The Complete Picture Project: Uncovering hidden AI bias

Can the diversity of the crowd be properly represented in AI datasets?

How do developers and users ensure that Artificial Intelligence (AI) algorithms serve all the members of a community equitably and fairly? The Outsight team has a solution…

This is not a small question. According to Forbes, the global AI-driven machine learning market will reach $20.83B in 2024. Low- and middle-income countries have already seen a rapid expansion in applications using this technology. Not surprisingly, the humanitarian and development sectors increasingly make use of machine learning models to reach beneficiaries faster, understanding needs better and make key decisions about the form and execution of life-saving programs.

AI-driven applications range from chatbots that connect individuals affected by disaster to their required resources, to applications that help diagnose bacterial diseases. These increasingly powerful new tools have the potential to dramatically improve aid delivery and life in communities affected by crisis. However, this value is tempered by the reality that biases can easily find their way into even the most diligently engineered applications.

AI models and applications are often built far from the communities where they will eventually be used, and are based on datasets that fail to reflect the actual diversity of these communities. This disconnect can lead to the inclusion of unintentional biases within an AI model, ultimately driving unfair system choices and recommendations that are difficult to detect.

For example, a recruiting application using AI may be designed to encourage new economic job opportunities and evaluate all the candidates applying for jobs. This is a laudable goal, but it can be tainted by biases in the algorithm that unfairly treat factors associated with gender, social background, physical ability, or language. The algorithm can systematically exacerbate existing disadvantages faced by certain groups.

Similar challenges can face large-scale aid programs that attempt to leverage AI. A cash distribution program serving an area hit by disaster or a conflict may use AI to guide cash distribution, check for misuse, and measure performance. If these automated insights favour certain communities, they could end up excluding already marginalised groups and individuals.

The Hiding Places of Bias

Whenever AI is employed in a decision-making system, it is in the interests of technical developers, adopting organisations, and communities to ensure that the algorithms are providing value, while not causing harm due to bias.

Determining whether subtle bias exists within an algorithm is a difficult task — even for experienced data scientists and conscientious AI users. A wide range of factors may contribute to bias within an AI algorithm, some of which are the result of the algorithm’s performance. There is a growing set of tools to help search for algorithmic bias within the logic of an AI application.

Evaluating the ‘wiring’ of an AI tool is important, but it is not the only concern. The sources of bias may inadvertently be embedded in the data set itself. Data bias risks can include:

• Who is included — Bias in choosing who is selected in a data set.

• How data are connected — Failure to recognise connections amongst different data that are important within a community.

• Depth of insight — Failure to capture elements that are uniquely important for members of a community group.

As an example, datasets that are used to train and test AI models often only represent the digital footprint of a community and not its real diversity. As a result applications are developed based on the characteristics of well represented community groups.

A typical, unrepresentative dataset, upon which AI models are often based.

In contrast, a true picture of the community might reveal many more ‘invisible’ members whose needs, resources, and desires are quite different; but that are not represented in the digital footprint.

The invisible real picture.

An algorithm that bases its logic on an incomplete or inaccurate picture of a community will be hard pressed to assure it has not inherited biases from the data it used. Similarly, it will be difficult for a potential user of a new AI algorithm to evaluate whether it exhibits bias, if the data used for the test is itself incomplete and fails to accurately reflect the diversity of a community.

The Complete Picture Project: Building Complete Views of Communities

The Complete Picture Project (CPP) addresses the challenge of hidden bias in incomplete data sets by constructing data resources that offer a complete view of the true diversity within a community. These data sets are assembled from multiple sources and may include a wide range of source content. The goal is to provide those working to evaluate AI bias with a known starting point — where representation within the community has been carefully considered within the data.

These data sets are well positioned to support various actors in the AI ecosystem (AI designers, AI developers, data scientists, policy makers, user researchers as well as users of AI systems) who are seeking to test AI bias. These evaluations are particularly important when engaging with communities most impacted by the SDG’s. These communities may have unique traits that differ from those included in more conventional data sources. They are also more likely to have data gaps and distortions due to access to digital technologies.

These independent, broadly diverse, representative test datasets offer developers and other AI testers a data resource for which the form and content are known. These datasets can then applied to AI models and the results inspected for biases that are hidden in the model itself. This ability to test for bias across the whole community would support efforts to detect gender and other group biases at any stage of the AI development lifecycle, from early design and development to long after pre-trained algorithms are already in use.

Scaling the Impact of CPP Data Sets

CPP data sets can provide a valuable resource in support of responsible AI development and use. Intentionally constructed data sets that broadly reflect the true diversity of communities can help advance gender equality and women’s empowerment (SDG 5).

While these datasets are being initially designed to specifically address data scenarios that are relevant to women, children, and communities who are most impacted by the SDGs, the CPP methodology we establish could be easily be extended and scaled to include other applications where parameters of where algorithmic bias is a risk as well.

The definition of bias is ever-evolving. As AI developers and their sponsors build a better understanding of the real world and the biases in it from various dimensions (such as geography, culture, non-binary gender, language, migratory status, ethnicity and race), it will be important to expand the availability of intentionally representative data sets. Building a collaborator network is key to the strategy for broad development and use of CPP data sets. Collaborators are needed to better understand communities, provide and shape data sets, and to apply data to AI algorithms. There are strong network effects among this ecosystem, where AI sponsors, governments, developers and data owners combine to drive and build off each others contributions.

The intent of the CPP team is to capture and distill practices and methodologies so that they can be broadly shared and adopted by others. The availability of individual data sets will vary according to each specific use case, but open data resources would be created when possible.

Overview of the planned CPP approach.

Next steps

The CPP team are keen to connect with organisations who are interested in collaborating on the project. Please feel free to get in touch or contact us on LinkedIn to find out more.

About the Authors and Outsight International

Devangana Khokhar
Devangana Khokhar is an experienced data scientist and strategist with years of experience in building intelligent systems for clients across domains and geographies and has a research background in theoretical computer science, information retrieval, and social network analysis. Her interests include data-driven intelligence, data in the humanitarian sector, and data ethics and responsibilities. In the past, Devangana led the India chapter of DataKind. Devangana frequently consults for nonprofit organisations and social enterprises on the value of data literacy and holds workshops and boot camps on the same. She’s the author of the book titled Gephi Cookbook, a beginner's guide on network sciences. Devangana currently works as Lead Data Scientist with ThoughtWorks.

Dan McClure
Dan McClure specialises in complex systems innovation challenges, and acts as a senior innovation strategist for commercial, non-profit, and governmental organisations. He has authored a number of papers on systems innovation methodologies and is actively engaged with aid sector programs addressing cutting edge issues such as scaling, localisation, and dynamic collaboration building. His work builds on decades of experience as a systems innovation strategist working with global firms in fields spanning technology, finance, retail, media, communications, education, energy, and health.

Lucie Gueuning
Lucie manages the MSF REACH project — researching AI and machine learning in the humanitarian context. More widely, she focuses on digital implementation for the development and humanitarian sector. She believes that digital solutions can be harnessed in order to increase the efficiency of the humanitarian sector and the service provisions for the most vulnerable.

Denise Soesilo
Denise is one of the Co-founders of Outsight and has worked with many humanitarian and UN agencies — advising on the application and implementation of technologies in humanitarian operations.

Outsight International
Outsight International provides services to the humanitarian and development sector in an efficient and agile way. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with the Outsight team, please get in touch or follow us on LinkedIn for regular updates.

Building an educational sectoral crypto-currency for the development sector

Recently Outsight was asked to help the Italian NGO, Helpcode, in partnership with the Politecnico Milano, scope how crypto-currency might be used to provide better services to beneficiaries in their projects. After some initial research we focused on sectoral currency as a way to multiply the value of donations in the education sector. Louis and Denise, the two founders of Outsight discuss the work…

The non-profit sector has, in recent years, started to take an interest in emerging blockchain and crypto-currency technologies, as these provide the potential process large amounts of transparent transactions at low transaction costs. These qualities — in theory — should enable the financial inclusion of beneficiaries, as the barriers of entry are low. In addition, specialised crypto-currencies can be utilised to multiply the impact of monetary funds when set up as a sectoral currency.

What is sectoral currency and how does it work?

The late Bernard Lietaer was a strong proponent of the radical possibilities of sectoral currencies and monetary systems to solve many challenges of today’s world. These included looking at the way we value resources in a short-termist fashion, to proposing mechanisms to protect the world economy from inflation. Among his many interesting initiatives, is the ‘Saber’ educational currency idea, designed for implementation in his native Brazil.

The educational currency is designed to set in motion “a substantial “learning multiplier” so that a given amount of money can facilitate substantially more learning for a greater number of students. The currency would fuel this learning multiplier without creating any new financial pressure on the economy. What this means in practice is that a tangible resource (in this case, a university scholarship) is given to younger students, rather than those who will use it. As the resource — turned into tokens — enters the educational system at a younger age, it is then possible to build a transaction chain between students of different ages until the tokens reach the older students who can cash them in with the university. The transactions that take place along the chain can be adapted to the needs of the system. In this case, the aim is for older students to provide mentoring services to younger students.

Students in the system hold an electronic wallet containing tokens. When a mentoring session takes place, the younger student will then ‘pay’ the older student with the tokens, which over time pass up the chain, age-group by age-group, until they reach the university students by the deadline of that year’s currency validity. Importantly, a demurrage fee (it loses its value after a set period) is attached to the currency in order to keep it in circulation. This prevents students from holding onto the tokens for their own profit later on as 100 tokens this year will become 50 tokens next year if not used. We have illustrated this chain below.

An overview of the educational sectoral currency system in the hypothetical DRC context.

In this example, a token could pass through five transaction points before being cashed in. Thus, a single scholarship for one student is having a positive impact on five other students who would otherwise not receive any direct benefit. This multiplying effect is the true genius of the sectoral currency approach and can be adapted to help many sectors, such as environment or care.

