Ken Frantz was flipping through a copy of National Geographic in 2001 and an image stopped him in his tracks. Men dangling high in the air, using a rudimentary ropes system to dangerously cross a river—a broken bridge crumbling on either side of them and the Blue Nile in Ethiopia rushing below.  

As the owner of a construction company, Frantz knew that the problem was solvable. 

It took Frantz and his team just three months to get that bridge rebuilt. Now, more than 20 years and nearly 500 bridges later, that mindset—seeing big challenges like rural isolation and poverty as solvable—fuels a new data-driven chapter for Bridges to Prosperity (B2P), a nonprofit that aims to meet an estimated global demand for 100,000 bridges serving 250 million people—one bridge at a time.

The Challenge 

Rural isolation is a root cause of poverty.  

Access to nutritious food, education, and health care—powerful social determinants of health—all depend on sufficient transportation infrastructure to get to markets, schools, and hospitals. Without access to these critical resources, health and economic equity gaps widen. People risk their lives to travel unsafe routes or go without altogether.  

Globally, B2P’s monitoring and evaluation program has identified an estimated 1.3 million people who do not have safe access to these resources, threatening their lives and livelihoods. Yet Abbie Noriega, the Chief Impact Officer for B2P, says so many people—even those working in global development and government—are unaware of the scope of the issue. 

One reason the problem is not more well known is a lack of reliable data. 

“For the most part, it just doesn’t exist,” Noriega said. “No governments in the world understand and have documented well the infrastructure gap in the rural context. We are missing data as simple as rivers and roads for a huge portion of the world.” 

The data may not yet exist, but the case for impact is strong.  

“We construct tangible bridges. When I present a picture on my phone and say, ‘Here is the bridge,’ and I see the realization dawn on people’s faces ” said Global Advocacy and Partnerships Director Eniola Mafe-Abaga. “In an era obsessed with groundbreaking innovations and complex ‘blockchain/data/disruptive technologies,’ our work stands out as a straightforward, evidence-backed solution with the power to transform lives.”

The Solution 

Twenty-plus years ago, Ken Frantz saw a simple problem with a simple solution. So, he rallied his network, and they built a bridge. And then another, and then another.  

B2P today has trail bridges in 21 countries.  

For the organization’s first decade, the team focused on mastering the technical challenges associated with securing materials and labor and transporting them safely in some of the most remote, and often geographically challenging, environments in the world. They are now masters at their craft, and it typically takes just eight weeks to construct a bridge. 

With the practical execution perfected, B2P’s focus has increasingly shifted to maximizing cost efficiency and durability, building greater trust with governments and community partners, and—now, more than ever—building bridges that are sustainable and climate resilient. 

Equally important is advocacy.  

“Redirecting even one percent of global infrastructure spending toward trail bridges could be transformatives, would be transformative,” Mafe-Abaga said. “The evidence for their impact is robust. Our current focus is on disseminating this knowledge to those who can implement these projects broadly. The ultimate goal is for governments to be resourced, willing, and able to sustainably construct these bridges for their communities.” 

Building that kind of widespread public will and demand requires better data, an area in which B2P has experienced significant growth since its early days.  

Before B2P sets out to build a new bridge, prospective locations are identified through robust needs assessments. B2P connects with national governments to begin to build support and gain permission. Then they train local needs assessors to conduct social and technical assessments and convene public meetings and focus groups.

Working closely with the community, these assessors compile as much data as possible, from the disparity in heights between banks to the number of past mortalities on site. Catchment surveys help them understand how people are using crossings, both before and after a new bridge has been constructed. 

“It’s a much more community-driven, locally-driven process. You can never replace local knowledge,” Noriega said.  

That information is added to a centralized, growing database of global information that includes coordinates, photographs, and information on a massive network of partners on the ground. B2P sees significant opportunities ahead for how geo-mapping technologies and AI can accelerate their work and are in the beta testing phase of Fika Map, a suite of remote analysis tools that use machine learning to locate where access is most beneficial. 

The tool has the power to make B2P solutions more scalable and replicable than B2P’s founder could have ever imagined.  

In the meantime, they continue to solve major challenges for the communities they serve. According to B2P, easier access to health care leads to an 18 percent increase in care visits. There is a 30 percent increase in labor market income and a 75 percent increase in farm profits when people have year-round access to the local marketplaces. Twelve percent more children enroll when they can access school.  

B2P’s data also shows that social connection is the top reason that rural communities are crossing their bridges. 

“A connected community is a resilient community,” Noriega said. “It’s one of those things that makes life worth living.”

The Takeaway 

B2P is a bit of an outlier in the nonprofit field. They don’t fit neatly into the category of health care, education, climate, or gender, but the work they do influences all those dimensions of life.  

“This is one of the best investments you can make, dollar for dollar, in poverty alleviation,” Noriega said. 

Everyone at B2P has a personal story to tell about their experiences visiting one of their bridges. For Noriega, she was at a bridge site in Haiti when she noticed that everyone she saw crossing while carrying something—a child, cargo, an animal pulling a cart—was a woman. In Rwanda, Mafe-Abaga watched a young boy, maybe 3 years old, running across the bridge, and she was struck by the realization that the bridge would exist and serve his community for the entirety of his life.  

Caitlin McWhorter, the Director of Marketing and Communications, has been to three or four bridges in Ethiopia and returns home each time proud and excited to tell her daughters about the work she’s helping to advance. 

“Being able to talk to my kids about that makes me so proud,” she said. “Without these bridges, kids can’t go to school. Women can’t get to hospitals to have a baby. It’s a profound feeling, getting to see how this work—this simple intervention—is actually life-changing.” 

A simple intervention with an outsized impact and a goal that the B2P team believes is achievable if they continue to do what they do best, while using data to accelerate the adoption and replicability of trail bridges around the world.  

“There are so many complicated problems that are going to take centuries, millennia, to solve. The one we’re trying to solve is actually not one of them,” Noriega said. “It feels like a rare opportunity to say I’m working on something and I’ll probably see pretty massive global results in my lifetime if we do this right.” 

The post Bridges to Prosperity Makes Big Problems Solvable appeared first on data.org.

Ishango.ai bridges the gap between the demand for data skills and the availability of a robust workforce by leveraging the power of remote work, enabling international companies to tap into the talent pool in Africa without contributing to what’s referred to as the “brain drain” on the continent.

The Challenge

In 2020, as the COVID-19 pandemic raged, Eunice Baguma Ball and Naveed Ratansi talked about silver linings. Amid so much fear, uncertainty, and sadness, were there any bright spots? New opportunities? Ways to accelerate progress in the face of such immense challenges? 

Eunice had worked in the African tech ecosystem for over 12 years while Naveed had founded multiple education companies and had extensive commercial experience. Fascinated with the growth of remote working, they speculated how it could change work in Africa, which was experiencing significant emigration of highly skilled professionals to other countries, seeking better opportunities and improved living conditions. 

And that’s when it hit them. What if they could create jobs, foster local skills development, and reverse the brain drain in Africa by leveraging the new boom in remote work? 

“We see it firsthand all the time,” said Eunice Baguma Ball, Ishango.ai Co-Founder and Head of Operations. “Many of our friends have attained amazing degrees and qualifications but struggle to find opportunities, and the reality is that there are not enough jobs to accommodate the 10–12 million individuals entering the workforce each year.” 

Eunice and fellow Inshango.ai co-founders Naveed Ratansi and Oliver Angelil understood that one of the answers to bridging this gap could be remote working. With so many companies already working in a distributed manner around the globe, they set out to create incentives for professionals to stay and contribute to their home countries’ growth while meeting the needs of a high-demand market: data and technology. 

“We knew we could not only be leaders in this new space but that we could make an impact on so many young people who were committed to their communities but were faced with economic hardship if they stayed. It was a really exciting time,” said Ball. 

The Solution

Ishango.ai offers global companies the ability to access an untapped talent pool: African data scientists and data engineers. And those data scientists and engineers are put through a robust development program that includes a stipend, mentors from global institutions, and soft-skills training to take their careers to the next level.

“We knew we were going to face two significant challenges,” shared Ball. First, the company would need to change the narrative that outsourcing any degree of data talent must be pulled from countries outside of Africa. “We had to not only convince prospective clients that they could find high-skilled data talent as a service but also that the talent could come from Africa.”

Second, said Ball, was ensuring that the talent they were offering was not only highly skilled technically but that individuals had key soft skills, such as communication, critical thinking, and cross-team management and collaboration — all crucial when working with multicultural and virtual teams. 

