Citizen election reporting in Kenya: A failure of technology duplication, or a breakthrough in online-offline collaboration?

The Kenyan elections were more than a month ago, but a debate continues in the crisis mapping community about whether the various technologies deployed to track and respond to outbreaks of violence were a confused and possibly dangerous mess, or a successful contribution to what was ultimately a peaceful (if disputed) process.

DO WE REALLY NEED ALL OF THOSE PROJECTS??? Do we really need 3 maps, 7 phone numbers, and several web-forms? Is that really such a crazy bad idea to have one coordinated number/web-form that could then have in the back-end multiple responders and organizations working together? – Anahi Ayala  (ICT Works blog post)

The criticism goes on to describe this duplication as irresponsible and dangerous, especially supposing that the submitted information has no real response mechanism.

While it’s true that having multiple public numbers for submitting information about one election is not ideal, I believe that behind the scenes was a much more encouraging process that has only just begun. Here’s why I think that in the balance, technology was part of the solution, not the problem, during Kenya’s elections:

1) Unprecedented collaboration among technologists, at least at a pilot level.

Map Kibera took part in elections monitoring by mapping and reporting through SMS, blogs and video throughout the election period on our multimedia sites, Voice of Kibera and Voice of Mathare in two slums. Kepha Ngito, our executive director, offers this extensive writeup of how the process looked behind the scenes, definitely worth a read. Map Kibera already had been working with Ushahidi-based websites and video news for three years in Kibera, and with blogging and video in Mathare for about two years; therefore neither project was created specifically for the election. Given our status as an established community-based group focusing on reporting and local information, we were ready to take on this event without creating any new technology.

Example of report from election day on Voice of Kibera

Example of report from election day on Voice of Kibera

As elections neared, more organizations began to set up temporary programming around election reporting. In particular, our team joined events held by Ushahidi around their Uchaguzi platform, and we began to think about how to collaborate: they as a national scope project and ourselves in-depth in two key communities. Ultimately, some members of our team worked throughout the election at the iHub headquarters of Ushahidi to monitor their reports coming in from Kibera and Mathare, and share our more detailed and verified reports with their system. This meant both reports and response could be tightly coordinated.

Would it have made sense to have used only one reporting number, that of Uchaguzi for instance? No, because Uchaguzi is no longer active, while Map Kibera is building up a long term citizen engagement including this SMS number. It made more sense to work on interoperability and coordination.

2) Unprecedented coordination among community-based groups

What was the key to all the information coming in, and the verification process?

At the community level, there was unprecedented coordination among a variety of agencies who normally do not work together. Concerned groups put aside whatever challenges normally keep them operating separately, and pledged support to each other in order to serve the good of the community. This kind of network is a real breakthrough in coordination locally given the challenges that often prevent such teamwork, and it naturally came from desire for security in the slum not any outside impetus. As Kepha writes:

KCODA, Pamoja FM, Map Kibera, Kamukunji Pressure Group, CREAW, the Langata District Peace Committee, Community Policing groups and the office of the District Commissioner joined efforts to create a network called the Kibera Civic Watch Consortium, a body that would respond to and coordinate the community’s efforts to maintain peace and provide interventions where possible. (Kepha Ngito, How slum communities came together to help prevent election violence)

3) Response and verification

It was this background offline coordination that would allow for immediate election-day verification and constant liaising with security groups, both official and community led, in case of any problem. The online-offline coordination often involved both SMS into the system, and phone calls to security or other key people to keep tensions down.

…We stationed our trained citizen reporters in each polling station to be relaying SMS news to our verification team to be verified and approved before being posted on our Voice of Kibera and Voice of Mathare websites.The Map Kibera verification team dealt with every information that came in, calling back and forth to establish the facts and figures about every report sent in. Our video teams rushed to scenes, most of which were not known or easily accessed by the mainstream or foreign press to capture instant news which they edited and uploaded on Youtube. Members also took photos and posted them to our blogs and Facebook group. In this verification process, the team succeeded in dismissing several false alarms, wrong information and propaganda for violence. In addition and in response, security organs and emergency service providers enhanced their presence in these areas highly reducing chances of violence. In one instance, when many reports were sent about youth gathering around in groups in one area of Kibera, after several phone calls with the security organs, the Police Commissioner authorized a chopper to fly around conducting a security check, the crowds soon dispersed and calm returned. (Kepha Ngito, How slum communities came together to help prevent election violence)

I heard a number of claims floating around about technology platforms being directly responsible for police or security response. I would advise that these be investigated closely. In the case of both Kibera and Mathare, if anything it was this type of “online” or SMS-based reporting in conjunction with offline personal and official networks, connected often through ordinary phone calls, which activated response, not a pure technical system.