About the context

The Helpcode project location of Bukavu, Democratic Republic of Congo was used as a hypothetical location for the use of sectoral cryptocurrencies in support of ongoing programmes with the broader aim to reduce poverty through improved access to education. At the current stage of the research, the location provided the use case for the exploration and prototyping. There are currently no plans for direct implementation.

Bukavu is a city of about 800,000 inhabitants in the east of the DRC on the southernmost shores of Lake Kivu. Bukavu is a commercial and industrial center in the region and is known for the production of coffee, tea, tobacco and strawberries). Bukavu is host to four universities and at least four higher learning institutes including a teacher training college, a scientific research institute and an Institute of medical technology.

Helpcode has a small presence in Bukavu mostly through financially supporting school children. Funds are administered to the Foundation Foyer Ek’Abana, who then disburses the funds to about 1,600 beneficiaries — all of them children — to support the costs of attending schools.

Additional projects are planned to provide a mobile medical unit to serve about 1,500 street children throughout the city with basic medical services, alongside programs to reunite these children with their families and to provide economic support, as well as supporting return to school and connecting to job opportunities. Many children living on the streets are orphaned. Many do not have identities, though some support exists now to issue birth certificates and IDs. Unconditional cash transfers alongside the current support may be an option to older children, but these children do not typically have smartphones.

In this context, sectoral currency could offer the added benefit of increasing value for every dollar invested by providing the system to school age children who could then exchange credits for mentoring or services from older children who will use them for scholarships. The value of the system would be underpinned by Helpcode by making an agreement to exchange the local currency for an agreed cash value at the end of each school year. As the currency moves up the chain towards the final use at university, each owner can receive something in exchange for the currency that is of value to the older students — i.e. mentoring, care services, food. The value of each dollar of the currency effectively increases each time it changes hands moving up the chain.

The prototype

Following the system proposal, Politecnico Milano produced a prototype built using the Ethereum platform. The prototype offers the following features:

• Registration as a student

• Peer-to-peer transactions for mentoring sessions using QR codes.

• Picture proof for mentoring sessions.

• Demurrage of currency for each school year.

• Cash-in at university.

At an early prototype stage, this is how the app looks.

The welcome page of the app.

The wallet page of the app. Here you can select the type of service and whether to send or receive tokens.

The transaction history page of the app. Where students can view their transactions.

The transactions themselves are made using a QR codes. The mentoree scans a QR code on the mentor’s phone once a session is complete to send credits to them.

The mentor’s receiving page.

The mentoree’s sending credits page. This would turn on the camera to scan the QR code.

Other important considerations

As a novel and relatively complex concept, it is important to consider the potential pros and cons of pursuing this idea in a development context.

Pros:

• Sectoral currency has been trialed in Japan.

• Some progress on humanitarian local currencies with ICRC.

• Increases the value of scholarships beyond just recipients.

• Existing demurrage crypto-currency example.

Cons:

• Need to ensure access to suitable end devices for trading with the currency.

• Risk of unforeseen variables — what if the currency becomes tradable for illicit services?

• Risk of monetizing transactions that should otherwise be freely shared (casual homework support, advice)

We also listed some remaining questions and concerns that need to be addressed before pursuing implementation further.

• Does this process require a critical mass of users to be effective?

• How much adult guidance is required in this process for oversight and guidance?

• What constitutes a valid mentoring session to initiate a transaction?

• Do all children need their own smartphone or can a third party on the ground manage the transaction while younger children deal with hard tokens / paper wallets only?

• What basic conditions need to be met for a sectoral currency to be successful?

Next steps

Together with Helpcode and Politecnico Milano, Outsight is pursuing the further development of the educational sectoral currency platform. We aim to engage with end users from a UX and service design perspective in order to ensure we can address the outstanding questions and make the tool more specific for its context of use. If you’re interested in using sectoral currency or want to discuss the topic with us, please feel free to get in touch.

ABOUT the authors AND OUTSIGHT INTERNATIONAL

Denise Soesilo
Denise is one of the Co-founders of Outsight and has worked with the World Bank and other development, humanitarian and UN agencies — advising on the application and implementation of space-based systems and other technologies in humanitarian operations.

Louis Potter
Louis is one of the Co-founders of Outsight. He has a wide range of experience covering development, health, innovation, technology and research. Having worked in the field, he is well acquainted with the practical realities of delivering impact. In recent years, he has been helping organisations to improve innovation processes and outcomes. He is an experienced facilitator and has been closely involved in efforts to improve collaborations between the nonprofit, academic and commercial sectors. He is based in Lausanne, Switzerland, and received his MSc in Global Health from the Karolinska Institute, Sweden.

Outsight International
Outsight International provides services to the humanitarian and development sector in an efficient and agile way. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with the Outsight team, please get in touch or follow us on LinkedIn for regular updates.

How can behavioural economics help us understand decision-making during COVID-19?

Behavioural economics offers an insight into why people make the decisions they do. In a pandemic — when even apparently small decisions may involve high stakes — the discipline can provide an insight into how such choices are made, and critically asses the emotional vs logical. In this blog, we offer an overview of some of the basic concepts of behavioural economics and how these apply to the current COVID-19 outbreak…

Many countries are moving forward and easing lockdown restrictions while there are still many unknowns about the virus and how it spreads. They are proceeding with varying degrees of caution in the face of unknowns related to both where and when the virus will flare-up as well as economic uncertainty. For example, EU countries anticipating the summer tourism season have focused on easing travel restrictions and opening up the leisure sector. But already, reports from several countries highlight the reality of recurring flare-ups of the disease.

There is widespread reluctance to re-impose lockdowns, and to incur further risks to economies as well as general morale. But in economies that are driven by consumer spending, how individuals make decisions in the face of such uncertainty will have profound impacts on both the path of economic recovery as well as the course of the pandemic. Previously mundane decisions such as whether and when to go clothes shopping, visit the mall, or to go out to a restaurant or pub, now have to take into consideration risks associated with COVID-19.

The field of behavioural economics could have much to offer as policy makers face difficult choices and trade-offs in the months ahead as the world adapts to the reality that COVID-19 is not going away soon. In the UK, the government use of behavioural insights has already been widely trailed, though not without some controversy. Behavioural economics studies the influence of psychological factors on how humans make economic decisions. It extends traditional economics to better account for real people’s beliefs and biases. Nobel prize-winner Richard Thaler summarises these extensions in terms of three 'bounds' on the behaviour economists have tended to assume:

“Bounded rationality reflects the limited cognitive abilities that constrain human problem solving. Bounded willpower captures the fact that people sometimes make choices that are not in their long-run interest. Bounded self-interest incorporates the comforting fact that humans are often willing to sacrifice their own interests to help others.”

As countries and communities move from an initial phase of tight lockdown and the associated restrictions on activity — which were necessary to “flatten the curve”, slow the spread of the virus, and avoid overloading health facilities — behavioural economics can teach us, first, about how people assess risks and, second, about how they then go on to make decisions based on the risks that they’ve assessed.

Assessing risks

Fundamentally, human beings are not always good at assessing risks. To take just three examples (though there are many more):

1. Probability weighting is a key element of Daniel Kahneman and Amos Tversky's Prospect Theory, introduced in one of the most cited social science papers of all time. Probability weighting tells us that we systematically overestimate small risks and systematically underestimate large ones. But we generally get certainty and impossibility right, which means there's a discontinuity or certainty effect at the extremes. As long as the risk to individuals of catching COVID-19 remains low, we might expect this effect, on its own, to lead to an abundance of caution.

2. We make mistakes about the independence of events. One manifestation of this is in the gambler's fallacy, through which people create imaginary dependencies between independent events. For example, the gambler’s fallacy predicts a strong intuition that a black is 'due' on the roulette wheel if we’ve just witnessed a long sequence of reds. Or that, in relation to Covid-19, we’ll feel that an individual risky behaviour becomes that bit riskier with each successive occasion that we get away with it (the total risk does increase, of course, but not the risk per occasion).

3. We easily confuse the probability of seeing some piece of evidence given that a hypothesis is true (e.g. the chance that I get a positive test result, given that I have COVID-19) and the probability that a hypothesis is true given that I see some piece of evidence (e.g. the chance I have COVID-19, given that I get a positive test result), when in fact these quantities are often very different. For instance, say that there's a 0.1% rate of the disease in a population, and a test for the disease gives the right answer 99% of the time. Most people who get a positive test result during a routine screening will think it is now 99% certain they have the disease. But because the rate of infection in the population is low, the true probability in this case (which statisticians can calculate with Bayes’ Rule) is actually still under 10%.

Making decisions under risk

Behavioural economics tells us a wide range of ways in which our probability judgments tend to go awry. But even given correct probabilities, the way we use those probabilities to arrive at choices often seem to lack any immediate sense.

A key influence here is framing and, in particular, whether changes are presented in terms of gains or losses. As it happens, an illustration given in a paper by Tversky & Kahneman in Science hits rather close to home. The setup is as follows:

Imagine that the U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimate of the consequences of the programs are as follows:

- If Program A is adopted, 200 people will be saved.

- If Program B is adopted, there is 1/3 probability that 600 people will be saved, and 2/3 probability that no people will be saved.

Which of the two programs would you favour?

On the average, programs A and B will save the same expected number of people (200), but A is a safe bet on saving exactly that number, while B is a gamble that may or may not save them all.

A big majority of respondents in the study (72%) favoured the safe option, program A. But then the researchers polled a second group, making a simple tweak to the language they used:

- If Program C is adopted 400 people will die.

- If Program D is adopted there is 1/3 probability that nobody will die, and 2/3 probability that 600 people will die.

These new programs do nothing but reframe the first set: C is identical to A, and D is identical to B. But, strikingly, this reframing utterly reversed the majority preference. Now, 78% of respondents preferred the risky program, D.

This is no fluke. One of us (GM) has replicated the result seven years in a row with students on a behavioural economics course. The reasons have to do with our diminishing sensitivity to both gains and losses relative to a reference point, which Prospect Theory captures with something called the Value Function (a replacement for economists’ usual workhorse, the utility function).