“How do you convince an Australian company that they can work with two data scientists in Ghana and that it will not only be cost-effective, it will actually result in greater outcomes?” said Courage Seyram Wemegah, Ishango.ai Program Manager. “When we first started out, we would show them the rigorous process of how we find and develop our talent. Now we use  case studies with data to illustrate how well our model works.”   

Ishango.ai recruits candidates through application open calls on its website and social media. Candidates are invited to take a coding assessment test and complete an interview with a senior team member. Successful candidates are then trained, matched with a company, and assigned a team and a senior data scientist as a mentor.

“Developing strong data scientist professionals extends beyond technical prowess,” said Wemegah. “Ishango.ai is looking for a combination of technical expertise alongside the ability to learn and adapt to different working environments. Our ongoing mentorship and training program smooths out any challenges around cultural fluency, soft skills, and most importantly, communication.”

Within the first eight weeks, the program prepares each participant to provide a presentation about their projects and key learnings for the company they’re working for. After this presentation, they could be offered a long-term contract.

Ethel Elikem Mensah, a participant in a recent Data Science Program cohort, said the training went far beyond soft and hard skills. “I developed a profound understanding of the impact data science can have in transforming businesses and driving social change,” she noted. “It transformed my career and my perspective on the power of data science.”

The Takeaway

Today, Ishango.ai data scientists have delivered projects across sectors such as finance, e-commerce, healthcare, agriculture, and industrial engineering for companies from around the world, including the US, Australia, Switzerland, and the UK.

“The data science program allows international companies to see the high return on investment that working with African data talent provides,” said Ball, “and many of them end up extending their contract. In fact, the project that Ethel is working on now is from 2021.”

Looking ahead, Ishango.ai is expanding its marketing, outreach, and education to find more companies and industries that align with its mission — fueling the demand for talented data scientists in Africa while making a meaningful impact on global social issues. 

They are also focusing on how to scale the employment and development of data scientists on the African continent. 

“One of our initial concerns was what happened to the other 700 applicants who didn’t make it into our development program,” mentioned Ball, reflecting on the large number of individuals who were not accepted. 

To address this gap, they have actively sought partnerships with online platforms like Dataquest and DataCamp to provide these candidates with scholarships to online skill-building programs and allow them to take part in the Ishango.ai community through webinars and events. In particular, they have prioritized scholarships for female data scientists to close the gender gaps in the field. 

“For those who weren’t accepted initially, it simply means they’re not quite ready yet,” said Ball. “We want to serve as a conduit within the ecosystem, building capacity in numerous ways and our hope is that in a year or two, they may return even more remarkable.”

Ishango.ai is also partnering with African education institutions to support their graduates with job-readiness skills and strengthen the data talent pipeline on the continent. For example, in 2021 they partnered with African Institute for Mathematical Sciences (AIMS), which hosted the Ishango.ai Data Science program at their campus in Kigali, Rwanda.

In the long term, Ishango.ai wants to expand its model beyond data science to provide access to African talent across industries. By leveraging local talent and expertise, they hope to unlock valuable insights and solutions that align with the Sustainable Development Goals (SDGs) and contribute to the betterment of communities in Africa while supporting knowledge transfer and economic mobility.

“Ishango.ai is helping to prove that data science is not just a career; it’s a tool for making a social impact,” said Mensah. “It allows us to bring together all of our skills, knowledge, and experiences to solve real-world problems. The ability to leverage data for positive change is both empowering and fulfilling, and I am grateful to be part of a field — and organization — that has the potential to make a difference in the world.”

The post Leveraging Remote Work to Empower African Data Scientists appeared first on data.org.

Dependable energy reduces poverty, drives economic growth, and supports public health and well-being. The link between development and energy access is mutual: electricity can speed up growth, but progress must also create a consistent demand for energy.

Many countries require a significant transformation in their energy systems to provide affordable and modern electricity services to unserved populations. Unfortunately, gaps in accessible and accurate ground-level data hamper comprehensive energy planning in many low- and middle-income countries (LMICs).

In 2019, The World Resources Institute (WRI), a global research organization, launched a flagship tool called Energy Access Explorer (EAE), which visualizes and analyzes energy demand and supply to equip energy planners, investors, development practitioners, and clean energy entrepreneurs with the information they need to close the energy access gap.

The Challenge

Despite global advances, the COVID-19 pandemic halted progress and worsened energy purchasing power for households in LMICs. Sub-Saharan Africa saw an increase in the number of people without access to energy for the first time since 2013, according to the International Energy Agency.

While some progress has been made, the number of people without access to electricity and clean fuels remains shockingly high.

“Today, Energy Systems Transformations is one of WRI’s priority areas considering the importance of energy for socio-economic development,” said Dimitris Mentis, Lead of EAE. “When we started this initiative, more than 1 billion people lacked access to electricity, and another 2.4 billion lacked access to clean fuels. There has been some progress, but the numbers are still staggering.”

To create financially self-sustaining electricity access initiatives, adequate, well-understood, and visible demand for electricity services must exist. Even more crucial? Connecting the goals of electricity access and sustainable development rather than approaching them separately.

For example, realizing the interplay between electricity and its national goals toward inclusive economic growth, security, and improved health and education, Kenya launched the 2019 Energy Act, requiring each of its counties to submit energy plans every three years with the ambition of achieving universal access to electricity for all Kenyans. WRI also works with partners in Kenya to provide technical support to county governments as they develop their integrated energy plans.

But all too often, these goals are not connected in LMICs.

“To address these issues, all partners — including the governments, private companies, and finance companies — need to be able to access adequate planning tools that use various data sources and inputs,” said Santiago Sinclair-Lecaros, Research Associate for EAE. “But many times, these stakeholders are operating in silos using different forecasting tools, most of which estimate investment needs without understanding aspects of demand or affordability.”

In other words, with a lack of clear and credible data, planners will often increase supply without considering the different levels of consumer need or their ability to pay for and use electricity. An initial grid connection can be prohibitively expensive, even if families could afford to make monthly payments later. Furthermore, unreliable electricity services can hinder productivity and force consumers to invest in costly backup systems like diesel generators.

The Solution

“As we dug deep into our research on energy access at WRI, we realized that if the players in the energy field don’t understand aspects of energy demand and affordability from the ​​bottom up, then they can’t create viable solutions or products,” said Mentis. “We knew we needed a platform that would synthesize granular information on both sides — demand, and supply — and that’s what led us to design and develop the Energy Access Explorer tool.”

EAE is the first online, open-source, interactive platform that uses satellite imagery alongside credible public and local data sets to visualize and analyze energy demand and supply in unserved and underserved areas.

“When we were developing the tool, we also knew we needed to reduce reliance on geographic information systems (GIS) because these tools are complex and hard to use for non-technical professionals,” said Jake Stockman, GIS Researcher, EAE. “We wanted people previously left outside of energy planning to be able to use a platform to generate customized, easy-to-read maps to understand the needs and possible solutions better.”

Off-grid developers, for example, can see where potential customers live and where demand for electricity may be high, while development finance institutions can pinpoint regions where electrification funding would achieve the highest impact. Further, clean energy entrepreneurs can access demographic and socio-economic data to understand consumer ability to pay for electricity. Impact investors and donors can identify areas that need funding to meet development goals on energy access.

But for the EAE tool to be successfully implemented and adopted, it must be localized to the particular needs of a region or country — and that requires building trust, coordination, and capacity.

That’s why the EAE team, first and foremost, engages all key local collaborators and identifies relevant geospatial tools and databases in the geographic area to ensure the platform will complement and add value to existing efforts.

“When, and only when, we agree with all of the local partners that EAE can actually add value, do we start the technical aspects of implementing the tool,” said Mentis.

In consultation with these local partners, the EAE team begins to identify key indicators and potential data sources to customize the tool for the region’s particular needs. Eventually, that data tracking turns into a dynamic database that feeds into a web infrastructure, with tailored functionality based on feedback throughout the entire process.

“But the most important part comes last,” said Sinclair-Lecaros, “during knowledge exchange and capacity building workshops. It’s here that we not only ensure that all partners are thoroughly trained on the tool so they can manage the system themselves, but we also get incredibly valuable insight into how end users are utilizing the tool and how we can make it better.

While the EAE team offers five years of technical support, their goal is to transfer ownership of the tool to the partners on the ground to ensure that it becomes truly embedded in the energy planning process and part of the larger local ecosystem. Regular knowledge exchange workshops help build this capacity and bring the local partners together so that by the end, they act in close collaboration and have a vested interest in seeing the tool continue.

