team created some guidelines for staff and allies with tips on how to defend one’s existence as someone working on innovation.  The guide addresses questions like: Why innovation?  Is it valuable to have an innovation unit? If so, why? If so and why, then prove it. Working on these questions led the innovation unit to develop metrics for innovation to justify staff positions focused on innovation. These guidelines can help people at other organizations who are trying something new to have a reference point; they allow innovation teams to say “such-and-such organization is doing this, so we can do it too.”

Metrics for innovation

Having a set of metrics can help innovation labs, teams or persons charged with organizational innovation to measure whether they are actually achieving their goals, too. One organization defined the following metrics:

  • permission to fail or fail cheaply without fear
  • working with heterogeneous groups
  •  sharing knowledge across countries and contexts

Working across organizational boundaries without “soul crushing bureaucracy” and having the real ability to work horizontally is one key to achieving these metrics.

Decentralizing the innovation function

Another lead discussant described the institutional changes and underlying understanding of people needed to improve and support innovation:

  • Identify the real incentives that someone has – individual or project – and the disincentives to innovating. It is important to look underneath the excuses people come up with such as time constraints and additional work, and find out what is driving them.
  • Hire realistic optimists – Sometimes in the ICT4D space, people gloss over the challenges and promote the technology. It is important to hire people who are grounded and have a good analytical sense, and who can think beyond gadgets and hype.
  • Building and sharing expertise within the organization – Creating a champions group of mid-to entry-level professionals within the organization, who understand the power that new technology has, is another way to make innovation and ICT4D spread. Rather than keep the expertise isolated within a specialist unit, finding younger people who are hungry for knowledge and who see this kind of work as a way to help further their career and set themselves apart from their colleagues can help. Then the “innovation team” can provide them with support and guidance. Participatory workshops on new tools and approaches can be organized where these innovation champions are tasked to research and explore something and then present it. Equipped with tools and trainings, they will be able to better identify opportunities for innovation.
  • Getting innovation into the plan early and working with those who are putting proposals and RFPs together to make sure that it is part of the metrics being measured from the beginning. It’s hard to add new elements into the program later because people will perceive it as additional work.

One Salon participant said that her organization disconnected “innovation” from its other programs so that space for trying new things would be made, and the fear of failing would be reduced or “offloaded” to the innovation team. In this case, the unit is funded through private sources which support it to experiment. It still has to struggle for its existence and show the impact and value of either failure or success.

Ideas for taking innovation and ICT4D forward

Some ideas for moving ahead included:

  1. Flexibility in program planning- In reality, most times during program implementation the plan changes and we have to figure out how to cope with it. The solution lies in the ability to quietly promote innovation and to influence donor organizations to embrace more flexible implementation.
  2. Integrating User-Centered-Design – Ethnographic research can help to better understand how people use technology locally and what its meaning is. It also helps identify existing patterns and ways of doing things that could be enhanced or shared with other communities if they are working well. Agile methodology from the software world can be pulled into development programs in order to end the top-down approach of solving problems from afar and having everything cooked up from the start. Rather, focusing on small iterations and the impact of the deliverables can be a better approach.
  3. Collaboration with Universities – Universities can be great places for working on and trying out  new ideas. Links with universities can be used as ways to find solutions, but even moreso to “change the proteins” inside of a traditional organization.  Collaboration among staff and students provides opportunities for staff to learn how to think about things differently and for students to understand real-world challenges in development agencies.
  4. Bridging the gap – Involving educators, health experts, child protection specialists and others who are not very interested in gadgets can bring about strong understanding of the real needs. Then connecting them with “techies” and ICTs in plain language and asking them to relate their own use of tech (they probably all use mobile phones in their personal lives, for example) to the ways that community members use tech can help to bring about solid, practical, sustainable and locally driven solutions.
  5. Provide a safe environment – Many humans are innovative by nature, said one discussant. Hierarchies and organizational processes are often what prevent people from doing new things. Giving feedback and psychological support can help those who are innovative to flourish within a difficult environment.
  6. The interdisciplinary approach – One Salon participant said that his organization had started to work with some senior staff to think and structure data in a way that would help them understand their challenges and programs better in order to innovate. This makes people more comfortable, and working across different teams with a variety of people and skill sets can help new ideas and solutions to bubble up.
  7. Information intermediaries – Infomediaries working at various levels can help connect people with technology, conduct training, and ensure that staff can acquire skills to use the technology themselves and in programs.
  8. Open source – Making project documents, budgets, concepts, “open” online can make them more accessible and  help  enable sustainable projects and prevent issues and costs associated with proprietary tools, applications and content.
  9. Younger management – There’s an age differential between the people who lead most large organizations and large-scale projects and those who are more interested in technology. One participant suggested it would be important to get younger people into positions where they can make contributions of ideas and decisions without being blocked by higher level people that may be “past their innovation prime.” Another solution may be to hire more experienced people but to ensure that they are open to working with  younger people who bring in new ideas. (Some Salon participants, however, felt that age has nothing to do with innovation, and that it is more related to personality types and organizational environments).