The upshot is that we’re generally risk-averse in relation to prospective gains but risk-seeking in attempts to avoid losses. The effect is extremely deep-seated: it has even been demonstrated, through some rather ingenious experiments, in capuchin monkeys by Chen & Santos.

Communicating risk

These sorts of effects are of clear relevance to leaders and governments responsible for formulating guidance and communicating to the wide public during times of uncertainty. The words and behaviour of a leader will strongly influence how a large majority of the population will make individual decisions that will have major economic and human impacts in consumer-driven societies.

With what we know from behavioural economics, how individuals actually decide what is gain and what is loss will influence these decisions.

For example, a political leader that states. “We’re open again for business”, and who accompanies that with a relaxation of social distancing measures may set an expectation that social activities such as congregating in bars, in parks, or beaches is again the norm. Thus, individuals could see not resuming these activities as a loss; and therefore, according to behavioural economics, engage in risk-seeing behaviour, not wearing masks and not respecting social distancing. The spike in cases we’re seeing in some US states, could potentially be due to this phenomenon.

On the other hand, a leader who leans too much towards caution — out of fear of seeing even a handful of new cases — may lead to people hesitant to venture out of their homes even for lower risk situations, such as going out to the park for a walk. There has been a lot of criticism of public health leaders: from their perspective, a high degree of caution will continue to be needed until the threshold of herd immunity is reached; which could be 1-2 years away. However, our economies will struggle to continue in suspended animation until then.

Therefore it is advisable for leaders to use wording and to communicate in ways that are balanced: it’s possible to be “open for business” while also assuring the population that “we’re going to double the number of testing centres” to retain the sense of caution. 

Getting this right is crucial over the months ahead as we all manage health and economic risks.

About the authors and Outsight International

Dr George MacKerron
George is a Senior Lecturer in Economics at the University of Sussex. His research is in subjective wellbeing, behaviour and the environment. He runs Mappiness, the world's largest experience sampling study, and is a co-founder of startup Psychological Technologies. George gained his PhD at the LSE, and prior degrees from Imperial College London and the University of Cambridge.

Dr Evan Lee
Evan is a trained MD and MBA with degrees from Harvard and MIT, he has dedicated his career to improving access to health. Initially practicing medicine in community health centers; for the past 20 years, he has worked across the private sector, NGO sector, and collaborated closely with UN partners to address access issues related to medicines, diagnostics, and other health technologies.

Louis Potter
Louis is one of the Co-founders of Outsight. He has a wide range of experience covering development, health, innovation, technology and research. Having worked in the field, he is well acquainted with the practical realities of delivering impact. In recent years, he has been helping organisations to improve innovation processes and outcomes. He is an experienced facilitator and has been closely involved in efforts to improve collaborations between the nonprofit, academic and commercial sectors. He is based in Lausanne, Switzerland, and received his MSc in Global Health from the Karolinska Institute, Sweden.

We believe that understanding the motivations behind behaviour is an essential part of quality strategy planning. This can apply to governments, industry or the third sector. As Outsight, we are happy to consult Outsight International provides services to its clients in an efficient and agile way using the ‘Hollywood Model’. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with the Outsight team, please get in touch or follow us on LinkedIn for regular updates.

The Hollywood Model: Dynamically built teams for creativity at scale

Outsight works with its network of Associates using the Hollywood model — a way to build dynamic teams, quickly, that are best-suited to a particular project. This can be particularly useful in the humanitarian and development sectors, where the tendency is to hire based on narrow technical competencies. But how does it work? And why is it called the Hollywood model? Dan McClure, an Outsight Associate explains more…

How many organisations can produce the equivalent of a hit movie? While it’s easy to roll your eyes at some of Hollywood’s efforts, the reality is that this industry is capable of repeatedly undertaking new and original initiatives: leveraging a myriad of different skills in the service of a complex and rapidly shifting market. Their survival and success depends on the ability to repeatedly do creativity at scale.

Until recently, few other industries had to meet similar creative demands. Most organisations — whether they were commercial businesses, government agencies, or non-profits — could focus on mastering the things they already did. A leader’s goal was to make sure things were well run and competent. Any incremental improvements reinforced established capabilities.

Committing to a steady course like this requires a stable world. Unfortunately, disruptive change is sweeping through one industry after another. Even before the advent of the global pandemic, it was clear we had entered into a turbulent era where new ideas, bold action, and systemic change would be necessary to claim a relevant place on the world stage. The winds driving this change are powerful: new technologies of a fourth industrial revolution, trans-border problems like climate change, and massive societal shifts in education, economic capacity, and urbanisation.

This is a world where being good at bold imaginative change has become a necessary core competency. For that reason, it is well worth taking a closer look at what Hollywood did to prepare for a business based on creativity at scale.

The Hollywood Studio System

Organisations are built to address the type of challenge they face. When mid-twentieth century Hollywood had to produce primarily for middle America’s host of movie theaters, the studio system arose. Large integrated movie studio operations bought together, under contract, the many types of talent needed to imagine and create a movie. Actors, directors and a host of other professionals in the employ of the studio execs — establishing a model that could efficiently produce a steady stream of films for a single major distribution channel: local movie houses.

This is not so different from the approach most large commercial and public sector institutions take to professional staffing today. As projects come and go, the organisation’s portfolio of skilled individuals are moved within the organisation, perhaps augmented by consulting resources that expand or fine tune the skill set.

Assuming a stable world, organisations can align the skills they have on staff with their mix of needs.

The studios’ comfortable level of control was challenged in final decades of the century, when the movie industry faced an increasingly challenging creative environment. New competitors threatened their entertainment monopoly and audiences demanded a more sophisticated and varied fare. Movies yielded ground to TV, which gave way to cable, and has now fragmented into a host of streaming services and other specialised media platforms. The quantity and sophistication of content has rushed ahead too, with last decade seeing the number of scripted shows growing by over 150% ushering in an age of peak TV.

The industry had to produce more demanding creative work at an ever accelerating pace. The unique demands of ambitious projects made it increasingly difficult to effectively bring the talent needed for the varied efforts under one roof. While a big budget action film might be best served by one set of skills, these could quite different from those needed to successfully realise an intimate drama or scripted TV series on a streaming service.

As creative projects grew in ambition and became increasingly unique, the studio lost its role as the centralised home of talent. Thus, more projects were assembled from a pool of individuals and organisations that had specific skills and resources.

Dynamic Collaborations: Building the Right Team

This shift from highly centralised team to custom-created networks of collaborators makes sense when program efforts must be both ambitious and original. Big ambitious challenges need a wide range of different skills, so there is creative power in a model where the right talent can be bought together for each unique project.

An organisation with its own ‘studio’-style teams inevitably find it difficult to overlay their fixed set of organisation skills on such shifting needs. Mismatches and gaps quickly emerge. In some cases, additional capacity will be needed, while in others, exceptional skills will go to waste. Gaps emerge in areas of expertise either because existing staff are insufficiently skilled or because the role is entirely new.

In this turbulent creative environment, the value of a stable, highly optimised, organisational skillsets is eroded. The new Hollywood Model recognised this, assembling a tailored team for a specific initiative and then allowing the various professionals to move to another project.

It should be noted that this ability to build dynamic teams is not about fighting for the top 1% of super skilled individuals. That’s a game that large well funded organisations will almost always win. Instead, highly effective teams are created by tailoring the right type of talent to the task. Someone who might be of marginal value on one project, could be a premier contributor on a different type of initiative. Leaders don’t need to fight for the widely recognized superstars, but rather can focus on finding the uniquely right contributor.

The ability to align complex projects with diverse talent also provides creative returns to the project contributors. Practitioners with a unique set of skills can cobble together a series of similar projects where their talents are fully appreciated. It also becomes possible for those with a more vagabondish soul to diversify their work, avoiding pigeonholes by embracing a number of different efforts.

Fostering Dynamic Creative Ecosystems

As the demands for creativity at scale grow in the world, other sectors can and should look for opportunities to adopt a Hollywood Model of dynamic collaboration building. Of course, this shift comes with new demands. One of the crucial advantages of traditional self-contained organisations is that the infrastructure for managing and integrating teams is clearly defined. When Hollywood abandoned the studio system, a number of new supporting services needed to emerge to fill these ecosystem building needs.

This is not trivial work. Dynamically constructing a collaboration requires the ability to identify and validate talent, negotiate acceptable terms of engagement, and integrate day-to-day activities. Simply trawling the world talent pool for potential matches between a project and a professional creates excessive overheads for all involved.

An ecosystem of both formal and informal support for collaboration building is needed to make the model viable. Across different sectors, nimble supporting services are rising to the challenge. A wide range of approaches are emerging, ranging from bare-bones freelance marketplaces to far more sophisticated program facilitators that take an active role in execution of collaborative work.

Other aspects of the collaborative ecosystem evolve more organically. For example, a study of video game development, where the product is created by many different collaborators, found that within the shifting networks of contributors were informal clusters of professionals and teams that regularly worked together.

Time to Embrace of the Hollywood Model

As organisations find that their challenges are increasingly defined by disruptive change, rather than stable performance, the need to create at scale becomes more urgent. Leaders may be tempted to see this as an issue of imagination, driving them to promote ideas and innovations from within an organisation’s walls. Encouraging creative thinking certainly isn’t a bad course of action, but it fails to recognise the systemic barriers a self-contained organisation faces when it seeks to actually realise an ambitious new vision.

Reaching outward, creating a more flexible organisational structure by dynamically building the teams that tackle initiatives, opens the door to effective action on big ideas. Ideas can be more original (tapping the right unique skills) and bigger (assembling larger creative teams). This is done while still making it possible for each new initiative to pursue possibilities that are different from the program before.

This is the kind of creative capacity our era of disruptive change demands. Whether an organisation is working in business, government, or non-profit action, it’s time to take inspiration from the Hollywood Model, and break down walls in the name of creative prowess.