Bringing together the various kinds of technical reporting options with great local networks can create response processes that are effective, but not overly sensitive to false alarm reports.

4) Good citizen election monitoring is not “pure” crowdsourcing. We and others relied on establishing networks and offline meetings and coordination to build participation.

Another misconception is that every SMS number was targeted for the general public. Actually, the Map Kibera SMS line was and is primarily used by our volunteer reporters to send information from prearranged locations like polling stations. For the election, aside from our members, the Kibera Civic Watch Consortium sent in many reports during the election. The numbers are publicized to general residents, but operate mostly through carefully cultivated users.

I think there is a basic misconception that “crowdsourcing” something like election violence will happen with anonymous individuals. In tight-knit communities, this is simply not the case. They may text into a nationally publicized number, but those reports are not always the ones you want or can rely on. Verification is needed, which means local networks are still key. My hunch is that when people report through a local system the information is more likely to be accurate, because they know the faces behind the tech.

Particularly in more marginalized, insecure, or informal communities, people come together based on relationship networks, and being known and trusted as a leader in the community is an earned privilege that does not come easily nor is it taken lightly. People do not often trust something new that is introduced from “outside”.

National scale projects targeted to single events like elections should heavily support existing community level initiatives, and community-level initiatives around information need to be long-term investments into the community fabric. This means not just new technology projects which are still rare, but also traditional community media or data-driven local planning groups.

5) We’re still working out what works best in the space, so multiple projects are important for narrowing it down. A top-down model won’t work for citizen-based technology in emergencies, at least not for a long while.

While coordination and duplication avoidance is good, we are talking about places where the normal emergency response functions need supplementation and should be supplemented. I don’t know if a single top-down system for emergencies is ever going to work in Kenya, but it certainly hasn’t yet. I’ve seen way too many everyday crises happen with absolutely no response at all save for neighbors helping neighbors (and literally saving each others’ lives on a daily basis). In that sense people need access to options and a variety of ways to draw attention to and publicize an urgent situation. It’s also in the spirit of the technology world to keep trying out new ideas and iterating.

On the other hand, it’s true that some might irresponsibly publicize reporting channels that seem to promise response they can’t deliver, and technology is most certainly something we are now seeing organizations use to make themselves look good even at the expense of the public. We should ask whether there were unnecessary institutional barriers or unethical motivations to any lack of coordination or collaborative spirit, and direct our transparency lens that way. If competition for funding or funder requirements inhibited the social benefit of working together, as it usually does, then these incentive systems should be exposed. Also, the opportunism of pop-up and parachute technology projects just a week or so before the election is a distraction, and there were several of these as well. But what I think we’ve seen here is a partial triumph of civic collectivism over the usual silos created by the donor marketplace, which is why I’m seeing the glass as half-full. It could stand to be filled up all the way.

But here’s the most important trend that gives me hope:

7) A sea-change is underway in terms of how people engage with information in Kenya: they feel it’s their right and responsibility to speak out and to protect peace by countering rumor; and they increasingly feel they have tools with which to do so.

This is my hunch, but since 2009, I believe that the positive side of social media has had an impact in Kenya – or at least in Nairobi. I noticed during the election that people expected to be able to counter incorrect news and information sources by using their Facebook account or Twitter or one of the projects referenced here – they have grown used to reporting themselves and no longer rely exclusively on traditional media sources. When they see something happening, they expect someone local – if not themselves, then a neighbor – to be able to take a photo, send a message, somehow communicate.

This means that rumors can be countered more quickly, and leaves room for peace activists (most Kenyans) to organize and amplify accurate and helpful messages and at least contribute to the conversation, creating a more balanced discussion.

