As an author, consultant and responsible AI champion, Heather Dawe’s work has taken her to global stages, including the World Economic Forum in Davos, where she has spoken about AI bias and the need for accountability in AI development. “AI is built from data, and data reflects society,” she explains. “Because we live in a […]
As an author, consultant and responsible AI champion, Heather Dawe’s work has taken her to global stages, including the World Economic Forum in Davos, where she has spoken about AI bias and the need for accountability in AI development.
“AI is built from data, and data reflects society,” she explains. “Because we live in a biased world, that bias is inherently present in our data, leading to AI systems that can unintentionally perpetuate prejudice.”
As a chief data scientist at technology consultancy UST Dawe works across multiple sectors, from retail to financial services and manufacturing, helping clients across Europe harness AI ethically and responsibly.
This commitment to responsible AI has led the data scientist to co-author a book on the subject with Dr Adnan Masood.
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“There seems to be a greater proportion of women working in responsible AI compared to the broader AI field,” she notes. “Perhaps that’s a reflection of the discipline itself, but ensuring a balanced workforce is critical to building AI that reflects society fairly.”
Dawe’s path to becoming a champion of responsible AI evolved after working as both a software developer and a civil servant following a maths degree.
For someone captivated by probability and its power to forecast future events, Heather Dawe faced an ironic uncertainty after earning her degree—she saw no clear path forward.
“I didn’t really know what to do next,” Dawe recalls.
That uncertainty led her to software development, where she landed a role at IBM, working on large-scale telecommunications systems. In those early years, she discovered the power of data and coding—especially when paired with analytics.
After nearly a decade as a programmer and software designer, she pivoted to the civil service as a government statistician and pursued a master’s in statistics. “This was before data science existed as a formal discipline,” she notes.
Her work took her to the Department of Health and later the NHS, where she helped apply machine learning at scale.
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More than 15 years ago, she began assembling one of the UK public sector’s first data science teams.
A key milestone was leading the development of NHS mortality indicators—machine learning models built on millions of NHS data points to provide critical insights into hospital mortality rates.
Though the work was complex and politically sensitive, Dawe emphasises its impact: greater transparency and, ultimately, better patient care.
Dawe’s passion for data science and AI continued to evolve, leading her to cofound a consultancy focused on AI and machine learning. She later moved into the insurance sector before joining UST, where she now leads AI and data science development across the UK and Europe.
Making an impact
Reflecting on her career, Dawe highlights several key achievements. Beyond her NHS work, she takes pride in her role as a leader and mentor in AI.
Publishing a book on responsible AI was a milestone, as was speaking at Davos—an experience she says is still “sinking in.”
At UST, she and her team are refining proprietary large language models, fine-tuning them with client data to deliver tailored AI solutions.
“There’s a lot of excitement around generative AI,” she notes, “but we’re also seeing renewed interest in traditional data science, as businesses realise older techniques still hold immense value.”
Dawe views AI as a blend of creativity and mathematics. Outside of work, the polymath channels her creativity into painting and writing. “Mathematics itself is creative,” she says. “Balancing analytical thinking with creative expression helps me stay focused and motivated.”
Raising visibility in the sector
Her advice to other women in technology is to trust their abilities and speak up. “I’m naturally introverted, and it took me a long time to believe in my own perspective and capabilities.
“When you’re in a minority, it’s easy to doubt yourself, but your ideas and viewpoints are just as valid as anyone else’s,” she adds.
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Dawe takes her role as a woman in tech seriously, seeing representation as a catalyst for change.
“As a technology leader, I realised I had a responsibility to be visible,” she says. While she doesn’t believe women in tech should feel obligated to take public roles, she knows visibility can inspire the next generation.
“I speak in schools when I can because I want young people to see that AI and technology aren’t just for one type of person. Diversity strengthens the field.
The future of AI
Looking ahead, Dawe remains both optimistic and cautious about AI’s trajectory. “AI is already transforming society, and its influence will only grow,” she says. “But as technology advances, ethical considerations must keep pace.”
Whether through consulting, writing, or advocacy, her goal is to ensure AI benefits everyone. “Fairness and responsibility must be at AI’s core,” she emphasises. “That’s the only way it can truly serve society.”
As AI evolves, leaders like Dawe will be key to shaping it—not just as a powerful technology, but as a force for ethical and positive change.
TechInspired’s key takeaways
Embrace uncertainty and growth: Dawe’s career path wasn’t linear. She transitioned from software development to government statistics and then AI leadership. Her journey highlights the value of adaptability and lifelong learning.
Trust your voice and perspective: Dawe acknowledges the challenges of being in the minority as a woman in tech, but emphasises the importance of self-belief and speaking up.
Representation matters: While not every woman in tech needs to take on a public role, seeing diverse leaders in AI helps break stereotypes and encourages more women to enter the field.
Ethical AI needs diverse voices: AI reflects societal biases, making it crucial for a diverse workforce to shape its development. Women in AI, particularly in ethical AI, play a key role in ensuring fairness and accountability.
