A Launch Met with Enthusiasm

The WHO event was the ideal platform to unveil Epiverse in Africa, bringing together a diverse audience of global health leaders, innovators, and policymakers.

One of the most inspiring outcomes of the official launch was the level of interest from strategic partners eager to join the journey. Representatives from countries across Africa expressed their interest in adopting Epiverse and integrating it into their national health strategies. There was a shared recognition of the need for initiatives like Epiverse to address diverse health challenges like epidemic preparedness and healthcare optimization by reimagining solutions and methods.

Collaborative Opportunities

Beyond the launch, the event highlighted exciting opportunities for collaboration, including:

• Local Data Solutions: Tailoring Epiverse tools for specific regional needs. This can only be done by working closely with local experts and communities to adapt our interventions. And this echoes our data.org approach of thinking globally, but working locally.
• Capacity Building: Empowering regional hubs to ensure local ownership and equipping local professionals and communities with skills to facilitate the Epiverse adoption and maximize its impact.
• One Health Approach: Aligning efforts with other social impact organizations (SIOs) working in animal and environmental health.

These discussions laid the groundwork for transformative partnerships and innovations.

Looking Ahead

Our plan for Epiverse’s next phase of broader adoption is ambitious yet focused: “Roll out the suite of tools in 10 African countries as part of the initial implementation”. To ensure success, we will prioritize local engagement, working closely with government bodies, local data practitioners, and key stakeholders to understand each country’s needs and/or challenges.

We are also committed to localizing training and fellowship programs to build the capacity of professionals on the ground, empowering them to champion Epiverse’s adoption. By equipping local leaders with the knowledge and tools they need, we aim to create a sustainable model for long-term impact, led by those closest to the issues at hand.
As part of this effort, we are excited to announce the launch of the Epiverse Fellowship Program in Q1 2025. This program provides an opportunity for professionals to develop their expertise, collaborate with global peers, and drive the adoption of Epiverse in their respective countries and communities.

Together, we can harness the power of data and technology to address past and present challenges while anticipating tomorrow’s needs. Our shared goal is to create a healthier, more equitable world and foster a resilient, inclusive approach to global health security.

The post Catalysts for Change: Building the Future of Public Health Intelligence appeared first on data.org.

And across the board, all are looking for rigorous global capacity-building efforts to meet their aligned needs. 

That call to action, which is equal parts challenge and opportunity, was at the center of our Generative AI Skills Challenge, powered by data.org with generous support from Microsoft. With 581 applications received across 93 countries, it is clear that the scale of potential is tremendous. 

“We were truly inspired here at Microsoft as we watched the projects unfold,” said Greg Bianchi, the director of partnerships at Microsoft Philanthropies. “Our team is really committed to partnerships that create opportunities in the digital economy–and particularly in the AI-enabled economy–and we seek to do that work to democratize access and provide opportunities in historically excluded populations.”

Microsoft joined data.org in sponsoring the challenge, with valuable capacity-building workshops and coaching resources provided by EY to the network of applicants. 

The five organizations that were ultimately selected–Data Elevates, The Tipping Point, GIEVA, Mississippi AI Collaborative, and Myna Mahila Foundation–represent some of the best ideas and strategies in the field, and they came together for a recent webinar to discuss the lessons learned throughout the process.

Trust (to Start) the Process

The power brokers leading the AI revolution remain, in large part, in the global north. So, it is not surprising that many communities outside of that privileged group do not immediately trust the technological tools and solutions being developed without their input. 

“Generative AI has the potential to revolutionize how we tackle global challenges thanks to its unparalleled ability to scale, but only if it is applied with a strong emphasis on community-led solutions that are informed by local context,” said moderator Uyi Stewart, the chief data and technology officer at data.org. “Trust is a key component of each of the awardee projects.”

From the get-go, the Generative AI Challenge sought to engage and empower a more diverse cross-section of leaders. Our awardees embraced that challenge and took thoughtful steps to acknowledge fears and build trust. Of the 4,712 people trained in total, 87 percent identified as women or non-binary, and an incredible 95 percent are at risk of exclusion from the digital economy. 