During these elections there was a new sense of the importance and responsibility that citizens have for being information collectors, transmitters, publicizers, verifiers, and the inkling that the standard channels of information aren’t the only ones that exist anymore – and that citizens have the responsibility to not only voice opinions but keep the rumors down, to participate in peace. Real crisis prevention has much more to do with local leadership, coordination, and behind the scenes response than the information that’s necessarily visible online. But that isn’t to say that creating visibility, keeping track of the truth and bringing information out of the dark in close to real time isn’t extremely valuable – it connects and inspires those who want to keep the peace and provides the opportunity for a local counter narrative to the dominant media.

Don’t risk missing the bigger story here: the simple act of residents recording actual ground level events themselves will have a long-term transformative impact on society – nowhere perhaps, as profoundly as in places like informal settlements.

This post originally appeared at Disruptive Witness.

­


On citizen engagement and “feedback loops”

This post also appears on Disruptive Witness.

Citizen feedback on development and aid projects has been a kind of “holy grail” for aid for a few years now. The latest discussion comes in a recent blog post, “Consumer Reports for Aid“, by Dennis Whittle of the Center for Global Development. This is one of my very favorite topics, too. And, I eagerly sought the same kind of thing in 2009 when we began working in the Kibera community.

But here’s why we might be awaiting such feedback loops – in the model of Yelp or Consumer Reports - until the cows come home, dedicated hackathons notwithstanding.

When we tried to activate a citizen feedback loop in Kibera with Map Kibera, we thought that having a communication mechanism for residents to post comments about aid projects on the ground could revolutionize the way not only NGOs practiced, but the way the community viewed and took ownership over development. On Yelp, if I leave feedback, either positive or negative, I feel more connected to the businesses in my community and helping them succeed, fail or improve. In short, I feel a subtle sense of ownership. If the local NGOs and projects in a place like Kibera could be put online and rated by citizens, or various services commented upon in a detailed way, then maybe we’d have some real and meaningful feedback. USAID and big donors would respond to that, not to some puffed up self-reporting.

In fact, when we launched Voice of Kibera, that was one of the first ideas we had about what it might become. It wouldn’t necessarily be the news reporting site we have now; maybe it would allow people to mark services and organizations and comment on them.

It’s clear to me now why that didn’t happen – though, as you’ll see, we’re still working on the broader goal.

1) It’s hard to overestimate the complexity of a neighborhood of some 200,000 citizens, several tribes, a variety of languages, and little government whatsoever, that has existed in spite of the government’s desire to wipe it out and whose often transient residents have to struggle every day to make a living. I’m talking about one place, but I might be referring to many urban informal or extremely poor neighborhoods in the world which are the target of large amounts of aid dollars. There is a way things get done, and a reason why they get done that way – an entrenched system in which both the aid donors, government, and local actors play a role. People are very sensitive to the micropolitics that could impact their lives much more seriously than in wealthier environments. Offending the wrong person, or pleasing the right one is an important determinant of success.

Being in the business of engaging people, soliciting and publicizing their honest and informed views, and getting accurate data out there is a big job, and in my view far too little attention is being focused by techies or donors on the community side of this equation. Ultimately that’s what Map Kibera seeks to do, but it takes a lot more than setting up a web platform.

In this context, the role of a trusted representative is very important – who represents local opinion? Is it just whoever gets on Twitter while their neighbors still don’t have a mobile phone? In our excitement over technology there are always those who figure this out and can then hijack the process. System gaming problem? Not solved.

2) International aid is a mainstay of the Kibera and many other poor communities’ economies. This is what the international aid juggernaut has wrought. Yes, most Kiberans work outside of the aid industry and its various projects, but were you to do a critical analysis of the local economy and jobs, you would find that NGO jobs are the best paid and most stable, and come with a reputation upgrade, while “appreciations” – a soda at the end of a meeting, or a bit of airtime, cash or t-shirts – will be given out to a myriad of community members who attend any sort of event or meeting. Therefore, how do you build loyalty and good ratings on your Development Yelp? By intelligently executing a project that everyone relies upon day to day, that has impact, and legitimate sustainability (meaning the NGO jobs should” be phased out eventually)? Or by winning a popularity contest by fitting the expectations for other perks? It’s a lot easier to do the latter. The incentives and potential rewards for supporting a claim that an NGO is doing great work are very high. Saying something negative can get you in trouble. We’re talking about tight-knit communities here. Why spend time giving critical feedback when it’s potentially going to get you in trouble?

