Bridging Data and Innovation: UK Black Tech’s Mission to Solve Local Challenges
Harnessing Data for Change: Solving Local Challenges Through Innovation, Collaboration, and Ethical AI
The future of data-driven decision-making in the UK faces a critical juncture. While advancements in AI, machine learning, and open data repositories offer immense potential, barriers such as data silos, bias, and accessibility continue to hinder progress.
At the recent Tech Show London held at Excel, London, on March 13, 2025, UK Black Tech hosted a panel discussion titled "Let’s Address Local Challenges: Using Data Models to Make Informed Decisions."
Moderated by Marvalyn Omoyinmi, a project manager at UK Black Tech, the conversation tackled sector-specific applications, future workforce development, and policy frameworks necessary to harness the full potential of data in addressing local challenges.
A major issue facing the industry is the fragmentation of data models, which limits their effectiveness in providing holistic solutions for local communities.
Mark Martin, a data science and computer science lecturer, emphasized that "many data models exist in silos, are locked behind paywalls, or are highly secure, making them inaccessible for innovators who could use them to drive change."
Without structured frameworks that allow seamless collaboration between stakeholders, organizations risk losing valuable insights that could drive meaningful action.
Another critical concern is data bias and integrity. As Martin pointed out, "We need the information data to be quite diverse. If it's not, it won’t be applicable to the broader population."
This lack of representation in datasets leads to skewed insights that fail to address the needs of all communities.
Chinazor Vivian Kula, a resident technologist at UK Black Tech, added that "people see data as an asset rather than an insight, making them hesitant to share it." This hesitancy not only restricts knowledge exchange but also perpetuates disparities in access to technology-driven solutions.
Building Solutions Through Data Models
One of the initiatives discussed was the Sickle Cell Hackathon, an effort led by UK Black Tech that brought together medical professionals to develop AI-driven solutions for sickle cell anaemia patients in London.
"We were able to come up with a solution for preventing, predicting, and treating sickle cell cases more effectively," Kula shared.
The initiative demonstrates how data-driven models can be tailored to solve community-specific health challenges—a model that can be replicated across different regions and conditions.
Another successful initiative is the London Data Store, a public data platform designed to improve transparency and empower local problem-solvers.
Martin described its impact as follows: "It provides access to data across multiple sectors, such as jobs, healthcare, and community engagement, allowing researchers and individuals to drive solutions in their own industries."
These examples underscore the potential of open data ecosystems in fostering community-driven innovations. However, without structured governance and policy frameworks, the benefits of such initiatives remain limited.
Introducing UK Black Tech
UK Black Tech (UKBT) plays a crucial role in addressing these challenges by promoting diversity in tech, supporting innovation, and ensuring representation in decision-making processes. The organization collaborates with institutions, businesses, and communities to create equitable opportunities within the tech ecosystem.
UKBT’s primary mission is to foster the growth of underrepresented tech professionals by providing training, mentorship, and access to opportunities.
Initiatives like the Peckham Digital Access Zone have helped upskill over 200 Black professionals in digital technology, data science, and AI.
Kula highlighted the importance of this approach, stating that "education in data science needs to be project-based. It’s not just about learning theory—it’s about applying knowledge to solve real-world problems."
Scaling Up Data-Driven Solutions for Local Governments
One of the major takeaways from the discussion was the need to scale data-driven models for use in local governments. Martin pointed out that "there is a massive appetite for data scientists in the UK, but we must ensure that their skills are applied to solving real problems."
He encouraged aspiring data professionals to explore open-source platforms like Kaggle to practice with real datasets and develop industry-ready skills.
Moses Makola, a web developer specializing in large language models (LLMs), highlighted AI's growing impact on public services.
“One opportunity moving forward is how LLMs can help personalize services, especially in healthcare," he explained. AI-driven insights can improve patient care, optimize public resources, and enable governments to make informed decisions more efficiently.
However, Makola warned against blind reliance on AI: "People don’t trust what they don’t understand. If we don’t educate the public on how AI and data models work, scepticism will continue to grow."
Building public trust is just as critical as advancing the technology itself.
Balancing data transparency with privacy was another crucial discussion point. Kula stressed the need for standardized data formats across sectors, explaining that "if data collection is inconsistent, it becomes difficult to extract meaningful insights."
Establishing clear governance frameworks will ensure datasets remain accurate, unbiased, and secure while allowing for responsible innovation.
Martin added that "companies often struggle when migrating data from legacy systems to modern platforms."
Integrating synthetic data—artificially generated data that mimics real datasets—was proposed as a potential solution to address privacy concerns while maintaining the accuracy of insights.
The Future of Data-Driven Innovation in Local Communities
Looking ahead, the panelists stressed the need for collaboration between government agencies, private sector innovators, and educational institutions.
Martin emphasized that "data models must be designed to tell a story—one that reflects the lived experiences of local communities."
Without real-world insights, data alone cannot create meaningful change.
In response to an audience question about when machine learning should be used, Martin used a compelling analogy: "What's the difference between a microwave and an oven? You might get quick results from AI, but if you rely on it entirely, you lose the depth and quality that traditional data science provides."
The message was clear—AI should enhance problem-solving, not replace thoughtful data analysis.
The discussion ended with a reminder that the tech industry’s progress depends on responsible innovation, education, and inclusivity.
"If we don’t ensure that data science is accessible to underrepresented groups, we will keep reinforcing the same biases," Kula concluded.
Time for Action
The UK Black Tech panel at Tech Show London 2025 underscored a crucial reality—data is only as powerful as those who can access, understand, and use it. Without breaking down silos, eliminating bias, and fostering collaboration, even the most advanced AI and data models will fail to address real-world challenges.
Through bold initiatives like the Sickle Cell Hackathon, the London Data Store, and the Peckham Digital Access Zone, UK Black Tech is proving that data-driven solutions must be designed with and for the communities they serve. The future of tech in the UK depends on bridging the gap between innovation and local impact, ensuring that technology works for everyone, not just a select few.
Now is the time for action. Policymakers, educators, and industry leaders must create policies that protect data integrity while promoting accessibility, invest in diverse talent, and support ethical AI development. The power of data is undeniable, but its true potential will only be realized when it is placed in the hands of those ready to build, solve, and transform the world around them.