“Historically in Nigeria, when new technology comes into the system, there is a lot of resistance from everywhere, especially digitally connected technologies,” explained Dr. Daniel Newton Obaka, the president and co-founder of Global Integrated Education Volunteers Association (GIEVA), which is training and upskilling women entrepreneurs in northern Nigeria on the use of generative AI capabilities to create digital livelihoods. 

The Truth Will Set You Free

Part of building and maintaining trust is anchoring in honesty. 

Newton Obaka spoke about the importance of recognizing the risks, limitations, and ethical pitfalls of generative AI, a message that his fellow awardees reinforced. Their projects each include training on the fundamentals of the technology, improving digital literacy, comfort, and confidence before pushing the limits of how AI can be applied and stretched. 

“Part of our role is to show people how AI is working at the base level and under the hood,” said Rob Segan, co-founder and head of technical direction at Data Elevates, an organization skilling Venezuelan migrant women on generative AI through a Massive Open Online Course (MOOC). “The more we show people what it is and how it works, the concerns they have shift to enthusiasm.”

Building enthusiasm, he continued, is dependent in part on tailoring skill-building and problem-solving to the local context and the real problems marginalized groups are facing in their communities. Regularly asking questions about current needs and applications informs both program design and the outreach and recruitment strategy to identify the future DSI workforce. 

“As a mission-driven organization, it’s really important that the power that’s coming with generative AI isn’t just going to people in cities or people with graduate degrees, but it’s also going to people that we work with, like marginalized populations and women and migrants and people working in rural areas,” he said. 

Tools to Harness Technology

The Tipping Point (TTP) provides in-depth training, thoughtfully curated prompt libraries, and generative AI-enhanced mentoring to educators in remote settings in Greece. Yiorgos Nikoletakis, the CEO of TTP’s partner organization, 100mentors, said that they, too, are working with marginalized populations and those who are at risk of exclusion from the digital economy. What he said makes this technological revolution different, though, is that those communities can more easily and quickly be brought up to speed.

“Is AI categorically better than other tech solutions? Yes. The profound answer is that it has no technical prerequisites for the users. It’s the first technology that you can use only your natural language,” he said.

In his case, generative AI is getting better at recognizing the Cretan dialect by the day, improving adoption and trust in his participants, many of whom are over 50 and self-proclaimed “technophobes.” 

The need for better source data from underrepresented languages is a widely agreed upon challenge to improving equity in generative AI. Tanvi Divate, co-founder of Rani Jobs at the Myna Mahila Foundation, said local language and context not only improve AI tools, but increase the chance for trust, adoption, and potential interest in starting a new career. Myna Mahila is training their network of women Rani workers in generative AI to power a text-based AI platform designed to dispel misconceptions about women’s health.

“By offering such a confidential and reliable AI tool, we are creating a safe space for women to not only access information and seek healthcare services without the fear of judgment but also for them to upskill in this new age technology,” she said. “Women in India are constrained by social norms and household responsibilities… we provide this flexible work from their homes or hyper-local offices that we have built in these communities.”

Because to meet the global demand for generative AI skills and build the workforce, the Generative AI Skills Challenge awardees know that traditional skilling and pathways are not going to suffice.

“When we were thinking about what an AI career looks like, we realized that AI will be integrated into all careers,” said Dr. Brittany Myburgh, an assistant professor of art history at Jackson State University, one of the partners in the Mississippi AI Collaborative that is developing an AI ecosystem, including an apprenticeship program and intensive AI curriculum program for teachers, students, and businesses. “Rather than building a career pipeline in AI, it was important to focus on a knowledge pipeline to upskill everyone in Mississippi in generative AI and meet them where they’re at.”

To learn more about the projects and reach of our awardees, watch the webinar and explore Skilling that Scales: The Generative AI Skills Challenge Impact Report.

The post Trust, Truth, and Technology: How Our Generative AI Challenge Awardees Are Leveraging the Power of AI appeared first on data.org.

How will we respond when the next crisis hits? 

To ensure that we are better prepared when that time comes to collect, share, and take action informed by data, we launched Epiverse, a collaborative to develop a trustworthy data analysis ecosystem. This system of standardized, easily accessible epidemiological software tools, is making exciting progress toward strengthening our resilience and response in the global fight for public health. 

