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At our November 18th Technology Salon, we discussed how different organizations are developing their ICT for development (ICT4D) strategies. We shared learning on strategy development and buy-in, talked about whether organizations should create special teams or labs for ICT- and innovation-related work or mainstream the ICT4D function, and thought about how organizations can define and find the skill sets needed for taking their ICT-enabled work forward. Population Council’s Stan Mierzwa, Oxfam America’s Neal McCarthy, and Cycle Technologies’ Leslie Heyer joined as lead discussants, and we heard from Salon participants about their experiences too.

Participating organizations were at various stages of ICT4D work, but most had experienced similar challenges and frustrations with taking their work forward. Even organizations that had created ICT4D strategies a couple of years ago said that implementation was slow.

Some of the key elements mentioned by our first discussant as important for managing and strategically moving ICT forward in an organization included:

  • being more informed about where different offices and staff were using ICTs for programmatic work,
  • establishing a standard set of technology tools for organizational use,
  • improved knowledge management about ICTs,
  • publishing on how ICTs were being used in programs (to help with credibility),
  • engaging with different teams and leadership to secure support and resources
  • working more closely with human resources teams who often do not understand ICT4D-related job descriptions and the profile needed.

Our second discussant said that his organization developed an ICT4D strategy in order to secure resources and greater support for moving ICT4D forward. It was also starting to be unwieldy to manage all of the different ideas and tools being used across the organization, and it seemed that greater harmonization would allow for improved IT support for more established tools as well as establishment of other ways to support new innovations.

In this case, the organization looked at ICTs as two categories: technology for development workers and technology for development outcomes. They used Gartner’s ‘pace layered’ model (which characterizes systems of innovation, systems of differentiation, and systems of record) as a way of analyzing the support roles of different departments.

One of the initial actions taken by this organization was establishing a small tech incubation fund that different offices could apply for in order to try something new with ICTs in their programs and campaigns. Another action was to take 10 staff to the Catholic Relief Services (CRS) ICT4D conference to learn more about ICT4D and to see what their peers from similar organizations were doing. In return for attending the conference, staff were required to submit a proposal for the tech incubation fund.

For the development of the strategy document and action plan, the ICT4D strategy team worked with a wider group of staff to develop a list of current ICT-enabled initiatives and a visual heat map of actions and activities across the organization. This formed the basis for discussions on where lots of ICT4D activities were happening and where there was nothing going on with ICTs. The team then discussed what the organization should do strategically to support and potentially consolidate existing activities and what should be done about areas where there were few ICT-related activities – should those areas be left alone or was there a reason to look at them to see if ICT should be incorporated?

Having done that, the organization adapted Nethope’s Organizational Guide to ICT4D to fit its own structure and culture, and used it as a framework for ICT4D strategy discussions with key staff from different teams. The Nethope guide suggests five key functions for strategic, organization-wide ICT4D: lead organizational change, drive knowledge exchange, build a portfolio, manage processes, and develop an advisory service (see below). The aforementioned activities were also clustered according to which of these 5 areas they fell into.

Screen Shot 2015-11-24 at 8.53.12 AM

(Table of contents from Nethope’s Guide.)

The organization felt it was also important to change the image of the IT team. ‘We had to show that we were not going to tie people up with formal committees and approvals if they wanted to try something new and innovative. Being more approachable is necessary or staff will bypass the IT team and go to consultants, and then we open ourselves up to data privacy risks and we also lose institutional knowledge.’

Salon participants agreed that it was important to know how to “sell” an ICT4D-related idea to frontline staff, management and leadership. Some ways to do this include demonstrating the value-add of ICTs in terms of longer-term cost and time efficiencies, showing the benefit of real-time data for decision-making, and demonstrating what peer organizations are doing. Organizations often also need someone at the top who is pushing for change and modernization.

Our third discussant said that her company has been shifting from a commercial product developer to a full-fledged technology company. She outlined the need for strategic thinking along that journey. Initially, the company outsourced activities such as research and data collection. With time, it started to pull key functions in house since systems maintenance and technology has become a core part of the business.