The Takeaway

“Trust building is critical,” said Mentis when asked what others in the sector should take away from the success of the EAE. “Bring everyone together often, and do it in person if possible.”

He also recommends thinking broadly when identifying which partners should be involved. “We don’t just bring in the nodal agencies we work most closely with. We cast a wide net, including health and education, agriculture, in some cases urban development, private sector stakeholders, and other NGOs.”

Such an inclusive process strengthens and spreads trust across the community and dramatically helps with succession planning and capacity building. “One of the challenges that many planning solutions have been facing is that a tool or model is developed, but the stakeholder or individuals involved leave the organization or government agency,” said Stockman. “By having so many people at the table, you ensure that others are willing to step in to provide training and support as vacancies occur.”

Another essential takeaway is that solutions can only be sustained if local capacity building occurs simultaneously.

 “Building capacity is an important first step, but equally essential to ensure the capacity is retained in the country. There is no better body than an academic institution that can train the future generation of planners, clean energy providers, and data scientists,” said Mentis. “That’s why we also focus on creating partnerships with academic institutions to incorporate this particular initiative into their curriculum and training.

EAE is currently operating successfully in seven countries — Kenya, Uganda, Ethiopia, the United Republic of Tanzania, Nigeria, Zambia, India, and Nepal — but has plans to expand into the eight more countries in Sub-Saharan Africa. Together with partners, they also want to incorporate new data sets and use cases focusing on productive uses of energy and clean cooking to customize EAE further.

“Only last year, we conducted more than 20 in-person training workshops, reaching more than 1,000 stakeholders. Moving forward, our goal is to train even more partners and equip them with an application to help them identify priority areas for energy access interventions,” said Mentis. “As we gain knowledge and experience, we are finding new and thrilling opportunities to improve our efforts for an even greater scale and meaningful energy impact.”

The post How WRI’s Energy Access Explorer Empowers Inclusive Data-driven Solutions appeared first on data.org.

Rich in both qualitative and quantitative data, Generate Health also engages community members and organizational partners with insights from indicators such as infant mortality, maternal mortality, access to prenatal care, low birth weight, and on-the-ground lived experiences. 

As the organization began its most recent strategic planning process, they wanted to know—how were they using data to contribute to the region and where could they improve. data.org’s Data Maturity Assessment (DMA) became an essential tool in identifying their current use of data and prioritizing ways to increase data insights to better serve the community. 

The Challenge

Infant mortality is a significant problem in the St. Louis region. In fact, the number of infant deaths in the region each year could fill 15 kindergarten classrooms, making it one of the worst infant mortality rates in the nation. What’s more, Black babies are three times more likely to die than White babies before their first birthday due to the toxic stress experienced by Black parents caused by racism and discrimination and the challenges in accessing equitable and culturally congruent services.

Data source: Generate Health

Armed with and fueled by this staggering data, Generate Health mobilizes critical community partners—from hospitals to health systems to social service providers—to take action. 

After two harrowing years of doing everything the organization could to help protect mothers and babies during the COVID-19 pandemic—working with partners to increase quality care through home visitations, access to perinatal behavioral health, safe sleep education, and more—the team came up for air, realizing that it was time to reflect, assess, and plan for the future. 

From the outset of their strategic planning process, leaders within Generate Health understood that data was an essential driver of every facet of their work, but that they may not be utilizing it effectively. 

“This was really an opportunity for our team to talk more strategically about data with the recognition that we have a lot of it and we’re not always using it intentionally,” said Leah Moser, director of planning and partnerships.  “We wanted to know—are we asking the right types of questions? Is the data we’re collecting helping program outcomes? Are we sharing it back to our communities and partners effectively?”

Staff across the organization deal with a variety of data types depending on their role—from health and program to finance and donor data—yet it’s not consistently shared in a way that garners greater insights.  

Further, they wanted to make sure that they were putting impacted community members at the center of data collection and analysis. 

“We’re at a moment in the organization where we not only think hard about how we leverage the information that we have, but how we take into account the communities we serve at all steps,” said Moser. “We recognize that there are power dynamics between community members and those coming into the space asking questions. So we have to make sure that we consider the impact of the questions we’re asking and that those questions are truly necessary.”

Moser and her team recognized that Generate Health needed help to take their data to the next level.

The Solution

In the St. Louis region, organizations like Washington University and the St. Louis Regional Data Alliance are helping build data capacity and collaboration among their fellow social sector organizations. It was through Generate Health’s ongoing connection with these partners that they discovered data.org’s Data Maturity Assessment. 

Launched in 2022, the Data Maturity Assessment (DMA) provides social impact organizations a snapshot of their data maturity journey plus the relevant tools and resources to move forward. The DMA provides a framework for assessment within three categories:

• Purpose: What does the organization want to use data to do? 
• Practice: How does the organization plan to use data to achieve its mission? 
• People: Who works with data and makes data-driven decisions? 

Over the last year, more than 1000 organizations have taken the DMA to identify ways to strengthen their data maturity—one of them being Generate Health, where eight individuals at different roles of the organization took the assessment. 

There are five stages—or archetypes—of maturity within an organization’s data journey, and each one presents specific opportunities to build a flourishing data practice. 

“Generate Health landed squarely in the ‘Data Informed’ archetype,” said Moser. “And this really reflects where we are. We have begun to harness the power of data for impact but we need to further develop and refine our efforts.” 

Moser points to two key areas for improvement that the DMA highlighted—better coordination and better transparency. Generate Health needed to create more holistic strategies for how they use the data they already had access to, and in turn, communicate more frequently and openly about that data with community members and partners. 

“The DMA helped us realize that storytelling is a big part of the data process,” said Moser. “When we use data outcomes to tell stories about our positive impact—especially when it’s the result of collaboration—it not only strengthens trust in our organization but encourages further data sharing and coordination with our partners.” 

The DMA also signaled the need to create stronger processes and protocols around collecting, inputting, and ensuring quality data.

Generate Health took these and other DMA findings and aligned them across their strategic plan. 

“Being able to integrate the recommendations from the DMA was a huge turning point for the organization. It provided a really comprehensive view across and pointed to where we needed to prioritize and invest,” said Moser. 

The Takeaway

What advice would they have for other organizations thinking about taking the DMA?

“Go for it.” 

Moser continues, “But after you complete the assessment, it’s critical that you make space to communicate the findings back to your team.” 

Generate Health convened two all-staff meetings to review and discuss the findings, giving a comprehensive presentation that showed all scores across categories and looking closely at areas where there was variance. 

“It was truly eye-opening to be able to have these conversations across the entire organization,” said Moser. “We had staff that hadn’t thought about their roles intersecting with data, but when you drill down they’re involved in the data pipeline every day. It became clear that we all have a responsibility to data.”

Moser noted that also having multiple people across different roles at the organization take the DMA was crucial in aligning a common understanding of the successes and challenges around data, helping the team develop a shared language, and creating buy-in for a data-driven culture.  

They then reconvened to brainstorm how to align and integrate data strategies with the strategic plan. They went through the plan in painstaking detail, identifying data needs and the resources needed to meet those needs, with an overarching goal of streamlining data processes across initiatives.

As Generate Health looks forward to the next several years, they are also thinking about what roles they need internally to sustain advanced data strategies. Ideally, Moser notes, they would have a centralized learning and evaluation role that has a broad lens across the organization.

“Funding an organizational data practitioner is tricky,” said Moser. “We need more funders who will support general operations. But through this process, we’ve gotten better at knowing what data we need and how to communicate with funders to help them see the bigger picture. And we have a lot of hope for the future of data at Generate Health.” 

The post Assessing Organizational Data Maturity Helps St. Louis Health Coalition Use Data for Greater Impact appeared first on data.org.

With 63 partners in 34 countries reaching more than 159 million women clients, Women’s World Banking works to create greater economic stability and prosperity for women.

As Inclusive Growth and Recovery Challenge awardees, Women’s World Banking and the University of Zurich assessed how algorithms in digital credit applications can increase lending to women borrowers, studied the applications of machine learning and AI to remove bias in lending, and explored the challenges facing digital financial services as a result of COVID-19 and the potential solutions.

Watch video

The Challenge

One billion women manage their financial lives outside of the formal financial system. That means a quarter of the world’s women don’t have access to a safe place to keep and save money or a way to obtain credit, insurance, pensions, or other financial services. 

Why? Sonja Kelly, vice president for research and advocacy at the Women’s World Bank, says it’s complicated. 