Using GitHub—a collaborative development platform for creating, storing, and managing code—we have more than 15 packages available. The design of these free-to-use, open-source tools was informed by methods and analysis used successfully in epidemic response to infections including cholera, COVID-19, dengue, diphtheria, Ebola, influenza, and Zika. Three of the packages are available on the Comprehensive R Archive Network, or CRAN, making them more easily accessible and proving their high quality, and have been downloaded more than 21,000 times, and three are certified as digital public goods by the Digital Public Goods Alliance.

In other words, the Epiverse ecosystem is growing by the day, and we are committed to making it accessible and actionable for our likewise growing network of partners. The Epiverse community launched ​​training materials to support the adoption of computational tools in epidemiology and hosted an in-person training event in Colombia.

To further expand our reach, we are excited to announce a new partnership with RECON and rOpenSci. RECON delivers a collection of epidemiological tools that provide key building blocks and methods for the Epiverse ecosystem. rOpenSci brings over a decade of expertise in creating software standards and managing code and community through its unique software peer-review process.  As part of this partnership, rOpenSci will work with Epiverse developers to produce sustainability strategies for the software suite, including growing the user and contributor base, training skilled maintainers, producing developer documentation, and planning for governance and knowledge transfer. rOpenSci will also use its expertise in multilingual software development to help make Epiverse more accessible to non-English users and contributors. 

At data.org, we think a lot about the best ways in which we can contribute to an ecosystem of digital public goods and build purpose-driven data capacity for the social impact sector. Through our training, resources, webinars, and cross-sector partnerships, we aim to advance the growing community of people and organizations doing good work to harness the power of data and deploy it for social impact. With RECON and rOpenSci in our corner, we are in an even better position to do just that. 

The post Forging Partnerships and Accelerating the Field: New Epiverse Partnerships with RECON and rOpenSci appeared first on data.org.

In data.org’s landmark report, Workforce Wanted: Data Talent for Social Impact, we explored this explosive growth in demand for purpose-driven data talent across nonprofits, research organizations, educational institutions, advocacy coalitions, and beyond. The field is growing rapidly, with new roles consistently emerging across sectors.

We are committed to helping to fill those roles with a pipeline of diverse, interdisciplinary data practitioners.

That was the inspiration behind our Capacity Accelerator Network, a global community committed to building the field. With accelerators based in the United States, India, Africa, and soon Singapore, CAN is driving data for social impact in financial inclusion and the intersection of climate and health through training, curriculum development, and experiential learning opportunities with a key focus on inclusion, diversity, equity, and accessibility (IDEA).

We also see a worldwide demand for people to fill roles in large distributed projects creating integrated and generalizable community-driven software, a need that has become more visible through our Epiverse collaborative. Over the last two years, researchers interested in data science tools for public health and epidemiology have been working together on the Epiverse-TRACE (Tools for Response, Analytics, and Control of Epidemics) research project.  From Bogota to the Gambia to Berlin, the teams work together to change how analytics are used in global infectious disease response.

Through our involvement with Epiverse-TRACE, the data.org team sees firsthand the need for skilled data science practitioners, and also has identified the need for social science, communication, and translation roles geared toward improving the interaction between developers, users, and other stakeholders. These are some of the roles we hope to continue to identify, design, and feature here as part of our commitment to field building.

Finally, we know we are in an environment with roles that are new, or being performed without formal recognition.

The social sector has become increasingly digitally mature, but digital public goods are often built without the unique challenges and opportunities of social impact in mind. As a global convener and thought leader in data and AI, we at data.org believe that we need to acknowledge and name a role in the social sector called the “data ecosystem designer” that is charged with creating the data ecosystem that allows digital public goods to thrive and scale in the social sector. These data ecosystem designers are akin to city planners, as we describe in a recent blog post. As we collaborate with social impact organizations globally, we will help support new and unrecognized roles and what they may accomplish to drive change in the future. 

For individuals in the workforce who are energized by the idea of being that force for change, we are excited to share the new data.org jobs board.

Our curated jobs board taps into our expansive network, connecting data professionals with organizations doing good work around the world. Because that is our primary focus: jobs that drive impact. From entry-level to senior positions, job seekers will find meaningful career opportunities, and social impact organizations will connect with the field’s most qualified and passionate candidates. We are approaching this resource in a way that is both targeted in its focus on quality DSI opportunities, yet also open-minded, recognizing that DSI jobs of the future can be in any sector and, quite often, will require interdisciplinary experiences and skills. As we explore the world and tackle challenges through the lens of data and AI, we must remain open to approaches we have not yet considered and roles we have not yet imagined.