ABOUT DAN AND OUTSIGHT INTERNATIONAL

Dan McClure has spent over three decades working on the challenge of disruptive systems innovation. He has advised global commercial firms, public sector agencies, and international non-profits in support of their ambitious efforts to imagine and execute agile systems level innovation.

Outsight International is an organisation specialised in providing services to the humanitarian and development sector in an efficient and agile way. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with Dan and the Outsight team, please get in touch or follow us on LinkedIn for regular updates.

Decrypting human-centred design: Why it is important for the third sector

What role can human-centred design practically play in development and humanitarian work? As a researcher and designer, Gunes Kocabag — an Outsight Associate — is often asked this question. Sometimes with scepticism — but more often with genuine interest.

Human-centred design has become a respected practice in certain parts of the humanitarian and development sectors (aka the third sector). However, while many people may have seen references to its techniques, it may not be obvious how it is applied in practice. In this article, she outlines: what is human-centred design; why it is necessary; and how to apply it in humanitarian and development contexts.

FROM DESIGN AS A CRAFT TO DESIGN AS A MINDSET, and FROM USER-CENTERED TO HUMAN-CENTERED

Design has historically been categorised as an art, a craft, or as a way to improve the look and functionality of products. However, from the 80s onwards a new perspective on design has progressively taken hold – an approach that defines design as a process and a mindset that can be applied to solve diverse problems. The term ‘Design Thinking’ was popularised by the design firm IDEO in the early 90s and today has gained increasing popularity in the business world as a methodology to approach complex problems.

A key principle of the design mindset is its emphasis on placing user needs and expectations at the centre of the process. As users (aka customers) in the commercial context are more and more empowered with their decision making, companies are racing to understand their users and identify their innermost unmet needs to create the next winning product in the market. That is why user-centred design is increasingly popular in corporate innovation circles.

Global development work often happens within complex systems made up of multiple partners, people on the ground, multiple end beneficiaries and various contextual factors. So it is not only about creating solutions that work for the end-user but also for all key stakeholders within the system. It requires an approach that is not only user-centred, but human-centred, which takes into account the complexity of all stakeholders. Thus, in humanitarian and development innovation, the term that is predominantly adopted is human-centred design (HCD).

WHY HUMAN-CENTRED DESIGN?

Although human centred-design is becoming increasingly recognised and embraced by leading third sector actors such as the Bill & Melinda Gates Foundation, UNICEF and WHO working regularly with innovation, there remains lack of clarity on how human-centred design can be properly harnessed to ensure better interventions for a greater range of projects.

Here are three key reasons why human-centred design can greatly improve the success of humanitarian and development projects.

Reason 1: HCD complements system thinking to reveal differences between how the system works in theory and how people actually engage with it

Systems thinking is often referred to as a go-to approach to solve complex problems — and rightfully so — as it provides a great way to break down and make sense of the parts of a system and the relationships between them.

The systems thinking pioneer Donella Meadows defines social systems as “the external manifestations of cultural thinking patterns and of profound human needs, emotions, strengths and weaknesses.” Human-centred design can help dig deeper into those external manifestations to get to the core of human behaviours, needs and expectations behind them.

By placing the focus on the human actors within the system, HCD helps bring abstract concepts such as beneficiaries, government officials or private sector initiatives to life.

By placing the focus on the human actors within the system, HCD helps bring abstract concepts such as ‘beneficiaries’, ‘government officials’ or ‘private sector initiatives’ to life: identifying the human stories behind each, with their unique needs, motivations and goals. HCD’s emphasis on qualitative data helps us move beyond an understanding of what people do to an understanding of the social, cultural, and psychological patterns that reveal why people behave the way they do.

Understanding not only how the system theoretically works, but also how people live and breathe within the system, we can create effective solutions that meet needs and expectations at both functional and emotional levels.

Case study: Improving the adoption of home-based immunisation records (HBRs) in Africa

Home-based records are medical documents issued by a health authority, and provide a record of an individual’s history of primary healthcare services (e.g. vaccinations) received. They are maintained in the household by an individual or their caregiver. Since the beginning of the Expanded Programme on Immunization (EPI) in 1974, home-based records have served an important role in increasing the effectiveness and efficiency of immunisation programs around the world. However, retention rates in many countries remain significantly low, which is particularly worrying in countries with a high birth cohort.

To tackle this problem, we first need to understand the system and the actors within the system. A systems-thinking approach focuses on understanding the key parts of the system and how they interact with each other. Adding human-centred design to that, we glean a better understanding of the human actors behind the institutions and the human actors that affect and get affected by the system.

When I worked on this challenge in collaboration with WHO and multiple other development partners, focusing on six African countries, our first task was to understand the system map and identify the key stakeholders. Then we applied HCD to dig deeper. Through ethnographic, immersive research on the ground with health workers and caregivers as well as officials in the Ministries of Health, we were able to challenge the big picture.

During pilot research, we brought together Ministry of Health officials, caregivers and health workers to compare their knowledge of how the system should be working, with an understanding of how it is actually working. Being able to observe what was actually happening, the physical and emotional burdens on the ground, what unofficial, makeshift solutions were put in place by those who had to solve problems on the ground helped us all view the system under a different light and helped shift priorities at the institutional level. Through this nuanced understanding, we were able to align key stakeholders on prioritising the needs of the end beneficiaries and health workers on the ground, as well as creating a roadmap for successful implementation that balanced the different priorities of the stakeholders involved.

Reason 2: HCD goes beyond creating solutions to creating end-to-end experiences that drive adoption

For successful adoption of a developed solution, a functional framework focusing on efficient delivery is not enough. To deliver a solution that is efficient and effective, we need to ensure it fits into the lives of those who will be using it. The main premise of HCD is to frame the whole challenge from the perspectives of the human actors, be this the end beneficiary, a specific actor in the value chain, or a key decision maker. We then design interactions and experiences tailored for the specific context and expectations of those who will be interacting with the particular product or service.

When designing services, HCD addresses these interactions not only at one point in time but through the whole journey of service delivery: before, during and after. This helps us understand the functional and emotional highs and lows of the experience, developing fixes to mitigate the lows and catalysers to enhance the highs. Through this methodological approach we can identify potential pitfalls early on and design solutions that work end-to-end.

A service journey maps out the user’s experience step by step, as well as the people, processes, policies, and systems behind the service delivery.

Case study: Improving the quality of data in humanitarian emergencies

Access to high quality and timely data can be a life and death-defining factor when monitoring humanitarian emergencies. The MSF REACH project, coordinated by my colleague, Lucie Gueuning, is an initiative addressing exactly this problem through creating a web-based platform to support MSF staff on the ground. The platform combines institutional data with crowd-sourced information from various sources.

While all are working towards a common goal, the platform needs to be used by different types of users with different levels of familiarity with the technology, different environments of use, culture and legal context, different skill sets and mental models. The quality of the data, which is key to the platform’s success, depends on providing an inclusive experience to all its different users.

A human-centred approach to solution development in such a context, can ensure that the user experience of the platform is designed to maximise its effective use by different users, taking into account all steps of the experience from accessing the service to data entry to making sense of the data. To give one specific example, the design of the user interface can have a significant impact on the quality of the data as well as how users perceive and prioritise data.

By putting users at the centre, human-centred design ensures that the interactions fit the users’ different mental models and drives the adoption and successful use of the platform. For MSF REACH this means high quality data, which is critical for saving lives.

Reason 3: Through divergent thinking, HCD catalyses new perspectives and out-of-the-box solutions

HCD is a process that can be applied to different problem spaces. It is made up of iterative cycles of divergent and convergent thinking, following a pattern of exploring possibilities before narrowing down on one solution. This emphasis on divergent thinking allows its practitioners to ask ‘what if…’, think out of the box and imagine possibilities beyond established patterns of thinking. Divergence is then followed by a structured and criteria based process of convergence that defines what is possible.

HCD follows an iterative process where divergent thinking is followed by structural convergence, both for problem definition and for solution development.

Bringing together different mindsets and skills sets is essential for divergent thinking. This helps explore the problem space from different perspectives and create richer solutions. Thus, HCD projects rely on a combination of different topic expertise combined with the perspectives of stakeholders on the ground. Participatory design, co-creation with communities, design sprints are common methodologies that are used to catalyse divergent thinking in a structured way.

Case study: Developing a strategy for 10 years from now

Developing strategies and roadmaps in the humanitarian and development context is a complex task. It involves multitudes of stakeholder (often with very specific areas of expertise) who need to understand one another, if not reach a common understanding. Building empathy between stakeholders is key to having a meaningful conversation around priorities. HCD, with its emphasis on divergent thinking, can create a space for building empathy among stakeholders, a safe space to step into someone else’s shoes and think creatively. It is here that HCD practitioners can thrive in a facilitating role, helping structure discussions, outcomes and strategic roadmaps.

When I worked with a global foundation as a consultant on HCD, our challenge was to bring together employees to co-create a future strategy while introducing the HCD methodology. Using a HCD approach, we were able to get participants from different groups within the foundation to work together and collectively discuss how the foundation should evolve to support its global network of partners. In a workshop setting, participants stepped into the shoes of policy makers, advocates, scientists, end beneficiaries and other actors they interact with day to day. With this new perspective, they articulated how the future could impact those actors and what this could mean for the foundation’s strategy. This approach enabled participants to leave behind their roles and titles and explore the problem space from a new angle, providing a strong foundation for the definition of a new strategy.

To sum up, human-centred design can greatly improve the success of humanitarian or development projects by:

• Revealing the nuances between how the system works in theory and how people actually engage with it.

• Creating end-to-end experiences that drive adoption.

• Catalysing new perspectives and out of the box solutions.

HOW CAN WE APPLY HUMAN-CENTRED DESIGN IN THE THIRD SECTOR?