Among the barriers: legal constraints in family law and inheritance determine a woman’s ability to own property or access collateral for financing. In addition, female entrepreneurs are more likely to operate in the informal sector, often from home, providing cash-based retail or services. Add to this unconscious or built-in bias in credit scoring processes.

The good news is that recent innovation in financial technology has accelerated opportunities for those in emerging markets to access financial services easily and affordably. For instance, digital financial services allow customers to conveniently deposit even small amounts of cash to make payments, pay bills, send remittances, or store money outside of the home—all through the use of a mobile device.  

Still, access to these services is not available to all women.

For one, while mobile accounts for 85 percent of broadband connections in low- and middle-income countries (LMICs), there is a significant difference in mobile ownership between men and women, with women less likely to have a smartphone and less likely to access the internet from their mobile devices. If women can’t access these new digital financial services, including even small loans, they can’t build the credit necessary to scale up to larger loans. 

Second, technology can perpetuate the same biases and exclusionary tendencies held by the people who create it. “If you put a machine on top of a human process, it’s just going to learn the human bias and make it worse,” says Kelly. Alternatively, if algorithms are built upon data composed primarily of men’s activity, they may not be built with women’s behavior patterns in mind. Women’s World Banking’s research and technical assistance work revealed that even when men and women have the same average credit score, women are more often rejected for loans. 

Coders sitting in Silicon Valley are writing code for some of the biggest creditors in the world for emerging markets. The majority of those coders are men. A close look at the outcome of the algorithms they’re creating revealed that even when men and women have the same average credit score, women are more often rejected for loans.

The Solution

In 2021, Women’s World Banking and partner institution, the University of Zurich, applied for data.org’s Inclusive Growth and Recovery Challenge, which called for breakthrough ideas that harness the power of data to help people and communities thrive.

They were among the nine awardees who were granted funding, technical assistance, and expert guidance. With this support, the duo set out to use those resources to work with financial service providers around the world to increase credit access for low-income female entrepreneurs.

“Our work focused on solving the self-reinforcing challenges of women’s low data footprint,” said Kelly. “Their lower likelihood of seeking credit only serves to decrease their access and use of credit for their businesses. That has to change.” 

Using data from financial institutions in three countries—India, Mexico, and Colombia—the team audited credit processes for gender bias using AI and machine learning techniques alongside other statistical methods. 

They found two key trends.

First, “reject inference bias” existed in all three markets. This means a substantial subset of women rejected for loans should have been granted those loans. When compared to men who were also rejected, women often had higher credit scores on average. But the algorithms to assess applicants did not flag these creditworthy women, for myriad reasons. For example, an algorithm may rely on data points with a strong bias against women—for the amount of time spent in brick-and-mortar businesses (using mobile GPS data), even though women tend to spend more time working at home given their unpaid care responsibilities.

Second, they found a high risk of future bias in credit assessment in institutions that were heavily dependent on existing data to “train” algorithms to spot creditworthy applicants. The low representation of women in these existing datasets drove this risk.

Based on these findings, and recognizing that not every institution has months to spend auditing their risk process for bias, Women’s World Banking and the University of Zurich assembled a set of easy-to-understand analytical tools to begin conversations about gender credit bias within financial institutions. 

Their “Check Your Bias” tool is a six-dimension scorecard for CEOs and data scientists alike to assess how well they make decisions about whether and how to lend to women compared to men. This toolkit includes an open-source code for advanced data analytics to spot bias among rejected applicants.

For the institution with the highest proportion of rejected women customers, they built a gender-fair algorithm to approve new loans for women entrepreneurs. More importantly, they are processing this algorithm for other institutions struggling with similar issues and making these tools publicly available on GitHub.

The Takeaway

“Analyzing for bias and implementing solutions should be a bespoke process, as each financial institution is unique,” said Kelly. “But we recognize that success means to scale and that the adage, ‘information is power’ really is true. This is what drove us to package all of these tools into a replicable toolkit for other financial services providers.”

They are also pursuing opportunities to use AI to increase women’s access to and use of other products, including savings, and insurance to close the global gender gap in women’s financial access.

“As we evolve this project, we’re focusing less on the actual tech used and more on the outcomes of that tech,” said Kelly. “We have to back into the bias, the decision making, and the algorithms. Those three variables can be extremely gendered. If we want to make digital financial services more accessible, we have to address those first.”    

Women’s World Banking is excited to replicate and scale up its initial work by collaborating with a cohort of four institutions in 2023 to provide technical assistance and capacity-building for identifying and addressing biases, in addition to continuing to share these open-source products. 

“Gender inequity cascades through so many facets of society,” said Kelly. “But if we can start to give women greater access to financial prosperity, we can begin to really chip away at this inequity and see women thrive. And that not only affects the individual, it affects families, communities, and entire economies.” 

The post Innovative AI for Women’s Financial Inclusion appeared first on data.org.

Organizations like Break Through Tech are working towards helping women overcome gender barriers that are both pervasive and persistent in the tech industry. Currently, the percentage of computer science and artificial intelligence PhDs awarded to women languishes at 20 percent. At the cross-section of academia and the private sector, the organization helps launch women into technology-related degrees and careers.

With offerings in computing and artificial intelligence, Break Through Tech programs begin during students’ early college years for young women, with a particular emphasis on welcoming Black, Latina, Indigenous, and first-generation women, trans, and nonbinary students. The program is not only free, it also pays a stipend, allowing women to participate who would otherwise need to work to pay college expenses.

Albina Krasykova and Tammy Babad are two such students. As fellows in the AI program, they credit Break Through Tech with exposing them to meaningful career development opportunities and positioning them for success in the tech industry after graduation.

The Challenge

Gender inequality in tech is a long-documented problem, and it’s only getting worse. Only 25 percent of computing jobs in the U.S. are held by women, down from 32 percent in 1990, and unchanged since 2016. Add to that the mere two percent of women who graduate with a degree in computer science, and you have a field dominated by men.

Leading researchers of fair and ethical AI standards, such as Sharla N. Alegria, have found that lack of diversity in a field leads to a greater risk of unintentional discrimination. Too often, the people building a model or algorithm don’t know enough about the marginalized communities it is going to impact to effectively develop responsible and ethical technological solutions. 

Take the classic example of crash-test dummies. Early designs of airbags were modeled for male bodies, leading to an entirely avoidable number of women killed by airbags. In fact, only recently, in 2022, was a dummy modeled after an actual female body instead of simply a smaller version of the male dummy.

Two seniors majoring in computer science at the City College of New York (CUNY) — Albina Krasykova and Tammy Babad — know first-hand what it’s like to be one of very few women studying what’s still considered a male-centered field.

“At CUNY, literally thousands of people are majoring in computer science — so it’s even more noticeable that as a woman, you’re a minority,” said Babad.

“I have always been inspired by innovative technologies and the leaders developing solutions that will impact the whole world’s dynamics. But when it came time for me to start my career in tech, I found it to be quite challenging, especially as a woman,” said Krasykova. “I kept asking myself: ‘Am I really capable of doing something this incredible as a career? Can I actually be a leader in tech? Am I smart enough?’”

So when both women were given the opportunity to develop hands-on skills in artificial intelligence alongside other women and with the guidance of experienced female mentors, they jumped at the chance. 

The Solution

Launched in 2016 with support from founding sponsors Verizon and Accenture, Break Through Tech partnered with CUNY with one central goal: to increase the number of women graduating with degrees in computer science and related tech disciplines.

Over the next three years, CUNY saw incredible progress: women declaring computer science and related disciplines as their major increased by 61.5 percent and women graduating with relevant bachelor’s degrees increased by 95.4 percent.

Buoyed by these results, Break Through Tech began replicating its programming model in other cities, including Chicago, Washington, DC, Miami, Los Angeles, and Boston. Pivotal Ventures, an initiative of philanthropist Melinda French Gates, signed on as an investor, along with the Cognizant Foundation and Verizon.

Through deep engagement with nearly 200 industry partners, Break Through programs provide not only theoretical instruction but also practical tools to help students launch their tech careers.

“The program started with a summer [machine learning] engineering course where I learned about data analysis pipelines, training and validating ML models, and common ML/AI libraries—practical skills to help qualify me for entry-level jobs in the field,” said Babad. “And then this fall, I had an incredible experience in the AI Studio, where I worked with a team of peers on real-world projects and created a portfolio of AI solutions.”

As part of the experience, students have access to ongoing one-on-one mentorship—both from women professionals involved with the program and peers in their cohort.

“Honestly, the group of women I was working alongside felt like family,” said Krasykova.