This jobs board is not a catch-all for every posting with even a passing reference on data or AI. This is a carefully vetted and intentionally curated resource that will make it easier for top talent to find high-quality jobs that fuel purpose-driven careers. 

Purpose-driven careers like those profiled in our Pathways to Impact series. Jacqueline Chan, for example, is the senior director of data and evaluation at the United Way Bay Area, a regional nonprofit that brings together partners from the nonprofit, business, and government sectors to address poverty in the greater San Francisco area. Hers has been a long and winding road to get into DSI, but each stop along the way has moved her closer to what she now considers a calling. Or like Linda Kamau, the executive director of AkiraChix, a social impact organization that provides young women in Africa with skills to compete economically and bridge the gender gap in technology. Linda saw the gender barriers firsthand when she started her career as a software engineer, and she made it her mission to open opportunities for other women in technology.

To do good work, we need good people. Good people with the right skills and a shared commitment to and passion for social impact. If you’re one of those people, you know someone who is, or you have a job opportunity that you think belongs on the Jobs Board, check out the listings or send us a message.

Together, we can build a stronger, more diverse, and more collaborative field of data for social impact.

The post Uplifting Talent and Driving Demand: Building the Data for Social Impact Workforce Together appeared first on data.org.

And the students aren’t the only ones getting an education.

The eight institutions—University of Chicago, California State University Fresno, City Colleges of Chicago, Howard University, Morehouse College, North Carolina State University, University of Illinois Chicago, and University of Texas San Antonio—are members of the US branch of data.org’s Capacity Accelerator Network (CAN), a group of like-minded organizations around the world that are committed to building a more diverse pool of talent and training one million purpose-driven data practitioners by 2032. 

Playbook

Data Science for Social Impact in Higher Education:  First Steps

Leaders from the US CAN, which launched in 2022, hosted a webinar to discuss the release of the Data Science for Social Impact in Higher Education Playbook. The playbook is a comprehensive resource to capture best practices and lessons learned from their work to date and help organizations beyond the network to apply findings to their own unique context. 

“Together, this all-star team implemented data science courses, degree programs, and trainings at their respective universities. They learned from one another and supported one another,” said Priyank Hirani, associate director of the Capacity Accelerator Network and host of the webinar. 

Hirani was joined in the session by Dr. David Uminsky, executive director of the Data Science Institute at UChicago; Dr. Mario Bañuelos, associate professor and associate chair in the math department at California State University, Fresno; and Kate Connor, professor and Aspen Rising President Fellow at City Colleges of Chicago.

Each of the speakers underscored the importance of partnership and collaboration in advancing and accelerating data for social impact (DSI) in higher education. 

“I was able to learn so much and we were able to do more at the University of Chicago—and do it better—because we had such a strong network,” Uminsky said.

From an infrastructure perspective, Uminsky and his team at UChicago have a head start on many educators and institutions looking to scale up data science. The university’s Data Science Institute has grown exponentially in recent years, and data science is on track to become the fifth largest—and one of the most diverse—majors on campus. 

Attracting a more diverse group of students to the field, though, is a work in progress. Reflecting on his own time as a math student, Uminsky recalls a homogenous group with limited career options. UChicago is trying to flip that narrative through CAN participation and the Institute’s Summer Lab initiative, an immersive, 10-week paid summer research program that has been a template for other CAN partners. 

Recent PhD graduates hired by UChicago are developing a deeper understanding of data for social impact, and are now adding teaching capacity for other partners like City Colleges of Chicago. It’s a win-win, giving these early-career professionals meaningful teaching and inclusive learning experience, and allowing other institutions to offer new training and coursework that would otherwise not be possible with their current faculty.

“We just truly did not have the instructional bandwidth and that’s a common challenge in community colleges. In an emerging field it can be difficult to hire because the pay is higher and we just can’t match pay in industry,” said Connor, whose City Colleges created a data science course taught by UChicago preceptors. “In this partnership, we learned, and then we would implement, and then we would discuss and adjust. That kind of grace in curriculum development can be difficult to do in a system that has tight structures around curriculum. It really helped us be successful in implementation.”