Going back to my initial question, ‘What role can human-centred design practically play in development and humanitarian work?’, I would like to finish this post by providing some concrete pointers on when and how you can incorporate HCD into your work:

• During scoping and need identification - to ensure we’re accounting for the experiences, needs, mindsets and context of the all human actors involved and not just making assumptions about what is needed.

• During solution development - to develop solutions that fit into the lives of the target group and provide an end-to-end experience that drives adoption.

• During implementation - to prototype and test solutions with users and stakeholders, to learn and iterate to improve the solutions.

• During monitoring and evaluation - to complement quantitative data on what is happening with qualitative exploration of why it is happening.

• Throughout our work - to catalyse collaboration, out of the box thinking, iterative solution development and experimentation through design sprints, co-creation workshops or methodological training.

Human-centred design is not just a high-level theory, but a practical tool that can add value over different project phases. For those who use it, it quickly becomes indispensable for achieving efficient and effective implementation. It is exciting to see its increased adoption in the global development field, yet there are still many more situations in which humanitarian or development practitioners are not taking in the whole picture, and thus missing opportunities to implement much more efficient projects and systems.

ABOUT Gunes AND OUTSIGHT INTERNATIONAL

Gunes is a researcher and service designer specialising in the development of human-centred solutions in complex stakeholder environments. She has worked as a consultant for public and private sector entities as well as global development organisations in areas including global health and financial inclusion.

Outsight International provides services to the humanitarian and development sector in an efficient and agile way. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with Gunes and the Outsight team, please get in touch or follow us on LinkedIn for regular updates.

Making development self-sustaining: Seven essential principles

The Kit Yamoyo diarrhoea treatment kit under local production in Zambia for the local Zambian market. The kit was designed, and the local market developed, using one-off donor funding.

What is self-sustaining development and why is it important? Simon Berry — Outsight Associate — explains…

The term ‘sustainable development’ appears often in international development discussions. But what does it mean? The phrase can be used interchangeably to mean one of two things which are, in fact, very different. In the environmental sense it means ‘living within our environmental limits’ — development that ‘meets the needs of the present, without compromising the ability of future generations to meet their own needs. The term, however, also describes development that carries on once the resources used to create it are removed. Here, I refer to the latter form of sustainable development as ‘self-sustaining development’, to distinguish it from what one might call ‘environmentally sustainable development’.

In 2010, my partner and I started discussions with stakeholders in Zambia around transforming access to oral rehydration salts (ORS), the globally recommended treatment for childhood diarrhoea. Having established that there was local interest, we set-up a UK-based charity, ColaLife, to take the idea further. We started with a trial of the idea and went on to a national scale-up. By 2016 a locally designed and tested diarrhoea treatment kit was available nationwide in supermarkets and in hundreds of small shops. Additionally, the government were showing interest in a government-branded version for distribution through its clinics.

Donor funding finished two years ago (March 2018) and ColaLife formally completed its role in September 2018. It is early days, but all indications are that the transformation we achieved while we were involved and donor funds were flowing will continue to be self-sustaining. In fact, things have developed further with the government adopting the diarrhoea treatment kit as the standard in the public sector. The change that was created with the help of donor funding and external support from ColaLife has survived following the withdrawal of both. It has proved to be self-sustaining.

How does one achieve development that is self-sustaining?

Here are some key principles I have developed over the years while working with others on development projects that I think are crucial if you are to achieve self-sustaining development.

1. Plan for self-sustainability from the outset - You don’t achieve self-sustaining development while being forced to come up with ‘an exit strategy’ two years before donor funding comes to an end.

2. Don’t do anything that makes you or your organisation a permanent part of the solution - This is crucial and is the foundation for the other principles. If you allow yourself to become a part of the solution, then, by definition, when you leave, part of the solution will leave too! It is alarming how many ‘development’ initiatives fall into this trap, always with at least two negative consequences: firstly, the change they created while operational is not sustained; secondly, while operational they are likely to have undermined and weakened the capacity of local organisations who have the long-term responsibility for creating and sustaining the desired change.

3. Do everything through local systems and structures - If you are not to become a permanent part of the solution, then you will have to work through local systems and structures. Where these lack capacity or direction, help build the capacity, help refine or improve the direction. Above all, avoid setting-up parallel systems or structures.

4. Build a ‘smart partnership’ to guide planning, testing and scale-up - It follows that you will need to work in partnership with local stakeholders. However, it is important how these partnerships are formed and operate. It is important that partnerships are formed around a shared vision not around an organisation or an individual. When this is done successfully, it promotes engagement, ensures shared ownership of the vision and helps ensure that the partnership will survive the departure of any single member. We call partnerships formed around a vision ‘smart partnerships’. From the outset, be open and inclusive: invite everyone in, as part of a process where a broad membership can self-select their level of engagement. Some may go on to become implementation partners, while others may continue as a broader consultative group.

5. Self-sustaining development should fit with government policy - If it doesn’t, seek to better align plans or work with government to influence or advocate for policy change. It is unlikely that any initiative that doesn’t fit with local policy will be self-sustaining.

6. Engage your intended beneficiaries from the very outset - This sounds obvious but it often overlooked. It is essential to operate on the basis of what you know people want, rather than on what you think they need.

7. Be invisible - The urge, on the part of donors and development agencies, to brand everything they fund or support is overwhelming. However, this must resisted as it completely changes how the intervention is perceived. For example:

This was the original artwork for the billboard for the promotion of the diarrhoea treatment kit - Kit Yamoyo – at the start of the scale-up in Zambia.

In a second phase of marketing a USAID project, run by JSI, agreed to fund additional billboards but insisted on having their logos on the billboards and these ended up looking like this.

This was a mistake. Inherent in ColaLife’s self-sustainability approach is that any donor assistance should not be permanent. This approach is not compatible with donor branding being on any customer-facing aspect of the intervention.

Integrating these principles into your project

Undoubtedly, many of these principles may require a more extensive level of planning and analysis than was originally thought necessary, yet there is no such thing as too much preparation. As explained by Dan McClure (another Outsight Associate) in his blog post on ‘Mastering the art of hard problems (and avoiding the rush to easy solutions)’ — mapping the complex systems and stakeholders involved with a problem or possible solution is essential in order to ensure that these principles can be integrated efficiently into development initiatives. Do not be scared to think big and think ahead early on in order to ensure you’re not putting out fires or having to re-orientate the project at significant extra cost further down the line.

Investing in the right things at an early stage — system design thinking, researching the existing structures, analysing the problem, and stakeholder engagement — will ensure a project stands a much better chance at becoming self-sustaining and, thus, create a greater positive impact for beneficiaries.

ABOUT Simon AND OUTSIGHT INTERNATIONAL

Over a 40-year career Simon has been a leader in the voluntary, private and public sectors. He has lived and worked in South America, the Caribbean, North Africa, sub-Saharan Africa and the UK. He is an expert on self-sustaining development – development that out-lives the resources that were used to achieve it.

Outsight International provides services to the humanitarian and development sector in an efficient and agile way. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with Simon and the Outsight team, please get in touch or follow us on LinkedIn for regular updates.

How can AI be used in the humanitarian sector? Lessons from the frontline

The MSF REACH platform on a phone in Jakarta 2018

Artificial Intelligence (AI) has become a buzzword within the humanitarian sector in recent years. Much like ‘blockchain’ or ‘drones’, it’s an area where new technology is developing quickly and operators are keen to test its possible applications. From an economic perspective, it’s big business too: from a total of $1.3B raised in 2010 to over $40.4B in 2018, funding has increased at an average annual growth rate of over 48%.

Understanding how exactly AI can positively impact humanitarian field work remains a work in progress. Lack of actionable knowledge about impact, potential, and infrastructure needed for a long-term strategy are slowing the adoption of the technology. Yet, AI-based interventions could: automate time-consuming tasks; aid in data collection and management; enhance user capacities and capabilities; and ensure emergency specialists focus on complex analysis and decision-making. But where and how should these applications be utilised to achieve this potential?

My experience working with AI

For the past three years I have managed REaction Assessment Collaboration Hub (REACH): an emergency support program to enable Médecins Sans Frontières (MSF) act faster in emergencies. REACH combines institutional data with crowd-sourced information (including social media, early alert websites, and relevant RSS feeds) in real-time to provide the organisation with virtual eyes on the ground.

Humanitarian organisations have disaster teams who specifically focus on monitoring emergencies — ensuring that collected data is timely, reliable, and shared with relevant stakeholders. The ability to deliver critical information is currently highly person-dependent, often taking significant time for the relevant information to reach decision-makers during disasters.

REACH’s platform addresses these challenges by providing a quick and more accurate insight into the evolving situation on the ground, which in turn allows for rapidly rolled-out interventions, adapted to the specific needs of an affected area.

The MSF REACH platform

In the initial phases of the REACH project, we wanted to integrate AI components into the system. However, it was through extensive research, scoping, interviews and testing that we made a strategic decision to leave these components out of the platform. The following explains why we made that decision based first on three main misconceptions we identified, followed by possible areas of added value.

Three common misconceptions about AI

• Misconception 1: AI is the same as other types of automation
  There is a general skepticism within the humanitarian sector about ‘automation’ — humanitarian work has traditionally been a sector that relies on human relationships and diplomacy in volatile contexts. To hand such delicate and high-stakes interactions to machines is understandably seen as too risky. However, to extrapolate this to all possible uses of AI in the sector is naive. There are clear situations in which AI can help inform stakeholders, but we require a new understanding of how to design and interact with AI.

  More specifically, what is needed is a hybrid solution that combines the experts with the machine. Such a methodology can help us develop this approach and ensure that any solutions are appropriate for the context and address the users’ specific needs. In each and every context, we need to define a goal for the technology to solve. An algorithm should produce reliable data that will support people running operations, not replace them. With this in mind, solutions should not simply be a concept, but real tools enabling end-users to focus on tasks that require human intelligence (i.e. analysis, choices, etc).