For  additional resources on the Salon topic, look here – and add your resources as well.

Salons are held under Chatham House Rule, therefore no attribution has been made in this post. Many thanks to our lead discussants and to ThoughtWorks for hosting and providing breakfast.

If you’d like to attend future Salons, sign up here!

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This is a cross post from Heather Leson, Community Engagement Director at the Open Knowledge Foundation. The original post appeared here on the School of Data site.

by Heather Leson

What is the currency of change? What can coders (consumers) do with IATI data? How can suppliers deliver the data sets? Last week I had the honour of participating in the Open Data for Development Codeathon and the International Aid Transparency Initiative Technical Advisory Group meetings. IATI’s goal is to make information about aid spending easier to access, use, and understand. It was great that these events were back-to-back to push a big picture view.

My big takeaways included similar themes that I have learned on my open source journey:

You can talk about open data [insert tech or OS project] all you want, but if you don’t have an interactive community (including mentorship programmes), an education strategy, engagement/feedback loops plan, translation/localization plan and a process for people to learn how to contribute, then you build a double-edged barrier: barrier to entry and barrier for impact/contributor outputs.

Currency

About the Open Data in Development Codeathon

At the Codathon close, Mark Surman, Executive Director of Mozilla Foundation, gave us a call to action to make the web. Well, in order to create a world of data makers, I think we should run aid and development processes through this mindset. What is the currency of change? I hear many people talking about theory of change and impact, but I’d like to add ‘currency’. This is not only about money, this is about using the best brainpower and best energy sources to solve real world problems in smart ways. I think if we heed Mark’s call to action with a “yes, and”, then we can rethink how we approach complex change. Every single industry is suffering from the same issue: how to deal with the influx of supply and demand in information. We need to change how we approach the problem. Combined events like these give a window into tackling problems in a new format. It is not about the next greatest app, but more about asking: how can we learn from the Webmakers and build with each other in our respective fields and networks?

Ease of Delivery

The IATI community / network is very passionate about moving the ball forward on releasing data. During the sessions, it was clear that the attendees see some gaps and are already working to fill them. The new IATI website is set up to grow with a Community component. The feedback from each of the sessions was distilled by the IATI – TAG and Civil Society Guidance groups to share with the IATI Secretariat.

In the Open Data in Development, Impact of Open Data in Developing Countries, and CSO Guidance sessions, we discussed some key items about sharing, learning, and using IATI data. Farai Matsika, with International HIV/Aids Alliance, was particularly poignant reminding us of IATI’s CSO purpose – we need to share data with those we serve.

Country edits IATI

One of the biggest themes was data ethics. As we rush to ask NGOs and CSOs to release data, what are some of the data pitfalls? Anahi Ayala Iaccuci of Internews and Linda Raftree of Plan International USA both reminded participants that data needs to be anonymized to protect those at risk. Ms. Iaccuci asked that we consider the complex nature of sharing both sides of the open data story – successes and failures. As well, she advised: don’t create trust, but think about who people are trusting. Turning this model around is key to rethinking assumptions. I would add to her point: trust and sharing are currency and will add to the success measures of IATI. If people don’t trust the IATI data, they won’t share and use it.

Anne Crowe of Privacy International frequently asked attendees to consider the ramifications of opening data. It is clear that the IATI TAG does not curate the data that NGOS and CSOs share. Thus it falls on each of these organizations to learn how to be data makers in order to contribute data to IATI. Perhaps organizations need a lead educator and curator to ensure the future success of the IATI process, including quality data.

I think that School of Data and the Partnership for Open Data have a huge part to play with IATI. My colleague Zara Rahman is collecting user feedback for the Open Development Toolkit, and Katelyn Rogers is leading the Open Development mailing list. We collectively want to help people become data makers and consumers to effectively achieve their development goals using open data. This also means also tackling the ongoing questions about data quality and data ethics.


Here are some additional resources shared during the IATI meetings.

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