Fresno State was also able to add course offerings thanks to their CAN participation, but Bañuelos cautions that you need to build support and enthusiasm across departments for the work to be successful. His proposal for adding a minor, which is currently under consideration by the university, engaged eight different departments and broke down silos so that prerequisites could be included and stacked from across departments.

“We really wanted it to be an interdisciplinary effort and we wanted it to be accessible to multiple students—not just students in computer science or just students in mathematics,” he said.

Starting with that question—which students have access and which students need support to gain access—is where Connor believes all institutions must begin their journey.

“I would challenge our universities and our colleges to think about who is sitting in the classroom. How are you integrating your students’ ways of knowing and understanding the world into your data science training?” she asked. “That’s how we can create a field that approaches a discipline in a more comprehensive way. If we just have the same folks who always do this work doing the work, we’re not going to have the big social impact we’re hoping for.”

Students can be the best ambassadors for the programs, as long as the content feels relevant and engaging. Uminsky called on the STEM fields to do a better job of attracting students and illustrating career paths that are grounded in social impact and social justice. Students, he said, must be able to see and imagine a future that is financially secure, as well as personally meaningful.

“We need to give people the authentic opportunity to work on problems they care about. We don’t want any data scientists graduating from the University of Chicago unless they’ve worked on a real-world data science problem,” he said.

Through the summer lab and other CAN partner programming, students invited from all eight CAN partner institutions are paired with community-based organizations to tackle social problems like financial inclusion, gender equity, and climate change. They collaborate with network partners and community leaders to understand the challenges faced by different stakeholders, and then co-create a potential solution through data science. Those experiences are reflected in the playbook, where users can explore details on courses and modules, internships and research, events, and activities, partner outreach, and other key elements that may inform their own program development. 

The challenges faced by communities—and then explored by purpose-driven data scientists—are diverse and ever-evolving. As the Capacity Accelerator Network evolves in kind, its members are eager to continue sharing their work through mechanisms like innovative programs and resource-rich playbooks to the benefit of colleges, universities, nonprofits, and emerging professionals eager to accelerate social impact.

The post New Higher Ed Playbook Offers a Data for Social Impact Roadmap appeared first on data.org.

“Today, we stand at the edge of possibility.”

That powerful imagery from Dr. Ronda Železný-Green, program director of the Capacity Accelerator Network at data.org, kicked off a globally-attended webinar to release a first-of-its-kind new report, “Workforce Wanted: Data Talent for Social Impact.”

Workforce Wanted is informed by a review of 200 data talent initiatives around the world, 90 articles and reports, and more than 30 expert interviews, led by data.org and The Patrick J. McGovern Foundation, in collaboration with Dalberg and with support from the Mastercard Center for Inclusive Growth. 

Železný-Green points out that while social impact organizations are at the forefront of serving communities and improving lives, they continue to lag behind the private sector when it comes to using the power of data to advance change. Leveraging that power is the motivation behind the report, which speaks to the challenges and opportunities, success stories and gaps that must be addressed to create a stronger and more diverse talent pipeline to lead this work forward.

“The report shows the critical need and the tremendous opportunity for global data talent to enable the social sector to harness the power of data to solve the world’s most pressing problems,” said Mamadou Biteye, executive secretary for the African Capacity Building Foundation and moderator for the event. 

In the next decade, there could be as many as 3.5 million job opportunities in data science for social impact in low- and middle-income countries. But to get there, there is a lot of work to be done. 

An Emerging Field at a Crossroads

When Claudia Juech, vice president of data and society at The Patrick J. McGovern Foundation, started on this kind of work five years ago, the conversations in the field were still heavily focused on the ‘why.’ Why is data science important? Why should we invest? 

The case has been sufficiently made, but social impact organizations continue to struggle with the ‘how.’ 

“We are now shifting. Now it is about ‘where is the talent that we need to do that work?’” Juech said. “‘How do we implement?’” 

In particular, organizations are often missing the ‘who.’ They lack the people power to maximize the use of data. Existing staff don’t have the skills, and attracting talent is difficult when competing with private sector peers that often advertise higher-paying jobs with bigger teams and more extensive records of data science investment.