• Misconception 2: AI will replace human labour
  AI interventions are intended to minimise human effort on tasks that can be streamlined, allowing for human skills and interactions to be more meaningfully focused. For example, when we look at the applications of AI in healthcare to date, such as clinical decision support, this is intended to reduce the clinician’s administrative burden and allow for increased face time with patients.

  There is an increasing understanding in many sectors that humans will not be replaced by AI but rather supplemented by it. However, it may also be speculated that those who choose to explore and leverage AI applications within this frame may just replace those who refuse to consider AI optimisations. To work effectively, AI requires proficient data managers and data scientists to feed data into the algorithm and maintain it in addition to various other roles to validate and translate AI insights into tangible practices.

  To this end, AI works best when:

  1. A. Common-sense is not a requirement, and the answers are unambiguous. AI can outperform humans on some complex tasks, but it performs poorly on some others that humans take for granted (e.g. AI cannot answer questions such as ‘How can you tell if my carton of milk is full?’); AI works best in ‘black or white’ binary scenarios. Such as ‘Is my carton of milk is full?’

  2. B. Detailed explanations of results are not needed. It can be extremely hard to offer a satisfactory answer to the question ‘Why did the machine give this answer?’ When dealing in unstable contexts or with vulnerable populations, this lack of accountability can have serious implications.

• Misconception 3: AI can solve any problem
  The success of AI depends on the quality of the dataset. Before an algorithm can operate on a dataset, the data needs to be processed and cleaned so that the results produced by the algorithm are not skewed or imprecise.

  Cleaning data is laborious. Given the value of clean and structured data, an important design choice for a socio-technical system is how many resources to use up-front to ensure that the inflow of data is structured and stored appropriately. To build a high-quality database, the platform should incentivise users to input data abundantly and in the correct formats. It should have data managers to monitor the process and clean the database. With a pre-existing high-quality database, solutions can be adapted to harness the power of AI, but this option involves costs and design choices at the very beginning of the project/program.

How AI can add value the humanitarian sector

In the humanitarian sector, there are some specific areas already where AI may be harnessed for specific tasks to add value. These are:

• Predictive Analytics - Predictive models of humanitarian crisis (such as: migration patterns during conflicts, famines, epidemics, or natural disasters) allow for early preparation. These predictive analyses may also be leveraged for the improvement of workflows and the optimisation of supply chains. The Forced Migration Forecast developed by a team of scientist at the university of Brunel in London is an example of this.

The Forced Migration Podcast

• Image recognition - Used to identify disaster zones from satellite or drone data. Something currently being used by the Humanitarian OpenStreetMap Team.

• Natural language processing - Semantic models allow for complex searches for navigating information. This may be performed through: chatbot style interactions, speech recognition, transcription, and translation for various communication tasks. These tools can be rolled out to help people adapt to new contexts (i.e. due to forced migration) and better understand how to navigate their new surroundings and services.

• Adaptive web design - Sites that offer personalised interactions based on users’ behaviour. Allowing, for instance, prioritisation of the most relevant information for that user.

Smoothing the implementation of ai in humanitarian contexts

Humanitarian organisations need to invest in educating their personnel on relevant points of progress in other sectors. In any organisation, one of the major limiting factors of adopting AI is identifying expertise that can determine if AI is actually the right answer to a specific challenge. Education and knowledge transfer should happen frequently and bring the basic expertise to the workforce; enabling all staff members to understand how to, for instance, input data and set up data structures etc. With this in place it is possible to get the most return of investment from the technology application to a certain context or problem.

Also, it is very important to educate staff to engage with what has been tested — successfully or not — in order to learn from the others. It is very important to share lessons learned and new reports and publications should to be digested in order to stay up to date. For example the essay published by UNHCR and this publication written by IFC, a member of World Bank Group.

Given how resource-intensive creating AI solutions is — from data sourcing and cleaning, to validating the output — obtaining organisational buy-in with proper consideration of its risks and benefits is currently rare in the humanitarian sector. We must acknowledge that AI is still at a relatively nascent stage and a plethora of potential applications are still being tested and validated; mostly in high-income or private sector contexts. However, it is expanding in the humanitarian sector and low income contexts… albeit a little slowly.

One key final consideration for digital humanitarian projects and actors today is to focus on building large datasets that are clean and structured so that AI models could be trained on the data in the future. Mobile phones and other devices for data collection are already key components in humanitarian response and international development programs — offering a potential ready-to-use goldmine of insights, if structured correctly. Adding algorithms and automation to this well-structured data, allows for the fast identification of patterns in the data that can inform decisions and real-time analysis for a greater impact for your operations in the field.

ABOUT lucie AND OUTSIGHT INTERNATIONAL

Lucie studied at the Université Catholique de Louvain in Belgium. For the past three years, she has managed the MSF REACH project — researching AI and machine learning in the humanitarian context. More widely, she focuses on digital implementation for the development and humanitarian sector. She believes that digital solutions can be harnessed in order to increase the efficiency of the humanitarian sector and the service provisions for the most vulnerable.

Outsight International provides services to the humanitarian and development sector in an efficient and agile way. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with Lucie and the Outsight team, please get in touch or follow us on LinkedIn for regular updates.

Implementing cargo drones in Africa: Some lessons from the field

Denise (in the yellow vest) with the pilots during the Lake Kivu Challenge in February 2020.

My experience working in the cargo drone field

My journey with drones began in 2015, working with FSD on a dream project funded by the European Union Humanitarian Aid. The objective was to find out how we can use drones for anything anywhere in humanitarian settings. Given a blank slate and the task to find the most effective and promising applications, there was no better way to find out than to try.

Within the two years we implemented mapping projects in the Tadjik Pamir Mountains, Switzerland and Malawi, and deployed drones as part of an emergency simulation in France. During those years I also began first discussions with large medical humanitarian organisations to develop pilot implementation for cargo drone transport of diagnostic samples in hard-to-reach places. After having spoken to many tech providers, carefully weighing the pros and cons we decided that at that stage in 2016, the technology was still too early in its development to responsibly take into a real-world setting.

In 2017, I began a deep dive into cargo drone operations, working on the Lake Victoria Challenge in Tanzania, which was followed by the African Drone Forum Lake Kivu Challenge in Rwanda in early 2020. During those years, I worked closely with nine cargo drone companies to enable their flying operations. Seeing the industry evolve over the years, I am confident that we are ready to take this to the field in 2020 and 2021.

Where are we now?

Zipline is the only company so far that has been able to provide cargo drone services at scale – operating on the continent with some impressive successes to date. The initial business model is based on delivering transfusion blood. Today, four years after Zipline’s first delivery flight in Rwanda, the nation is on track to shift its entire transfusion blood supply to drone logistics reaching every part of the country in less than an hour upon receipt of the order. 

Medical deliveries and other development objectives remain at the core of the drive towards enabling a thriving drone industry in Africa, and the recent African Drone Forum has confirmed the appetite and commitment towards these objectives. Following the success of Zipline, the industry has been busy rising to the challenge.

The global drone logistics and transportation market is forecast to reach 11.2 billion USD globally by 2022, yet only a fraction of this market growth is forecast to take place in Africa. This is due to a combination of factors, but particularly that implementing high-tech solutions in remote settings has many risks and challenges. And there is not much experience or guidance out there in how to navigate these.

The following are some key lessons I’ve learnt over the past five years working in the sector, coordinating between industry, donors and governments.

What to look for in a cargo drone delivery company

Four key considerations I advise clients to consider seriously before working with any technology are the following:

• A demonstrated commitment to safety. This cannot be over-emphasised and should be one of the first considerations. Technical documentation, operations manuals, flight and maintenance reports are crucial to build a track record. To be absolutely sure, it can be beneficial to solicit the advice of one or several subject matters experts. This procurement guide provides a helpful checklist of documentation to request when looking to hire a cargo drone company.

• Technical specifications and business model appropriateness. Do the technology specs and business model align with what is required for the use case being addressed? Is the company committed to building technology for cargo delivery? Can the application accommodate African business models? I still encounter companies that have a primary focus in data collection (mapping and monitoring) but say they can easily also deliver cargo. That is a red flag for me. There are significant (technical) differences implementing these two applications and cargo drone work deserves full attention to its specific challenges.

• Range. Bigger is not always better but when flying drones in the expanses of the African continent, range can make the difference. Studies recently published in the Lancet show that drone logistics work in the African context can only compete with alternatives — namely motorcycles and other ground vehicles — in terms of cost effectiveness starting from a minimum range of 60-65 km both in routine and emergency scenarios. All the companies on our list can cover at least this minimum range. Many pure copter designs have a range limit of 20km and are not suitable for typical African use cases beyond urban deliveries. 

• Willingness and ability to adapt. When implementing projects, delays and setbacks are to be expected. We are charting very new territory. Building relationships based on trust and openness will help companies better understand their customers while implementing organisations can get the most out of their investments through valuable lessons-learned. 

Volansi getting ready for take-off.

Who’s doing what?

Here are some of the most promising drone tech providers I have been keeping an eye on — besides Zipline of course: 

• Avy - This Dutch company adheres fiercely to its “drones for good” slogan, keeping to a strict civilian focus. Avy’s Aera aircraft is being prepared to deliver medicines in the Netherlands within a year — circumventing traffic for essential and high priority deliveries. The aircraft is small and light with a payload capacity of around 1 kilogram — just enough for these high-value products. However, like many of their competitors it is likely that a larger model is in the making. Avy is no stranger to the African continent, having provided surveillance support for anti-poaching and park management activities.

• Phoenix Wings - Their Manta Ray aircraft is a heavy lifter among the small electric cargo drones. The aircraft was designed around the cargo and that thinking has paid off beautifully: the Manta Ray SR easily carries 7 kilograms in a 30 litre cargo compartment with a range extending more than 60 kilometers. Its signature turn into the wind upon take off is reminiscent of a spaceship in flight. Upon landing at the delivery location, the cargo compartment is released automatically.