Babad agreed, emphasizing the value of networking: “I remember so many instances where I was talking to other students and they would learn about what I was doing and say, ‘oh I should connect you to this person. Or you should contact this company, they’d be really interested in that.’ We were all there to support and elevate each other, not compete,” she said.

The Takeaway

In order to grow and diversify the tech talent pipeline, more intentional efforts are needed around recruitment, retention, and ongoing support. And when more women are in that pipeline, the industry will flourish.

“As a student of Break Through Tech, I can confidently say that the organization has had a huge impact on my journey to pursue a career in the tech industry,” said Babad. “I was given access to amazing resources and an incredible mentor all while learning about one of the coolest technologies in the world—artificial intelligence. What can be better than that?”

With that goal in mind, Break Through Tech is excited to expand to more cities nationwide and has a long-term vision of growing tech hubs across the country that will activate and align both sides of a city’s tech ecosystem: academia and industry.

“This organization is inspiring women to work on the most innovative AI projects, while also building a healthy community of female leaders,” said Babad. “Leaders who not only care about one another but are focused on creating a positive impact on the world.”

Organizations like Break Through Tech are helping to engage and inspire the next generation of women technologists—technologists that have the skill set and confidence to break down the gender barriers the tech industry has upheld for so long.

“We are living in a world where technology grows more powerful every day,” said Krasykova. “If we can have a diverse pool of people making decisions about what our tech will do and how it will do it, the possibility of creating fair and equitable solutions to modern problems will be closer in reach.”

The post Program Helps Women Enter and Thrive in a Male-Dominated Field appeared first on data.org.

But how do these two threats to society intersect and interact? How can we spot threats earlier and mitigate impact as a result?

Those are the kinds of questions the team at InnovaLab at Universidad Peruana Cayetano Heredia set out to answer through the creation of a digital infrastructure of harmonized and actionable databases across nations and sectors.

“If we want to couple climate data with health data with economic data with demographic data, it becomes very complicated,” says Gabriel Carrasco, director of the InnovaLab and a professor and researcher at the university. “These data sets don’t speak the same language, but we need greater insights for action, and that means there has to be a coordinated ecosystem of translation and connection.”

The Challenge

As weather patterns change, communities in climate change hotspots have become more susceptible to climate-sensitive infectious diseases like malaria, dengue fever, Lyme disease, West Nile virus, and more. Add in disastrous weather events, environmental degradation, and socioeconomic inequities, and the result is that already-vulnerable communities are facing extraordinary levels of hardship. 

In fact, over the past four decades in the Latin American and Caribbean (LAC) region, the incidence of dengue, a mosquito-borne viral disease, has increased from 1.5 million cases between 1980 and 1989 to 16.2 million cases between 2010 and 2019. That’s more than a 1,000 percent increase.

The existing public sector’s early warning systems for infectious disease and climate events are commonly disconnected; there are limited mechanisms in place that relate the two. In other words, there is a lack of data that helps understand and predict the impacts of extreme weather events and environmental changes on disease risk.

Attempting to find and connect climate and health data proves next to impossible with the current infrastructure in developing countries. For instance, when faced with an outbreak of dengue fever in Peru, the health minister has data on only health and demographics. If you wanted to combine that with climate data you would need to ask the minister of the environment. Want to relate economic data? Ask the minister of the economy and finance.

It might take weeks or months to gather the information, and by then, valuable time—and possibly lives—have been lost in a fast-moving infectious disease outbreak.

“Because everything in our world is so interconnected, it’s really hard to have information separated out in so many different ways. It means people don’t know where to get help or resources and we are missing valuable insights,” said Carrasco.

We’re engaging engineers, climate scientists, epidemiologists, data practitioners, social scientists, and more. The idea is that even if we, as scientists, want to be really open and think on multiple levels, we still have our own biases. Having as many disciplines at the table helps us think through all scenarios and needs.

Gabriel Carrasco-Escobar, Ph.D.

The Solution

Harmony is a concept most often used in music, but at its core is the idea of creating a consistent whole. The Harmonize Project seeks to build a digital infrastructure of harmonized databases to feed early warning systems for epidemics exacerbated by climate change in the LAC region.

In collaboration with the Barcelona Supercomputing Center (BSC)—and a network in Brazil, Colombia, and the Dominican Republic—and supported by Wellcome, the project will bring together ministries, universities, private companies, social impact organizations, and more to create a complex data infrastructure and collect real longitudinal data on the ground. These new data sets will provide valuable information on seasonal variation in land use and human behavior has given climate hazards, which are generally assumed to be unchanging in health impact models.

The outcome of such an infrastructure? Actionable knowledge to inform local risk mapping and create strong early warning systems to drive resilience in low-resource communities.

“We’re engaging engineers, climate scientists, epidemiologists, data practitioners, social scientists, non-profit leaders, and more,” said Carrasco, who is also the Peruvian principal investigator of the Harmonize Project. “The idea is that even if we, as scientists, want to be really open and think on multiple levels, we still have our own biases. Having as many disciplines at the table helps us think through all scenarios and needs.”

In Peru, the intervention activities will take place in the Loreto region, an Amazon area that is significantly affected by climate change and offers an ideal setting for the spread of vector-borne diseases. Collaboration with authorities and managers in both the public and private sectors and civil society will help local support and adoption of the project and its resulting tools. This is a model the Harmonize project hopes to replicate across regions and nations.

A four-year effort, the project is currently mapping stakeholders and gathering their requirements, which is not an easy feat.

“Precarious political systems, the high rotation of ministers and officers, private and public institutions that are uncomfortable sharing data—all of this adds to the complexity of this project. What we really want, in the end, is to meet the minimum set of requirements for each stakeholder so that they not only adopt the tool, but work to maintain its care and feeding,” said Carrasco.

Mapping with drones and machine learning

In collaboration with the NY Health Department’s Wadsworth Center, the London School of Hygiene and Tropical Medicine (LSHTM), and the University of California, San Diego (UCSD) Institute for Global Health, this project pioneers collection methods and analysis of remote sensing data using drones and Machine Learning (ML) to be applied to the control of vector-borne infectious diseases in urban-rural settings.

The Takeaway

As stakeholder mapping comes close to completion, the team is gearing up to start data audits to understand the landscape of data interactions. Next, begin the fieldwork—collecting the data across sectors to see if use cases can provide meaningful information.

And yet, while these are important steps toward achieving success with this project, one key step stands out the most to Carrasco: building buy-in.

“Ultimately we have to get the word out to those in positions of authority, across nations, as to why they should use this tool. It really comes down to loss and damage. Can we show them that there is a financial—not to mention human life—benefit to using this tool? Will they understand that it helps prevent economic damage?”

That understanding will be critical because creating a complex data infrastructure such as this is hard. It will take years, it will take a lot of back and forth, and will take a sizable investment. Systems-level data strategies, by nature, take a longer view to better understand the structural investments necessary to collect, clean, store, analyze and govern data across partners.

But without taking the time and resources to relate data sets to one another across nations, sectors, environments, and other contexts, we risk missing extraordinary insights—insights that could save lives and create resilience where there is now devastation. 

The Harmonize project is led by Prof Rachel Lowe at the Barcelona Supercomputing Center (BSC), in collaboration with principal investigators in Peru (Gabriel Carrasco, UPCH), Colombia (Mauricio Santos, Universidad de los Andes), and Brazil (Chirstovam Barcellos, Oswaldo Cruz Foundation). Our mission is to develop cost-effective and reproducible digital toolkits for harmonizing environment, climate, and health data for stakeholders operating in climate change hotspots. Harmonize will gather and organize existing multi-source climate, environmental, socioeconomic, and health data, as well as collect new longitudinal ground-truth data using drones and weather sensors, to calibrate and downscale coarser-resolution Earth Observation, climate reanalysis, and forecast datasets in disease transmission areas. The digital toolkits will allow researchers and users to link, interrogate and use multi-scale spatiotemporal data to understand the links between environmental change and infectious disease risk in the local context and to build robust early warning systems in low-resource settings.

The post Data Sharing Across Sectors Creates Better Early Warning Systems appeared first on data.org.

That’s when conversations began with a group of partners and donors—including co-founders Google.org, Canada’s International Development Research Centre (IDRC), and GIZ’s FAIR Forward on behalf of the German Federal Ministry of Economic Cooperation and Development—about setting up a collaborative fund to get resources to data scientists in low- and middle-income countries. The result was Lacuna Fund (lacuna means gap), which works to distribute funds to data scientists and researchers in underserved communities globally to help fill data gaps to make machine learning more equitable. 