“As a small company, we can be flexible and change easily,” she said. ‘ICT is embedded into our culture and everyone thinks about it.’ One challenge that many ICT4D initiatives face – whether they are happening in a non-profit or a for-profit — is sustainability. ‘People are often fine with paying for a physical product, but when it comes to the web, they are accustomed to getting everything for free, which makes long-term sustainability difficult.’

In order to continuously evolve their strategies, organizations need to have time and space to constantly step back and think about their underlying values and where they see themselves in 5 or 10 years. A more pro-active relationship with donors is also important. Although Salon participants felt that the ICT4D Principles and related processes were promising, they also felt that donors do not have a clear idea of what they are looking for, what exists already, what needs to be created, and what evidence base exists for different tools or kinds of ICT4D. One Salon participant felt that ‘donor agencies don’t know what kinds of tech are effective, so it’s up to you as an implementer to bring the evidence to the table. It’s critical to have the ITC4D support staff at the table with you, because if not these more detailed conversations about the tech don’t happen with donors and you’ll find all kinds of duplication of efforts.’

Another challenge with thinking about ICT4D in a strategic way is that donors normally don’t want to fund capacity building, said another Salon participant. They prefer to fund concrete projects or innovation challenges rather than supporting organizations to create an environment that gives rise to innovation. In addition, funding beyond the program cycle is a big challenge. ‘We need to be thinking about enterprise systems, layered on systems, national systems,’ said one person. ‘And systems really struggle here to scale and grow if you can’t claim ownership for the whole.’

Salon participants highlighted hiring and human resources departments as a big barrier when it comes to ICT4D. It is often not clear what kinds of skills are needed to implement ICT4D programs, and human resources teams often screen for the wrong skill sets because they do not understand the nature of ICT4D. ‘I always make them give me all the CVs and screen them myself,’ said one person. ‘If not, some of the best people will not make it to the short list.’ Engaging with human resources and sharing the ICT4D strategy is one way to help with better hiring and matching of job needs with skill sets that are out there and potentially difficult to find.

In conclusion, whether the ICT4D strategy is to mainstream, to isolate and create a ‘lab,’ or to combine approaches, it seems that most organizations are struggling a bit to develop and/or implement ICT4D strategies due to the multiple pain points of slow organizational change and the need for more capacity and resources. Some are making headway, however, and developing clearer thinking and action plans that are paying off in the short term, and that may set the organizations up for eventual ICT4D success.

Thanks to Population Council for hosting this Salon! If you’d like to join discussions like this one, sign up at Technology Salon.

Salons are held under Chatham House Rule. No attribution has been made in this post.

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

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

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

What do we mean by ‘big data’?

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

Why is big data a ‘thing’?

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

What does big data mean for development evaluation?

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

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

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

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

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

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

Are we all going to be using big data?

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

What about groups of people who are digitally invisible?

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

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

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

Where is big data most applicable in evaluation?

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

Screen Shot 2015-11-23 at 9.32.07 AM

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

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

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

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

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

What about bias in data sets?

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

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

What about the ethical and privacy implications?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

 

Screen Shot 2015-09-02 at 7.38.45 PMBack in 2010, I wrote a post called “Where’s the ICT4D distance learning?” which lead to some interesting discussions, including with the folks over at TechChange, who were just getting started out. We ended up co-hosting a Twitter chat (summarized here) and having some great discussions on the lack of opportunities for humanitarian and development practitioners to professionalize their understanding of ICTs in their work.

It’s pretty cool today, then, to see that in addition to having run a bunch of on-line short courses focused on technology and various aspects of development and social change work, TechChange is kicking off their first Diploma program focusing on using ICT for monitoring and evaluation — an area that has become increasingly critical over the past few years.

I’ve participated in a couple of these short courses, and what I like about them is that they are not boring one-way lectures. Though you are studying at a distance, you don’t feel like you’re alone. There are variations on the type and length of the educational materials including short and long readings, videos, live chats and discussions with fellow students and experts, and smaller working groups. The team and platform do a good job of providing varied pedagogical approaches for different learning styles.