“Through this report, our goal was really to articulate and better understand where the field is today and the scale of the opportunity ahead,” said Ginger Zielinskie, senior advisor at data.org, a lead author of the report, and a former social impact practitioner who has long seen the looming gap with data science staffing. “Talent continued to come up as an underpinning of each challenge we sought to solve.”

The Workforce Wanted project team identified four pathways to expand the talent pool in data for social impact:

1. New talent, or attracting early career professionals into the field through educational and workforce development pathways. Traditional programs often lack exposure to the social impact sector, so forging those connections is key.
2. Existing talent, or upskilling and reskilling workers who are already in the sector. They have already opted into mission-driven work. With the challenges around attracting and retaining this talent already solved, what can it look like when you give them opportunities for growth and development in data science? 
3. Transitional talent, or creating on-ramps that allow for greater exposure and access to employment opportunities. Hands-on fellowships, short courses, volunteer opportunities, and rotational leadership programs are all examples of how to support this pipeline.
4. Leadership, or helping those at the top of organizations to commit to the change process and implement meaningful approaches to build data-led cultures. 

Early on in the webinar, attendees were asked to identify the most important pathway, and the results were compelling. The four pathways  were neck and neck at 25, 24, 23, and 28 percent, respectively. 

In other words, they are seen as equally important, illustrating how much work has to be done across the board. 

“I was absolutely surprised by how early we are; by how much information and knowledge we still need to uncover and gain and aggregate and share and learn from,” Zielinskie said. “We have not yet used data and data science to our fullest potential. The opportunity is so massive.”

Finding the Right Talent

In an exhaustive review of the data talent landscape, the Workforce Wanted team heard over and over that there were not enough data talent professionals. More educational and training opportunities are needed, including university degree programs. Greater investment is needed to improve a growing number of ​​non-traditional training models, including massive open online courses (MOOCs), which have demonstrated varying degrees of efficacy. Leadership needs the opportunity to train and develop themselves in order to scale up what works and create institutional buy-in. And across all of these efforts, organizations must also consider the digital divide, and which communities do—or do not—have access to foundational tools like the internet and technology.

It isn’t just a question of having enough talent or enough training, either; it’s a question of having the right talent.

“The social impact sector sees the potential to use data and data science more effectively to tackle literally the hardest problems in the globe. The question is how do we use this powerful tool responsibly?” Zielinskie asks, calling out the most important theme of the report: lack of diversity. “If we actually want to build equity-centered data science solutions, we have to be proactive in focusing on building an inclusive and diverse workforce.”

The values of inclusion, diversity, equity, and accessibility (IDEA) are generally acknowledged as important, yet not enough has been done to embed them in the field in a meaningful way. When considering the strategies listed above for expanding workforce development, Juech points out that these strategies must be developed in a way that specifically addresses attracting and retaining more diverse talent.

“It’s important that we think about diversity of data professionals because we know that data fairness is better achievable if the people who work on data, clean data, analyze data, really represent the communities and the contexts where the data originates from,” she said. 

In 2021, The Patrick J. McGovern Foundation invested more than $10 million in workforce development initiatives, focusing heavily on working not just with individuals, but with teams and organizations. This nuance is important, as it ensures that capacity building does not live with a single person; it becomes integrated into systems and is therefore more sustainable. It shifts from individual projects to systems-level thinking. 

That intentionality, Juech adds, is essential at every stage of the process. She often hears leaders say, for example, that they post data talent jobs but do not receive applications from candidates from historically underrepresented communities. Organizations must take responsibility and hold themselves accountable, expanding outreach efforts and peeling back the onion another layer to ask what other benefits, flexibility, or support could make a position more attractive for both external and internal candidates.

“Be intentional about who you hire, who you promote, and who you offer growth opportunities to in nonprofit organizations,” she said.

Putting Money Where Your Mouth Is

Building capacity requires intentionality. It also requires investment. Funders must ask organizations about the makeup of their teams and begin to distribute funds to signal that this isn’t just a nice to have—it’s a priority. 

At the organizational level, that can be a harder decision than it seems. When presented with a choice between providing direct services to communities or investing in digital infrastructure and data capacity, Zielinskie understands why data science often takes a back-burner.