One of Lacuna Fund’s first areas of focus was agriculture in Sub-Saharan Africa, where farmers have access to high-tech apps to identify crop yields, pests, and diseases but lack the relevant data to make the tools useful for them.

With over 100 applications from—or in partnership with—organizations across Africa, Lacuna Fund provided 11 projects with first-round funding to unlock the power of machine learning. These projects aim to alleviate food security challenges and spur economic opportunities by giving researchers, farmers, communities, and policymakers access to superior agricultural datasets.

The Challenge

 “Currently, the vast majority of datasets that fuel AI and machine learning applications contain information about North America and Europe,” says Jennifer Pratt Miles, partner at the Meridian Institute. “This means that some of the amazing applications developed to help health care workers, farmers, and governments, may not be applicable to large parts of the world because the underlying data may be missing at best, or inaccurate and misleading at worst.” 

In the agricultural context, many farmers today have access to a variety of high-power tech applications that can identify crop yield, pests, disease, and more—dramatically stabilizing and increasing production as well as economic benefit. But without information about the crops they are growing or the local conditions, these tools are of little use. 

This data by its very design leaves farmers in places like Sub-Saharan Africa at a distinct disadvantage, where food insecurity is already at an all-time high, affecting almost 60 percent of the population.

“Not only would having complete data provide a whole new service to farmers and make their livelihoods more sustainable,” notes Pratt Miles. “But it would allow for better information gathering and forecasting to help us act proactively to mitigate food security challenges.”  

The Solution

When Lacuna Fund published a request for proposals targeting organizations in Africa with a focus on agriculture, they were pleasantly surprised by the depth and breadth of the more than 100 proposals that were submitted, and ultimately provided first-round funding to 11 groups across the continent. While the resulting projects and initiatives varied greatly, they all shared one primary goal: to create or complete agricultural data sets and most importantly, to make them widely available.

“Lacuna Fund’s IP policy states that data sets must be made public unless restrictions are needed to protect privacy or prevent harm,” said Pratt Miles. “But more and more the research community is finding ways to achieve both public access and privacy protection.”  

In addition, Lacuna Fund asked grantee organizations to engage with the local communities impacted by the data sets, create a sustainability plan for how the data would be collected and managed in the future, and perhaps most importantly, ensure that the data sets were actually utilized. To help ensure these conditions are met, Lacuna Fund requires that applicants be headquartered in—or have a substantial partnership with an organization located in—the region where the data will be collected

Multidisciplinary teams, from data scientists to agricultural experts, went to work.

In the Eyes on the Ground project, the team from ACRE Africa, an organization that provides insurance to small crop farmers, and the International Food Policy Research Institute (IFPRI) used smartphones to create a unique dataset of georeferenced crop images from 11 counties in Kenya.

“This is a novel concept that endeavors to provide smallholder farmers with risk mitigation and adaptation strategies through satellites and smart phones to ensure that they invest in high productivity agriculture,” says Lilly Waithaka, Agri-Climate Data Analyst at ACRE. “The ground pictures not only provide ACRE Africa the ability to fine-tune insurance products/models and minimize basis risk, but also to observe management practices that promote the adoption of productivity-enhancing yet resilient technologies.”

The University of Nigeria Nsukka, another group that received first-round funding, is using remote technology to monitor fish farming. These datasets will enable machine learning researchers to build models for predicting fish yield in terms of weight gain, water quality parameters, and feed consumption.

“We are hopeful this will open many opportunities to local fish farmers as it will shed tremendous light into what happens beneath the pond’s surface,” says Collins Udanor, Deputy Director at the University of Nigeria’s Education Innovation Centre. “This will indeed explain many things to the farmers and improve yields, as well as make available local datasets for the machine learning community.”

The Takeaway

Lacuna Fund recently brought grantee teams together in person for the first time to hear about work and outcomes from the 11 projects and to share learnings and information with each other.

“It was actually one of the most valuable parts of the entire process,” says Emma Heth, Project Associate and Ruckelshaus Fellow at Meridian Institute. “Grantee teams not only shared valuable knowledge and insights with one another, but Lacuna Fund learned a great deal about how we can improve this process in the future.”

For instance, it was clear that more support was needed to help teams move from the creation of data sets to developing and using machine learning models. “We’re now looking to scale our impact, so we support more than just the first point of the value chain in data science and move toward application,” says Heth.

And now that they have a proof of concept, they’re also looking at how to grow both funding and geography.  

In early 2023, Lacuna Fund will issue two calls for proposals for new partners. These calls will focus on data sets to better understand the relationship between climate change and forests, and sexual and reproductive health and rights.

“A key part of our plan to scale is forming regional or thematic hubs to identify partners in Africa, Asia, and Latin America, to lead and manage the grant-making process locally,” says Heth. Pratt Miles added, “This approach, paired with global, multi-disciplinary panels of experts that select grantees helps ensure the entire process is not only well informed and efficient, but that our guiding principles are always front of mind so that we’re funding datasets that have a transformational impact.”

The post Filling Agricultural Data Gaps Gives Farmers and Organizations Access to Powerful Tech appeared first on data.org.

An 80-year-old organization that provides free, confidential advice to assist people with legal, debt, consumer, housing, and other problems in the United Kingdom, Citizens Advice has a deep on-the-ground understanding of the most crucial issues communities are facing at any given moment. 

And in the fall of 2021, it was clear that the cost of living was becoming a crisis. 

“What’s unique about doing advocacy work at Citizens Advice is that we can quantify what would otherwise be qualitative because we have access to massive amounts of operational data through the services we provide,” says Head of Policy Morgan Wild. 

That access allowed their data and policy teams to quickly come together to create chart-smart visualizations of exactly how people across the country were facing greater economic insecurity. 

The Challenge

The prices of energy, housing, and consumer goods continued to climb throughout the fall of 2021 and those coming to Citizens Advice were making difficult decisions about what to cut back on and where to rely on community support. Citizens Advice’s data showed households increasingly seeking referrals to food banks and advice about how to pay their energy bills. These key indicators helped Citizens Advice forecast the looming crisis earlier than most other government or advocacy entities in the UK. 

“Even before it kicked up in the public imagination, the warning lights in our data started flashing,” said Tom MacInnes, chief analyst. 

“At first, the government didn’t realize the extent of the challenge,” added Wild. “But because we could see this coming down the tracks quite early on, the rising cost of living became a campaigning priority and we continued to push it.” 

By the spring of 2022, record numbers of people in the UK had entered or were facing poverty. Finally, on May 27, 2022, the UK government announced a £15 billion package to provide support to millions of households, including a discount on energy bills and a one-time cost of living payment.

“The package reflected everything we had recommended, in particular, cost of living payments of about £650 to households that qualified,” said Wild. “We were really pleased to see our policy efforts pay off and we thought, what do we need to do next?”  

The next step, they realized, was tracking the effect of this package on those seeking their services. This was a central test for government policy over the coming months: could it turn these trends around?

“A good few crisis indicators in our data that would let us look at where the package was affecting people,” said Wild. “And using this data we could continue to affect policy.” 

The Solution

After two sprints and several intense working days, the data and policy teams produced the organization’s first-ever cost-of-living dashboard. 

“It was a really nice example of the policy and data teams bringing together quite different disciplines to be able to visualize the dashboards’ various constituent parts,” said MacInnes.  

And what that dashboard revealed was stark.

By July of 2022, Citizen Advice had helped more people with energy issues compared to any other year on record and we’re seeing more people coming to them who were facing or experiencing homelessness than ever before. But it was also clear that parts of the government package were working. There was a sharp decline in food bank referrals in July, directly after the cost of living payment was distributed. 

The teams also realized that this data was only useful if the people making policy decisions had access to clear, well-displayed information. 

“We worked really hard to make our stuff look as enticing as possible to catch your eye and convey information quickly,” said MacInnes. Most importantly, they made the dashboard public, something they had only begun doing during the pandemic. “We had a lot of data, but you had to ask for it. It wasn’t fully accessible, even to our own staff.”

Alongside the publication of updated, transparent data each month, Citizens Advice also began hosting large virtual events, often attended by more than 1,000 people, to discuss and dissect the trends. Attendees range from the general public to officials from local and central government offices. The shift in approach has increased not only public trust in Citizens Advice but governmental reliance on their data and insight. 

“We have seen an incredible increase in requests for our data—from local civil servant analysts all the way to central government offices,” said MacInnes. 

The Takeaway

It’s the currency of the public dashboard data that is allowing Citizens Advice to continue to impact policy on behalf of those they serve. 