3) In fact, why spend time giving feedback at all? Time and energy are very precious resources when you live in a place where parents are forced to leave small children to play unsupervised all day because they need to work and can’t pay for daycare. You’ll need to distribute some appreciation to get participation, unless participants are using a system for rating large-donor projects they’ve been beneficiaries of (see Danish Refugee Council example below), in which case much of the feedback might be in the form of calling out the continuing need for more assistance.

4) Many might respond that anonymizing this information will solve some of the problems I’ve mentioned. That’s essentially the route that Global Giving went with most of the stories on its Storytelling platform. But in that case, you don’t have very detailed knowledge about specific interventions or programs, which to me is the ultimate goal. Also, in most instances, asking for anonymous information from people is perhaps the purest yet least effective method of crowdsourcing. Anonymous inputs means you cannot hold people accountable for false information, and also removes a key incentive – to have an online presence and visibility. Even with Yelp, that’s clearly a motivator – a little bit of egotism.

So how do you make visible the inherent knowledge in a community of what works and what doesn’t? Certainly every Kibera resident has a lot of valuable knowledge, that, for instance, the vaunted bio-toilet is just stinking up the corner and no one’s using its supposed cooking gas. There is indeed a desire in Kibera, at least, to weed out the unproductive and even fake “briefcase” or “ghost” organizations that are supposed to reside there, but which aren’t in evidence on the ground, which means there is some latent incentive to provide data.

That’s why we hope our teams on the ground at Map Kibera and others like them will become the trusted informational resource for the community and will do a kind of due diligence on the local organizations and projects. In fact, this is a standard role that journalists play in a community – accountability and investigation. New kinds of citizen journalists and information centers can fill this role in places where there is limited news coverage. These informants aren’t anonymous at all – but they are protected by association with a network and local reputation.

In fact, an idea the Map Kibera team had was to create a directory of organizations and projects in the area where each group could have a page explaining what they do. The neutral nature of this project would invite in organizations in order to allow people to know who’s doing what where, and basic transparency would be built in. It would also help those tiny initiatives of regular community members – the orphanages, day cares, and youth groups – without much money or tech savvy to have some visibility and essentially prove their value. Mikel and I worked on this a little bit in a different format with Grassroots Jerusalem at www.grassrootsalquds.net. We are still seeking funding to finish this platform and establish it in Nairobi. Once that’s done, I think we can rely on our dedicated team to fact-check reports and post about various initiatives, and because they’re trusted members of the community, they can retrieve detailed opinions of citizens, both positive and negative and quote them on the site.

There is another way this could all work, which is to create a loop about government and large donor projects (those less likely to have a presence in the community) or simply highlight needs that require attention locally. This is more akin to the FixMyStreet concept, calling out local issues which have no project yet attached in hopes of triggering government or other support. We’ve tried to do this in Tandale, a slum in Dar es Salaam. There, we trained a team of reporters who’ve mapped the area and now post blog reports about conditions in the slum. See http://tandale.ramanitanzania.org/blog/. In this case, the loop has so far failed to close on the government or other responder’s side, in spite of initial promise. Here is where an influential third party can play an important role, such as the World Bank or UN.

I also found interesting this example of the Danish Refugee Council trying to solicit feedback on its work, which might not be a model to copy but gives a pretty accurate picture of what types of complaints a system might field. This is what a loop would often amount to: “We are requesting for power to charge our mobile phones, in order to reduce the challenges about the power and sent more SMS feedback.” Response: “According to your prioritization, DRC doesn’t provide electricity to any community.” Basically, that’s a no. I’m not sure that gets us much further, yet, than fielding such requests for more assistance. But, it does make public a normally very private exchange between donors and beneficiaries, when they are in that traditional relationship common to development schemes. I think this is a step in the right direction, because the more we open up these processes the more likely they will be open for questioning and productive critique.

The fact is that every “complaint” about “service delivery” is actually a citizen claiming a right – clean water, for instance – often in a place where there is no easy solution and there is a systemic and ultimately, political reason why neither NGOs nor government have yet to provide for such needs. Usually, that reason has little to do with the government (or big NGO/World Bank/UN etc) not knowing that the problem exists, sometimes in great detail.