But an investment today can yield dividends in the future.

“To train this next generation of talent to develop mechanisms to support the upskilling within organizations, to build clearer and porous pipelines between the technology sector and the social impact sector, and to support leaders in driving this transformation, we have to get real about the capital required,” she said.

She and Juech and the rest of the Workforce Wanted team are hopeful that this report will help spark an increased investment, and improve coordination across academia, philanthropy, social impact practitioners, and partners in the tech for good space. There are emerging bright spots, and wherever there is a lesson to be learned, it’s essential that best practices and effective strategies be shared. 

The momentum is growing, as long as cross-sector partners are willing to double down and get serious about building a stronger and more diverse talent pipeline.

“Be curious about what the data has to really tell you,”Zielinskie said. “Be agile enough to evolve and opportunistic enough to take advantage, and we can drive this change forward.” 

To learn more about building data talent capacity, watch the full webinar online and download and read the full report, “Workforce Wanted: Data Talent for Social Impact.” You can also access the data.org Resource Library, and get your organization started with the data.org Data Maturity Assessment.

The post Workforce Wanted: Data Talent for Social Impact appeared first on data.org.

Today, in concert with the launch of  The University of Chicago (UChicago) Data Science Institute (DSI), we are delighted to announce seven new higher education partners committing to drive social impact through data science. This group constitutes the first hub in data.org’s Capacity Accelerator Network (CAN), and focuses on financial inclusion to address systemic issues of inequity. The collective goal of this consortium is to generate new pathways out of poverty for college students from low-resourced communities and increase the data science pipeline for social impact organizations collaborating with these students. We are honored to welcome our new partners into the data.org network. They are: 

• California State University, Fresno
• City Colleges of Chicago
• Howard University
• Morehouse College
• North Carolina State University
• The University of Illinois at Chicago
• University of Texas, San Antonio

These partners bring broad, interdisciplinary expertise—spanning from social policy to data science—to the challenge of financial inclusion. The consortium includes historically Black colleges and universities (HBCUs), minority-serving institutions (MSIs), Hispanic-serving institutions (HSIs), and community colleges, among others. As an organization committed to IDEA (Inclusion, Diversity, Equity, and Access), data.org was pleased to partner with UChicago to identify these seven partners. These leading institutions represent different geographies and populations across the US, and share both a vision and a strong track record in developing highly qualified students, with priority focus on women and minorities for careers in data science or STEAM fields.  

Collectively, this financial inclusion hub will create an open curriculum, tools, and a model for experiential data science education that scales across diverse higher education institutions across the globe. While UChicago will play a key leadership and organizational role in this initiative, all consortium members will have an equal and powerful voice and make essential individual contributions, such as drafting data science apprenticeship models, developing co-curricular experiences for students, piloting experiential learning courses, and collaborating with local organizations to apply data science skills to local issues. This approach builds on the findings of our RECoDE report, which emphasized the critical need for data-driven solutions to be co-created with the communities they serve. All partners will engage regularly to share their work, ideas, successes, and failures as they drive data science for social impact at their own institutions. As each partner works within different communities and contexts, the learnings from their collective experiences will be shared and integrated into the open curriculum. 

A Platform for Partnerships, In Action  

As a neutral platform for partnerships, data.org is uniquely positioned to provide support across several areas critical for the initiative’s success. Earlier this spring, we announced funding from the Mastercard Impact Fund for data.org’s Capacity Accelerator Network (CAN), including an award to UChicago to steward this consortium of higher education partners. Through the data.org network, we connect academic institutions interested in data science for social impact with funders, sector experts, and leading social impact practitioners to ensure programmatic sustainability and scale. 

Crossing Sectors to Scale  

We are proud to announce this first milestone in building a consortium of partners committed to developing, refining, and deploying open data science curricula for social impact. Through piloting the curricula and playbooks, we are excited to see the reach of each partner’s contribution, from educating individual students to working with local social impact organizations to ultimately effecting meaningful and equitable change at leadership and policy levels. The challenges we face as a society are systemic, interconnected, and complex, and only by bringing together different disciplines, sectors, and perspectives can we build solutions that scale for everyone, everywhere. 

The post 7 New Partners Join UChicago to Fuel Data for Financial Inclusion appeared first on data.org.