Sharing operational data in a clear, visual way helped build a case for government intervention and what’s more—provided insight into exactly what type of intervention might work. But in order to create these compelling, actionable dashboards, experts from across disciplines had to work together. 

“Each time our teams work together it gets easier and better,” said Wild. “We’ve identified the right foundations for this going forward and are now in the iterative phase, taking insights from our virtual events and evolving the dashboards—dropping some things and adding in new elements here and there.”

Looking ahead, Citizens Advice is now working on an open data offering to provide dynamic, localized information to the public as an expanded service of the organization. 

“Traditionally, we write a lot of policy reports at Citizens Advice with static data and graphs,” said Wild. “But the experience of the last couple of years has made us realize how valuable our data is and, even more, how important it is to show it visually and make it accessible to those who need it most.”

The post Public Dashboard Shares Ground-up Insights to Inform Government Response appeared first on data.org.

Across industries, around the world, in both the public and private sectors, emerging technologies are bringing innovation at record speeds. There is a growing understanding that data is critical for effective decision-making, and organizations of every kind, from healthcare startups to well-established NGOs, are collecting and analyzing data like never before.

The sophistication with which these entities are incorporating data into their decisions varies, but across the board, a persistent challenge has emerged: finding the talent with the skills and desire to maximize and make sustainable the meaningful use of data science.

But if you’re looking for a purpose-driven data professional, the University of Chicago (UChicago) may be a good place to start your search.

The Challenge

While access to top data talent is a challenge across the board, it is particularly difficult within social impact. Nonprofits and other social service organizations often have less mature data operations, offer lower pay than their private sector counterparts, and work with smaller teams and more limited datasets. In low- and middle-income countries alone, there will be a need for an estimated 3.5 million data professionals focused on social impact over the next 10 years. 

The demand is enormous, but the immediate career opportunities may not seem as attractive.

“Students don’t necessarily go into data science degree thinking, ‘I’m going to be a social impact data scientist.’ For years, we’ve been asking, ‘how do we build this sector and create these career pathways for students so they can see those opportunities for themselves’?” said Mindi Mysliwiec, senior director of outreach for the Data Science Institute at UChicago.

Mysliwiec’s background is in law, and she had a similar experience as a student. She knew she wanted to make a difference, and could see clear pathways to a public interest law career.

Today, she sees young people with those same ideals and energy overlooking social impact because, still in its nascency working with technology and data science, the sector has been slow to make the case and create the right opportunities.

“One of the challenges of going into the social impact space as a new graduate with a technical background is you look at, ‘who will be my mentor? What are my professional development opportunities’?” Mysliwiec says. “Our team is looking at ways we can professionalize this space. Building that community is really key to keeping this pathway as a career opportunity open for more people.” 

More people, and more diverse professionals. 

The STEM disciplines, both in academia and in the workforce, have been plagued by a lack of diversity. That homogeneity stifles innovation and often results in unintended consequences when technology is developed without inputs from a range of perspectives and is deployed in communities that look different from the one in which the so-called solution originates.

That, says Nathalie Valenzuela, is what makes her experience at UChicago stand out.

The Solution

A Master’s student from Fresno State University, Valenzuela is part of UChicago’s Data Science Institute (DSI) Summer Lab, which launched in 2018 and is an immersive, 10-week paid summer research program. She came to the program thanks to data.org’s Capacity Accelerator Network (CAN), which funded the creation of a consortium of education partners, including a broad network of minority-serving institutions, to amplify social impact through data science. 

“Data science is not just one stereotypical person. It’s so diverse here,” Valenzuela said, noting that in the past, she has faced discrimination as a woman in STEM. At UChicago, she found a supportive community. “There are so many people who are into it and are trying to pursue it, and knowing my work is going to impact society made me realize this is something I want to pursue further.”

The Summer Lab program—which in 2022 had 49 participants—engages Master’s students like Valenzuela alongside high school and undergraduate students, and pairs them with data science mentors in a variety of domains, including computer science, climate, and energy policy, biomedical research, and more.

Launa Greer, a software engineer at DSI, is one of those mentors.

“Being in an environment that had open dialogue between faculty and staff members and working directly with students on different computing and research areas was very interesting and attractive to me. I enjoy the intersections,” she said.

An interest in interdisciplinary work is no surprise for Greer, who actually studied religion, history, and philosophy as an undergraduate student before graduating with a master’s from UChicago’s Computational Analysis and Public Policy program, jointly under the DSI and Harris School of Public Policy. While she had a lot to learn coming into the world of data science, she wants to see more young professionals appreciate the value of bringing diverse perspectives into the field. 

“No background is wasted,” she said. “Really believing in yourself and giving yourself the patience to learn new material is important. Applied data science is challenging because it blends together so many different domains of thought. This is an area that is constantly evolving, so you need to be comfortable being uncomfortable.”

Seeing the tremendous need for talent in social impact, UChicago specifically added a social impact track to the Summer Lab two years ago, where students work as a team with an organization that is identified by another DSI partner—the 11th Hour Project, a grantmaking foundation that serves more than 400 nonprofits around the world. Locally, UChicago engaged the University of Chicago’s Office of Civic Engagement to build up a base of nonprofit partners close to home.

And just as the number of nonprofit partners is growing, so too is the number of students. Of the roughly 400 Summer Lab applications for 2022, 75 percent indicated an interest in social impact.

“The more social impact opportunities we put in front of students, the more students who will choose that path,” Mysliwiec said. 

The projects are hands-on and designed with the needs and capacity of nonprofits at the center, from climate to financial inclusion to social services. Building trust with the nonprofit partner is key, as is understanding the root of the challenge and making the solution sustainable after the Summer Lab team hands it over. 

While sustainability and replicability are at the core of the Summer Lab program, it is also central to DSI’s work more broadly. They are not only focused on building a talent pipeline through University of Chicago programming but also on creating open-source curricula and best practices that can be adapted and expanded upon to solve big problems in Chicago and beyond. Through the CAN consortium, a cross-institution team is building a modular, experiential data science curriculum focused on applications to real-world problems, like financial inclusion, that can serve as a model for other emerging programs.

The Takeaway

UChicago’s portfolio of data science programming continues to grow alongside student and sector demand. The Summer Lab is a perfect example, and the university doesn’t see the demand or growth slowing down anytime soon. The reviews from staff, mentors, and students alike continue to reinforce that the university has hit on something necessary and wanted.

“Knowing my work has an impact beyond me in a way is such a rewarding feeling,” Valenzuela said. 

Looking ahead, Mysliwiec and her team at UChicago hope to diversify and expand the data science talent pipeline by moving students through a continuum of programs. The DSI Summer Lab may be the point of introduction for a high school student, but the hope is that they will then pursue further education and training opportunities, whether it be at UChicago or one of the growing number of partner institutions investing in data science talent development and building on the lessons learned in the Windy City.

And if the program works as intended, those opportunities will include—and may someday center upon—social impact.

“Our goal is that the organizations have a great outcome, that the students have a positive experience, and ultimately that the students consider careers in data science for social impact,” she said.

The post UChicago Summer Lab Grows the Data Science for Social Impact Talent Pipeline appeared first on data.org.

That’s all it took for the Project AEDES team to take the seed of an idea and grow it into a working public health prototype that has caught the attention of NASA, UNICEF, and data science leaders around the world. 

And although the initiative—which stands for Advanced Early Detection and Exploration Service—now has more time, talent, and resources behind it, the sense of urgency that was born from the NASA Space Apps Global Challenge hackathon persists today.

“We were unified by a common cause. That’s what helped mold us into what we are now,” said Dominic Ligot, chief technology officer at CirroLytix, the data consulting company behind Project AEDES. “We all came from corporate backgrounds, so this was a great exercise in changing our thinking from how much money can you make to how much of a difference can you make. We weren’t used to this agile, fast-paced environment, and it’s stuck with us ever since. Now everything is a hackathon for us.”

The Challenge

In the Philippines, dengue fever is a public health emergency. Instances of the viral illness, which can be life-threatening, are up 58 percent in 2022 over the previous year, building on a consistent trend of high case counts and fatalities in the country.

The crisis was top of mind for the CirroLytix team in 2019 when they decided to sign up for the NASA Space Apps Global Challenge, a worldwide competition where teams have 48 hours to combine NASA and other data sources to solve a problem tied to the UN Sustainable Development Goals (SDG). At the time, still months before rumors of another disease called COVID-19 had begun to emerge, dengue was dominating the news in the Philippines. CirroLytix decided to center their hackathon project on tackling the issue, tied to SDG3: Good health and well-being.