The more that trustworthy community information representatives can detail and report and map and publicize and pressure and comment – and, do real journalism about – about the particular issue, the more likely that some downward accountability will be injected into the system. It’s also more likely that community members will begin to understand the forces at work in their neighborhoods and analyze what’s happening around them. It’s hard to imagine an information asymmetry as critical to address as that between residents of poor communities and major players in the development and government arenas, the 6 foot view vs the 30,000 foot.


Opening Data in Kenya. My Method is to Hack.

A techy cross-post from Brain Off

There’s good reason to join the excitement about Open Data in Kenya. As Tariq says on the World Bank blog

Open data in Kenya is special: it comes at a time of national change; it’s got a head start on tools and expertise from the global open data community and it’s happening in a country where the information ecosystem is still maturing.

I’m proud that our work with Map Kibera has any relation to this at all. And it’s certainly due to the hard work of passionate people, in a tough environment, especially Dr. Bitange Ndemo (if you have the time, Dr. Ndemo’s talk at the World Bank is recommended).

Now that the launch has subsided, and I have a spare moment in the air from Tanzania, I want to look in depth at what data and how data has been released on OpenDataKE, the means of working with the data and collaborating on the data, and how this resource can relate to other open data sets in Kenyan society. Now that the government has made a bold move, I think it’s the responsibility of the software development community and civil society to really step up and test out the data, and suggest how this can become a really vibrant and social resource. Again, Tariq says this succinctly

the call for open data should go hand in hand with a call for better quality data: data that might be collected by official government agencies or in this age, by citizens themselves.

Transect across data

My “method” is to hack. I want to make an interesting simple visualization with some data from OpenDataKE, focusing on Nairobi, using openly available tools. Browsing data sets, the Population Density per Constiuency, derived from the 2009 census, seemed promising. The difference in density across the urban landscape Nairobi is extreme. For a sense of it, just look at the density of features in OpenStreetMap in the map of the slum of Mathare compared to nearby leafy Mathaiga. And to help the hack, the population density data set even has a handy location column.

Or maybe not. The usual practice in tabular data is to split the latitude and longitude into two columns, but here both values are formatted along with the unnecessary name of the province in which the constituency is located. Anyone who has had to work with data is used to little problems like this, and it’s easy enough (for a programmer) to write a quick script to clean this up. So I selected Export to CSV (side note, the other options presented by the platform seem hardly useful), filtered just the constituencies in Nairobi, and cleaned it up just by hand (I was too lazy to script this for just a handful of values).

Gaps and Errors

I uploaded the CSV to GeoCommons, which has facility to deal with many formats of data and easily layer together interactive maps, and was surprised to see that several points weren’t placed in Nairobi at all. Turns out there’s several errors in the location column, at least in Nairobi, and possibly in the rest of the country (I didn’t check). I’d have to correct these by hand. My knowledge of the location and extent of the constituencies is limited, so I needed another source, and that is not something you can find on OpenDataKE. It took some searching until I found scanned maps of contituencies on the Mars Group site. An overview map of all the constituencies was missing, so I used the adjacent constituency names in order to place the mistaken ones.

This worked well, but I’m left with questions. Why isn’t constituency boundary data available on OpenDataKE? How did Mars Group get these maps? And now that I’ve gone to the bother of correcting this data set, how can I contribute the changes back, or at least alert the holders of the data to the errors? There is a nomination section on OpenDataKE, which was wonderfully active until July 9, and then went quiet (did Socrata’s support contract expire then?). Anyway, I’m hopeful these will start getting attention again, so I’ve submitted two requests (pending approval to post), one for constiuency boundaries, and another for a way to correct the location column in the population density data set.

My second surprise was that when I made the annotation size relative to the population density, I didn’t see a big difference among the constituencies. The area where Kibera is located, Langata, is about the same density as Westlands, and both are less than CBD and Eastlands. What’s happening here is that constituencies aren’t aligned to uniform urban settlement patterns. Langata, the home constiuency of the Prime Minister, includes both the slum of Kibera and the wealthy and sparse suburb of Karen. A more useful and telling metric would be population density per Ward, the sub-unit of constituency which does have fairly good alignment to settlement patterns. The census can and has been aggregated to this level, because there was a large promotion of the census count of population in Kibera.