The new Diploma in ICT and M&E program has tracks for working professionals (launching in September of 2015) and prospective Graduate Students (launching in January 2016). Both offer a combination of in-person workshops, weekly office hours, a library of interactive on-demand courses, access to an annual conference, and more. (Disclaimer – you might see some of my blog posts and publications there).

The graduate student track will also have a capstone project, portfolio development support, one-on-one mentorship, live simulations, and a job placement component. Both courses take 16 weeks of study, but these can be spread out over a whole year to provide maximum flexibility.

For many of us working in the humanitarian and development sectors, work schedules and frequent travel make it difficult to access formal higher-level schooling. Not to mention, few universities offer courses related to ICTs and development. The idea of incurring a huge debt is also off-putting for a lot of folks (including me!). I’m really happy to see good quality, flexible options for on-line learning that can improve how we do our work and that also provides the additional motivation of a diploma certificate.

You can find out more about the Diploma program on the TechChange website  (note: registration for the fall course ends September 11th).

 

 

 

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

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

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

*****

Announcing WhiteSave.me

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

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

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

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

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

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

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

How it Works

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

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

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

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

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

 

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

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

Elements and principles of high quality public participation

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

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

Principles underlying public consultation processes are that they should be:

  • Inclusive
  • Representative
  • Transparent
  • Accountable

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

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

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

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

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

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

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

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

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

Aggregation vs deliberation

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

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

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

Use of technology biases participation towards the elite

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

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

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

Combining online and offline public consultations

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

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

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

The importance of accountability

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

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

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

Political will and responsiveness

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

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

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

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

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

I love Dr. Seuss. His books are creative and zany. He made great social commentary. “If I Ran the Zoo” is a story about innovation and re-invention*. The hero, Gerald McGrew, is a young a boy who re-imagines the zoo. In his vision for the new zoo, he travels the world to find cool creatures that no one has ever seen. He brings them back to showcase in his “new zoo McGrew zoo,” which is dynamic, flashy and exciting.

McGrew’s new zoo looks a lot like today’s world of development sector innovation and “innovation for social good.” Great ideas and discoveries; fresh things to look at, play with and marvel at; but also quite laden with an adolescent boy’s special brand of ego and hubris.

See, most of our institutions have been basically like this for a while:

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But over the past decade, we’ve been hearing quite a lot of this:

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People inside and outside of the development and social sectors are innovating really hard to come up with new and cool things. Silicon Valley is putting in its two cents and inventing “life-changing solutions.” People are traveling all around and looking for “local” innovation, too. Some donors are even are supporting what they like to call “reverse innovation.” It feels a bit like the days of colonization are rolling on and on.Screen Shot 2015-06-12 at 1.49.18 PM

We see people with resources exploring and looking for opportunities, amazing ideas, and places to invest in or extract out value (BOP anyone?). These new ideas and innovations are captured and showcased for donors, investors, and global development peers.

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The most innovative are applauded and given more resources. Those who “win” at innovation are congratulated on Ted stages, like McGrew is for his cool new flavor of exotic creatures.

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But it’s fairly safe to say that one of the biggest problems in the world today is inequality. Many believe it’s the development model (in the small and the big sense) itself that’s the problem. Yet most of this “innovation for social good” is being stimulated by and developed within the capitalist, colonial, patriarchal models and structures that entrench inequality in the first place.

If I ran the zoo, I’d take innovation in a different direction. I’d try to figure out how to dismantle the zoo.

*****

Fun fact: Many people credit Dr. Seuss with coining the term ‘nerd’ in this book.

(Screenshots from: https://www.youtube.com/watch?t=20&v=BLQpqkbsrr0 and https://books.google.com/books?id=fdX3xUSbriIC&pg=PT57&source=gbs_selected_pages&cad=3#v=onepage&q&f=false. Book by Dr. Seuss from 1950)

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