It was a departure from their regular corporate and consulting work, but Ligot and his colleagues were looking for something more meaningful and fulfilling in applying their data science and technology skills.

“We asked ourselves, ‘How can we use data to solve human problems?’ and that’s what brought us into the hackathon space,” Ligot said.

With dengue, data was scarce. Information coming from local health departments was released on a significant delay, often by months, making it no longer actionable from a prevention and prediction standpoint. 

Project AEDES set out to close the gap, making data more actionable and giving public health officials a greater sense of when and where dengue cases would be on the rise. 

The Solution

Existing data on dengue cases in the Philippines was publicly available, but the team was disappointed to discover that it was in PDF format, not conducive for analysis or modeling.

Data scientist Claire Tayco had her work cut out for her. Right away, the team had to look at their 48-hour work back plan and factor in at least four hours of straight data entry. Tayco had never done a hackathon before and was six months pregnant at the time. She had her doubts that the data accessibility challenges could be overcome in such a tight timeframe.

Those initial doubts fueled her determination.

“At first, personally, I was hesitant because I didn’t know if I could do it. I wasn’t even concerned about winning at that time, but I did think, ‘this is something that matters. This is something that’s important’,” she recalled. “To be able to get it done within 48 hours felt quite rewarding.”

Once the case data was entered, NASA’s satellite imaging, paired with climate and weather data, became the key to unlocking the problem for Project AEDES. Dengue is spread through tropical mosquito bites, so humid weather and standing water create perfect conditions for spreading the disease. Satellite data identified areas already at high risk, exacerbated by current weather. 

With those predictive factors covered, the team wanted to integrate data that could aid in intervention, as well. They had read a case study on the use of Google search trends to identify outbreaks of the flu. Infected patients would search for their flu-like symptoms or search for treatments for flu, and the spikes in search terms would directly align with an increase in case counts. 

The same held true for dengue. 

And taken together, these datasets give public health officials a roadmap for predicting dengue and identifying possible disease hotspots.

“By the end of it, we had a working prototype which not only forecasted—but nowcasted—how many dengue cases there would be, way ahead of any official reports,” Ligot said. “It’s not just detection—it’s action.”

The prototype won, taking home Best Use of Data from a field of more than 29,000 people across 71 countries. As they further develop and enhance the tool, additional support has poured in. Project AEDES won an EO4SDG Award from the Group on Earth Observations in 2020, and in 2021 was recognized as a Digital Public Good by the DPGA Alliance and UNICEF Philippines. They’re currently working with the UNICEF Innovation Fund which, if they successfully move into phase 2, would lead to increased funding.

And Project AEDES is paying it forward for the sector, hosting its own hackathons and working with schools to cultivate data talent in the Philippines, where data for social impact is still in its nascent stage.

“If you build a road, people start going onto it,” Ligot said. “We’re helping others find the path to innovation.”

The Takeaway

Building a complex data solution in two days isn’t the typical path for product development, but it worked for Project AEDES. Starting in a high-pressure environment brought out the strengths of each team member and allowed them to build trust quickly, fostering a team culture where risk-taking, failing forward and acknowledging shortcomings or setbacks are encouraged. 

Reflecting on their journey over the past three years, Tayco said it’s ultimately the diversity of lived experience and area of expertise that has been the secret to their success.

“We gelled really well during the hackathon and even now, with all the enhancements, all the refinements we’re doing with the project, part of the reason it’s still alive is the people behind the project,” she said.

In the corporate world, where CirroLytix was born, sharing trade secrets is unheard of. Overcoming that mental block wasn’t easy, but the team has found that the collaborative, community ecosystem of data science for social impact has only served to increase opportunity for them, and especially for Project AEDES. 

They’re eager to share their lessons learned and provide the initiative as a jumping-off point for others. Other transmittable illnesses, like Zika, offer a window into other applications, as well as other sectors like agriculture and food insecurity, and disaster resilience.

“The same technologies can be applied and abstracted elsewhere,” said Mark Toledo, solutions architect and data engineer for the project. “We want to open source this solution for others to use or to develop something on top of it. All of these solutions should be available to everyone in the world and that’s how we see AEDES.”

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But for the benefit of whom? 

AI is booming, but its use is still limited, mostly to the elite. Addressing the needs of the poor using AI requires a holistic approach with empathy and altruism driving scientific temper and rigorous technology practices.  

Wadhwani AI was formed in 2018 to try to flip that reality, designing AI solutions that benefit underserved populations in developing countries. Working with government entities and global nonprofits, Wadhwani AI seeks to tackle some of the world’s most intractable problems where AI technology has the potential to be transformative.

The Challenge

Wadhwani AI works across agriculture and healthcare to develop and deploy human-centered AI solutions, including pest management for cotton farming, cough sound analysis technology to help identify at-risk COVID patients, and newborn anthropometry that provides early identification and intervention for underweight infants. 

In India, where the organization is headquartered, they saw the potential to extend AI solutions to eliminate a curable, preventable disease. In 2019 alone, the country reported 2.6 million new cases of tuberculosis (TB), representing more than a quarter of all cases in the world. 

How could AI solve this health crisis? That’s the question Wadhwani AI set out to answer.

“Our approach has fundamentally transformed from what was perhaps a research-first mindset to what is clearly an impact-first mindset,” said Alpan Raval, the chief scientist for AI and Machine Learning. “We are very focused on working backward from the potential impact of the work we do, and our innovations are also viewed from the lens of incremental effect on impact.”

That shift from research to application is an important one, both for Wadhwani AI and for other experts and academics. CEO Shekar Sivasubramanian believes organizations need to leave their comfort zones and better understand the applications and downstream implications of AI in the communities they serve.

“In applied problem solving, the challenge largely lies outside the lab and is attended to by multiple people with their own understanding of the problem. This is unchartered territory for most organizations, who may find it uncomfortable and scary to mud-wrestle the problems uncovered in the real world,” he said. “Limited attention is placed on themes such as explainability and trust, set aside for a later day. For applied work, however, all these matters relate to ensuring that users truly believe in the solution.”

Trust building, then, is a key challenge within the challenge of eradicating tuberculosis. 

The Solution

Wadhwani AI has developed a range of AI products to help close the gap between tuberculosis diagnoses and deaths. 

Their automated interpretation program uses AI to interpret blood test results to determine drug resistance to tuberculosis. Their work on detecting TB through ultrasound identifies abnormal features in chest scans. AI detects these abnormalities in an automated fashion and predicts the likelihood of the patient being positive for tuberculosis. They are developing a TB screening method using the patient’s cough sounds.

Particularly consequential in reducing fatalities, though, is their risk prediction project. Using a set of patient indicators like age, age, gender, location, and time interval between diagnosis and treatment initiation, they use AI to predict whether the patient will complete treatment, informed by corresponding outcomes for roughly half a million tuberculosis patients across the country.

And across all solutions, Wadhwani AI incorporates checks and balances, recognizing that AI alone is not a silver bullet. 

“We conduct extensive user research all through the lifecycle – in the data collection phase, and in passive and active evaluations phases,” said Vijayalakshmi Raghavan, Wadhwani AI’s director of solutions.

AI must often be used in conjunction with on-the-ground expertise, as well.

“Decision-making in healthcare has downstream consequences that may critically impact a patient’s well-being. Accordingly, our AI systems employ human-in-the-loop wherever possible, and our models optimize manual interventions so that human bandwidth is used where it is needed most,” Raval said. 

The Takeaway

In communities, Wadhwani AI wants to build trust. At the systems level, they want to help build capacity.

The World Health Organization has an ambitious National Strategic Plan to reduce tuberculosis deaths by 90 percent by 2025, and India’s Ministry of Health and Family Welfare has a Central Tuberculosis Division that is likewise focused on stemming the spread of the disease. Wadhwani partners with these kinds of government entities to maximize impact.

“Organizations interested in achieving scale must understand and respect the role that governments play,” said Sivasubramanian, explaining that, to increase efficacy, you must “make the government your best partner,” considering their intent and scale. “We must embrace the fact that the supporting ecosystems may be a ‘work in progress’, and learn to implement AI solutions in such an environment.”

Across government partners, donors, researchers, and direct program partnerships and support from global nonprofits, Wadhwani AI will continue to build AI systems that are sustainable and scalable in healthcare, agriculture, and beyond.

And at the end of the day, they hope this growing network of partners can help them bring the AI revolution into the homes and lives of billions more people. 

“We are conscious that we play a supporting role,” Raghavan said. “The solutions’ ultimate accolades—its smooth deployment and eventual success in the field—is owned by our partners.”

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