So again I’ve nominated a data set, for the population density aggregated at ward level. And I’ve also made a request for meta-information on the methodology of the census in Kibera and other informal settlements. While the 170,000 figure is surely more close to reality than the wild 1 million figures of the past, by comparing that number with estimates derived from other methods there is a discripency; the others agree on an average closer to 250,000. Additionally, and admittedly anecdotedly, many people in Kibera say they and their neighbors were never counted. Now this happens in any census, and it does not deligitimize the census, but in order to interpret data, openness on the methodology of data collection and analysis is also necessary.

The Civil Society of Data

Open government data exists in a wider ecosystem. Just a few months ago, Columbia University released amazing data sets of Nairobi, including high detail land use under open knowledge licenses. A truly beautiful and informative data set. Another place to find many a Kenyan civil society data set is Virtual Kenya. I thought the population density dataset would be interesting to layer with land use.

This data is distributed as Shapefiles, and I need tiles to use a base map. This is the purpose of MapBox, a rapidly developing tool set to make it easy to build beautiful map tiles. I loaded the Shapefiles in my locally running TileMill, styled the landuse categories based on Columbia’s pdf using carto, assigned interaction, and exported as mbtiles. These were dropbox’d, and posted to TileStream, as this map.

Mouseover or click on the map to get more detail about each parcel. This interaction technique is really interesting (as a geek), it’s entirely javascript and lightweight in the browser; it still has a few rough edges, but overall, a nice experience. There are limits, like TileMill doesn’t work with CSV, or permit multiple interactive layers, but it’s a great work in progress. Thanks to DevSeed for the TileStream account, and Dane Springmeyer, who spent some time with me hacking and bug hunting the interaction features of mapnik.

Like the OpenDataKE data set, and actually all data sets, there are errors … there is no such thing as a perfect map. The Ethiopian Church, across from YaYa, is not indicated nor is its land zoned as “public use” as other church lands in Nairobi are. And the Sarakasi Dome, home of our yoga practice in Nairobi, is not shown a unified plot at all. Now Columbia makes their contact information known on the site, and I’ve met them personally, so feedback here is direct over email, but I wonder from here … what is the method and intention to continually correct, update and discuss these data sets? Does it need to?

Of course, that is the primary approach of OpenStreetMap … geographic data in a wiki, that gets constantly examined, updated, and discussed, completely openly. OpenStreetMap can provide another overlay, so we can have some roads and points of reference for the final map. So on GeoCommons, I configured the tiles from the land use data on TileMill (this required some hidden configuration of the tile scheme), composited over semi-transparent OSM data (provided by GeoCommons through Acetate), and then finally, the population density points. This is the result for now of the data transect.

I hope I can improve this. You’ll see that the OSM streets don’t overlay precisely with land use. This I believe, but haven’t confirmed, to be the result of a project error in the Land Use data set. And an even better representation of the population density would have been a geo-join with area boundaries, had they been available. This would clearly show a thematic variation of population density. And of course, finer grained detail will be required to fulfill the original intention to show Nairobi’s vast differences in population density.

Where have we gone

Government data sets, authoratative civil society data sets, and completely crowd sourced data sets, layerd together in a single map, revealing a little more about Nairobi, and about the data itself. Each is collected, distributed, and updated in different methods. In some ways, I feel OSM leads the wild edge here of what’s possible, and what we want: a truly social environment for data. Data without community is data dry and unimportant. Of course, I’m not saying OSM is the final repository for all data: OSM doesn’t deal with demographic and private data of a census, and the methods to authoritatively certify versions of OSM data are just starting. But this hasn’t stopped several kinds of OSM and government interaction already beyond the “traditional” import, with the likes of Portland and the USGS interacting with the OSM community.

The ultimate promise of all this OpenDataKE is not necessarily in the data itself, but in the deep and wide serving conversations openness triggers. My own personal metric for this will be when government officials from OpenDataKE and slum dwellers from Kibera and Mathare (and Mukuru) openly collaborate and work together. Can’t wait to see this happen. To get there, I challenge you too … get geeky with some data and write about it!