• RigiTech - This Swiss company has an impressive track record within their management. Two of its founders were part of Sensefly’s early start-up team before moving into the cargo drone business. The third co-founder is an MSF veteran having conducted medical delivery operations in Papua New Guinea as early as 2015. RigiTech’s business model centers around developing a complete hardware and software platform for cargo logistics.

• Swoop Aero – This fast-rising Australian start-up has been flying vaccines for UNICEF and is about to start major operations in the DRC. From the outside, the aircraft looks less shiny than some of the competition, but the fundamentals are designed for safety, reliability and durability, which has proven to be a winning strategy. Swoop Aero is committed to expanding healthcare access through their logistics services and they are quickly establishing themselves as a market leader.

• Vayu – Vayu has settled on a long-range design that is capable of several hundred kilometers (up to 800 kilometers to be precise) of flight. Vayu provide the only gasoline-powered aircraft in this list, and have been involved with the development sector projects for years, striving to make solutions that work. In some environments the use of fuel can be justified as it greatly extends range compared to battery powered systems.  

• Volansi – Volansi is another Silicon Valley backed start-up with an impressive line-up, having logged experience in both North America and Africa. The company participated at the African Drone Forum Lake Kivu Challenge — and demonstrated solid tech and a highly professional team. A new aircraft has been in development, and will be launched shortly, so expect to hear a lot more from Volansi in the near future. 

• Wingcopter – Known for their fine German engineering and for having produced the fastest civilian drone (fast = stable flight in the cargo drone world), Wingcopter has made recent headlines with a strategic partnership with UPS. Wingcopter are also veterans when it comes to operating in Africa and other rural settings, among others delivering vaccines with UNICEF in Vanuatu and delivering health supplies in Tanzania. Wingcopter have adapted quickly to their customers’ needs by developing the winch system that lowers their cargo without the need of landing the drone.

A Wingcopter aircraft winching down a cargo box.

Implementing cargo drones in development

Implementing the use of cargo drones for logistics is a complex matter that requires careful choreographing. Safety (and security) management will take much attention and time. This includes: risk assessments; implementing risk mitigations; route planning; applying for activity permits and potential certification; air traffic management; and coordination. In addition, other aspects need to be managed: procurement; use case analysis; perceptions; waste and other environmental concerns; insurance; import and export; operations; skills development; regulations; perceptions; (data) protection; cost-benefit analyses; and media — among others. Since in many environments the cost-benefit is not yet fully established, future implementations should also be designed around collecting quality data. Cost-benefit analyses will require data on major cost drivers of drone operations such as failure rates under various operational conditions, down-time due to weather conditions and fixed costs for maintenance and running the operation.

To pull so many aspects together, whilst also dealing with multiple stakeholders with different interests, requires significant expertise, diplomacy and technical knowledge. Although, complex, I have seen that it is possible to bring all the pieces together efficiently and effectively. Any new implementations must build on the — so far — established best practices and lessens learned. This will help elevate cargo drones to their full potential in Africa.

ABOUT denise soesilo AND OUTSIGHT INTERNATIONAL

Denise is one of the Co-founders of Outsight. She is a world-renowned expert in unmanned aerial system (UAS) use in humanitarian and development settings, and in operationalising clean technologies. She has worked with the World Bank and other development, humanitarian and UN agencies — advising on the application and implementation of space-based systems and UAS technologies in humanitarian operations. Denise was directing the flying operations of the African Drone Forum. Denise has led the European Union Humanitarian Aid innovation grant for the implementation of drones in humanitarian action globally and has authored several leading publications on UAS in development and humanitarian action.

Outsight International provides services to the humanitarian and development sector in an efficient and agile way. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with Denise and the Outsight team, please get in touch or follow us on LinkedIn for regular updates.

Covid-19 and mental health: An exploding global burden

An increase in the already substantial burden of disease related to mental health will put a strain on healthcare systems at risk of collapsing under the pressure of the Covid-19 outbreak.

As the world grapples with the Covid-19 outbreak, rushing to “flatten the curve” and mitigate the risks of collapsing health systems, it is imperative we turn our attention to the mental health implications of this pandemic. Many proactive measures put in place around the world have underestimated the importance of incorporating MHPSS (mental health and psychosocial support) as an essential component of any emergency response. In a recently released report, the Inter-Agency Standing Committee (IASC) for Mental Health and Psychosocial Support in Emergency Settings advise that Mental Health and Psychosocial Support (MHPSS) “should be a core component of any public health response.” The fear of being infected can not only lead to severe anxiety, but also cause individuals to avoid seeking healthcare to prevent being exposed to the virus – or, paradoxically – to present too readily at emergency centres without medical cause. As noted in an article recently published in the British Medical journal, 

“Surges of such low risk patients are often precipitated by high levels of anxiety, leading patients to identify, catastrophise, and seek help for symptoms that might otherwise have prompted little concern, and leading clinicians to refer patients to hospital at the first sign of a mild symptom developing.”

Considering the mental health impact is essential: 

• The baseline prevalence rates of mental health disorders – before the outbreak – already constitute a significant portion of the global burden of disease. 

• Under the current climate of fear, enforced social isolation, and economic devastation, mental health difficulties may be expected to increase sharply.

• This burden will have a substantial impact on already over-stretched health systems.

Baseline prevalence: the substantial global burden of mental health diseases 

The Institute for Health Metrics and Evaluation and reported in their flagship Global Burden of Disease study estimates that 970 million people lived with a mental health or substance abuse disorder in 2017. This represents a staggering 1 in 7 people (15%) globally. The ‘disease burden‘ – measured in Disability-Adjusted Life Years (DALYs) — considers not only the mortality associated with a disorder —, but also years lived with disability or health burden. Of this, mental health disorders accounted for around 5% of the global disease burden when measured in 2017 (up to 10% in several countries). We may consider these to be conservative estimates. Many difficulties go under-reported and undetected, particularly in the developing world where there is typically less awareness and more stigma around mental health issues, and fewer resources at hand to identify and treat those in need.

Mental health from a socio-ecological perspective 

Mental health disorders are complex. They take many forms. Difficulties may range from depression, anxiety, PTSD, and schizophrenia — through to substance abuse disorders. They are not only located at the level of the individual. They are increasingly understood as unfolding within the context of systems of relationships which constitute our socio-cultural environment. They are exacerbated by harsh living conditions, the erosion of mutual social support mechanisms, limited access to basic needs and services and lack of opportunities for maintaining livelihoods and education. In recent years, there has indeed been a burgeoning of theoretical models for understanding mental health disorders that situates individuals’ mental health sequelae and recovery within interpersonal, political, and social context. This ecological perspective similarly incorporates a “resource perspective”, which assumes that human communities evolve adaptively. We are deeply embedded in complex and dynamic social contexts. Equally, symptom severity is not static but fluid and changes according to a continuum of pathological reactions. 

Simply put, the social and economic environment has a fundamental role to play in mental health. We need to pay attention to the various, context-dependent, long-term, and complex social, political, and economic measures affecting the mental health of populations. Given the importance of the socio-cultural and economic environment on mental health, the anxiety, economic impact, and social isolation brought about by the Covid-19 pandemic can only exacerbate the burden. 

The mental health impact of Covid-19

Some of the key factors related to the Covid-19 outbreak and its influence on mental health include:

• Boredom linked to quarantine: risks exacerbating most mental health difficulties, including substance use disorders, anxiety, and depression.

• Frustration, anger, and powerlessness linked to quarantine: risks exacerbating domestic violence, sexual abuse and violence and childhood abuse – further linked to the increased risk of substance use disorders as a maladaptive coping mechanism. In China and Italy, cases of domestic violence have increased. Several organisations preventing violence against women and feminist collectives are sounding the alarm.   

• Social isolation and loneliness: risks exacerbating most mental health conditions, notably depression, anxiety, and substance use.

• Fear: risks exacerbating anxiety disorders, including Obsessive Compulsive Disorder and PTSD. Feeling overwhelmed by anxiety can make it difficult to cope with the new lifestyle changes that are required, or may lead to people using unhealthy ways of coping, such as substance use. Another risk related to fear is an increase in psychosomatic reactions, in other words, physical manifestations of psychological suffering (sometimes understood as conversion disorder). This again could result in an increased number of patients attending emergency centres. 

• Financial loss: risks exacerbating most mental health difficulties, including substance use disorders, anxiety, and depression. 

We have little evidence on the mental health impact of quarantine on individuals. We have even less on the impact of a global enforced quarantine on entire communities. However, this rapid review recently published in the Lancet “suggests that the psychological impact of quarantine is wide-ranging, substantial, and can be long-lasting.” Most of the studies examined in this meta-review reported negative psychological effects including post-traumatic stress symptoms, confusion, and anger. Stressors highlighted across studies included longer quarantine duration, infection fears, frustration, boredom, inadequate supplies, inadequate information, financial loss, and stigma. 

We need to be concerned for the individuals affected and for their families and communities. Importantly, we also need to be concerned for the healthcare systems at risk of collapse globally in the face of increased mental health difficulties. 

The impact on frontline workers 

A recent article published in the Lancet, exploring the lessons learnt on MHPSS in China, stated that:

“Under strict infection measures, non-essential personnel such as clinical psychiatrists, psychologists, and mental health social workers, are strongly discouraged from entering isolation wards for patients with COVID-19. Therefore, frontline health-care workers become the main personnel providing psychological interventions to patients in hospitals.”

This is a triple burden, with negatively reinforcing feedback mechanisms: 

• Healthcare workers “on the frontline” of the outbreak are particularly at risk of experiencing mental health difficulties themselves. The large body of literature on medical emergency workers in general attests to the high prevalence rates of mental health difficulties related to the stress of the job. This refers both to the nature and the amount of work, as well as the exposure to human tragedy, increasing the risk of secondary or vicarious trauma. A recently published article in Brain, Behaviour and Immunity confirms the significantly high levels of vicarious trauma among frontline workers facing the Covid-19 outbreak in China.   

• Healthcare workers are also asked to take on the double task of acting as both medical AND mental health care workers. Not necessarily within their scope of practice, they may not be equipped with the necessary tools and resources, both professional and psychological, to handle this extra load.

• Healthcare workers may see an increase in the number of people presenting with mental health difficulties. There is a significant risk of the global burden of disease related to mental health difficulties increasing. This is not only necessary in relation to the virus itself (for example, anxieties and fears around contracting the illness), but more generally related to mental health conditions globally being exacerbated by current conditions.

Physical distancing, social solidarity: moving forward together 

The crisis has catalysed countless creative examples of social solidarity, mutual aid, encouragement, and support. As global mental health experts have noted in a recent report:

“We need to encourage physical distancing along with social solidarity. And any MHPSS intervention during this time needs to include key psychosocial principles, including hope, safety, calm, social connectedness and self- and community efficacy.”

• Healthcare workers need to be armed with adequate MHPSS strategy integrated into their response activities and the systems in which they work

• Patients in quarantine should have access to mental healthcare 

• Mental health professionals should be resourced and equipped to offer support online/via tele-therapy – and paraprofessionals (such as community healthcare workers) should be trained and equipped to join them in picking up this load. Online mental health services have been successfully implemented in response to the outbreak in China, as confirmed in this report in the Lancet. 

By mapping existing MHPSS service providers and institutions, efforts can be pooled to address the global burden of mental health disorders: a substantial burden projected only to increase.

About Gail Womersley and Outsight International

Gail Womersley is based at the University of Neuchâtel, where she lectures BA and MA students in sociocultural psychology. She has worked for over ten years as a clinical psychologist and researcher with displaced communities in the Central African Republic, the Democratic Republic of Congo, Greece, Iraq, Israel, the Philippines, South Africa, South Sudan, the Ukraine, and Zimbabwe. Her recent publications include the book: “Trauma Without Borders: Working with Adversity and Resilience Among Displaced Populations” (to be published by Springer in 2021).

Outsight International provides services to the humanitarian and development sector in an efficient and agile way. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with Gail and the Outsight team, please get in touch or follow us on LinkedIn for regular updates.

Mastering the art of hard problems (and avoiding the rush to easy solutions)

Forward looking organisations take the need for innovation seriously, seeking original ideas that help avoid disruptive threats and pursue original opportunities. Unfortunately, these much needed initiatives often fail to deliver on their promise of impactful change.

There are a number of common stumbling blocks. Good ideas may fail to earn the required investment, while even those that are funded find that they are unable to muster on-the-ground support necessary to drive adoption. Unexpected barriers, tangled dependencies, and ongoing change in the surrounding environment can also derail the innovator’s plans. Perhaps the most disappointing projects, are those that succeed only by staking out a small vision, taking incremental steps that make little impact on future success.

Surprisingly, these varied failures are seldom driven by a team’s incompetence or lack of creative imagination. Instead, they are more often tied to a specific, but crucial, step that is missed in the creative process. In a team’s rush to embrace a solution, they fail to first immerse themselves in the full messiness of the problem that underlies an important challenges.

Rushing to Design

Innovation typically begins with lots of energy. Well trained innovators listen attentively to those who are immersed in the area where change is needed. They use these insights to identify a good idea and then quickly move forward with design decisions that are informed by user engagement (option #1 on the diagram). They fail fast and learn quickly.

This approach drives directly to a usable solution, yet a strong case must be made for inserting an additional step early in the process. Even a fast moving innovator can benefit from taking time to understand the root cause of the problem that is behind their User’s need (option #2 on the diagram). This insight helps inform good design decisions. Still, there are limits to this targeted look back. Focusing only on the specific problem behind a user’s need often leaves the original vision unchallenged. The innovator may do a slightly better job in design, but still rushes ahead with the same fundamental solution.

Innovation teams may justifiably feel that they are doing a good job when they use these first two strategies. Yet, these seemingly well tested practices still fall short.

The unrecognised challenge is that neither genuinely important problems nor truly impactful solutions are as simple as they appear in this rush to design. In real world systems, diverse individuals and organisations are tangled together, so that even simple activities are the result of dynamic collaborations involving varied skills, resources, and motivations.

Seeing Beyond the Keyhole

This fact requires a non-trivial addition to conventional fast moving innovation methodologies. Before rushing forward to solution design, there is a need to pause and intentionally look back at the messy systems that are at the heart of the problem. (#3 on the diagram)

Understanding these systems demands a fundamentally different way of thinking. While a User’s specific challenge may be quite real, it is just a fraction of a much bigger picture. When an innovator focuses only on a specific need, it is as if they stare at the world through a keyhole. What they see is true, but it is hardly a complete view of what is inside the room.

This small actionable view comes at a cost. The unobserved complexity and challenges that lie outside the User’s and the innovator’s immediate view become stumbling blocks. Unrecognised complexity undermines business cases, casts doubt among potential stakeholders and leaves innovators surprised and unprepared for barriers and setbacks.

Innovators fail when they assume the world is simpler than it is. Of course this isn’t always the case. If an idea is small enough, or already thoroughly understood, it is possible to confidently make a small tweak or addition based on a narrow view of a problem and solution.

Yet, when innovators ambitiously seek to drive more substantive and sustainable change, it is no longer possible to assume that important problems can be addressed with simple ideas. To be truly impactful, the solution must embrace the true complexity of the problem and be suited to the scale of the challenge.

The embrace of the real world’s messiness begins by letting go of the original idea. Instead of supporting a preordained path to addressing a challenge, the user’s need can be treated as a symptom of the challenges found in complex real world systems. This broad-based, systems perspective looks at the diverse actors involved and seeks to understand how the world works. In real world systems, if something good or bad happens it is because of the way these tangled webs of actors, interactions and incentives connect. Understanding the rich complexity of these systems opens the door to a far more sophisticated view of the challenges and possible solutions.

The Power of Embracing Hard Problems

Investing time and effort in building a big picture view of a problem requires significant investment. This can be difficult to embrace. Just at the moment when everyone is excited to drive forward with realising the solution, the journey seems to take an about-face. Sponsors and participants in the creative effort may worry that the project is becoming mired in “analysis paralysis”. Fortunately, this thinking does not have to be bogged down in a never ending swamp of details. Rather, the effort should look down from above, doing just enough big picture work to see the important patterns of the system and its actors. This big picture systems view is broad but not necessarily deep.

With a top down view of the systems behind the problem, it possible to leverage four powerful creative capabilities:

1. Claim Bigger Problems – A bigger picture of the challenge naturally encourages broader thinking about the nature of the challenge and the scope of the solution. A particular User may have identified a specific issue, but it is far more likely that making a substantial change that impacts the future will require addressing a more substantial version of the problem.

   Stretching the problem can help the innovator to strengthen their case for change. Smart organisational leaders naturally guide their investments to big urgent problems. Stepping back and understanding the full scope of the challenge allows the innovator to claim a bigger more compelling problem.

2. Design More Sophisticated Solutions – It’s easy for an Innovator to look naive when they propose a simple solution to genuinely hard problems. Seasoned experts in the field quickly identify shortcomings, challenge the idea, and withdraw their support, often taking others with them.

   While an individual User may see a particular aspect of a challenge, working with system’s view makes it possible to see the many interconnected elements that are in play. Understanding the complexity of the problem makes it possible to recognise dependencies, trade-offs, and barriers that are only apparent when the entire system is considered. The innovator can then propose a sophisticated solution that rises to those challenges.

3. Tap Complexity’s Bigger Toolkit – There are many moving parts and dynamic interactions in a real-world system. Understanding this complexity can be a challenge, but it also offers a creative gold mine of resources and capabilities that can be used to build solutions.

   Seeing a broad-systems view offers the use of a big toolkit that includes varied actors, capabilities, technologies, and existing resources. These resources can be reassembled in new and creative ways, building powerful solutions without starting from scratch. Shaping solutions with this holistic view also allows innovators to take advantage of synergies and emergent behaviours which are only visible at a systems level.

4. Enable Creative Agility – The final advantage of beginning with a systems view of the problem is tied to the actual development of the idea. As innovations become bigger and more ambitious, the more they face unknowns and uncertainty. It’s simply not possible to plan a large creative change in advance.

   Powerful solutions are not just about coding a piece of technology and releasing it. High impact innovations require a wide variety of people, institutions, and technologies to evolve together, progressively transforming the current real-world systems.

   At any point on this journey an unexpected barrier may rise up to derail the effort. The best way for innovators to respond is to pivot and adjust as they go. Rooting an innovation in a broad understanding of the problem, rather than a specific solution, gives the innovator the flexibility to nimbly adjust their vision. When necessary, they can take a significantly different approach the solution, because they can see alternative ways to solve the underlying problem.

A Worthwhile Creative Discipline

Because a systems understanding of the problem is so useful throughout the innovation lifecycle, it is important to begin thinking about it early in the creative effort. This is not a bit of busy work that delays the real job of the innovator. While rushing forward into detailed design and implementation may feel tangible and productive, it is in fact an indulgence that borders on creative negligence.

Taking the time to think deeply about the messiness and deeper challenges, when everyone is anxious to drive quickly forward, can be a hard sell. Nonetheless the creative payoff is substantial. Building an early understanding of the system behind the problem makes it far more likely that the idea will eventually be big enough to matter and will survive the winding journey to adoption.

About Dan and Outsight International

Dan McClure has spent over three decades working on the challenge of disruptive systems innovation. He has advised global commercial firms, public sector agencies, and international non-profits in support of their ambitious efforts to imagine and execute agile systems level innovation.

Outsight International is an organisation specialised in providing services to the humanitarian and development sector in an efficient and agile way. Outsight International builds on the range of expertise offered by a network of Associates in order to deliver quality results adapted to the specific tasks at hand. If you’d like to discuss working with Dan and the Outsight team, please get in touch or follow us on LinkedIn for regular updates.