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How AI can make tech more inclusive
You will have read and heard a lot about AI in recent time and how it will change our lives forever, not necessarily for the better - perhaps even wiping out mankind altogether.
That might be a bit far-fetched, but the technology is not without its flaws. One of the most pressing concerns is the potential for AI systems to perpetuate and even amplify biases. If AI models are trained on biased data, they may produce discriminatory outcomes that could negatively impact marginalised communities. Even worse, more than half of the content available on the internet has been touched (or even entirely created) by AI, so AI models are trained by content created by other AI - so biased AI solutions could influence other models negatively. To unlock the full potential of AI and ensure that its benefits are equitably distributed, it is crucial that AI systems are developed with inclusivity in mind by diverse teams and trained without bias.
Inclusive AI refers to the practice of developing AI models that are fair, transparent, and accessible to all, regardless of race, gender, socioeconomic status, or other factors. By removing biases from the data and algorithms used to train these models, inclusive AI has the potential to break down long-standing barriers in various sectors. In order to achieve this, AI researchers and developers must prioritise fairness at every stage of the AI development process, even if this means longer development cycles and higher cost.
Bias in AI models often originates from the data that is used to train them. If the training data reflects historical inequalities or lacks diverse representation, the AI model will mirror those same prejudices. For example, facial recognition technology has been shown to perform less accurately for people of colour and women, largely because the datasets used to train these models were predominantly composed of white, male faces. Similarly, AI models in hiring systems have been criticised for favouring male candidates over female candidates due to biased data inputs.
To combat this, developers need to ensure that AI training datasets are diverse and inclusive, representing a broad spectrum of demographics, experiences, and contexts. That means that human oversight is needed to intervene if algorithms show bias.
The positive impact of inclusive AI can be seen in several areas. In healthcare, for instance, AI has the potential to improve diagnosis accuracy across all populations, including underrepresented groups. Similarly, in the criminal justice system, inclusive AI can help create fairer systems by eliminating biases in sentencing or parole decisions. When AI is trained to be inclusive, it can empower individuals, promote social justice, and drive progress toward equality.
Tech is one of the least diverse industries. If we look at software development as the traditional stepping stone into the sector, 92% of developers globally identify as male and only 3% of UK tech workers identify as black - AI-empowered solutions like Apto.ai can make tech more accessible to a wider (and more diverse) audience which in the end will benefit us all as users of technology.
techUK’s TechTogether campaign, taking place throughout March, is a collection of activities highlighting the UK’s technology sector pursuit to shape a more equitable future. In 2025 we are exploring: Inclusive AI, investing in diverse founders and entrepreneurs, the power of allyship and mentorship, and empowering young people.
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Björn Schwarz
Björn Schwarz is the Managing Director of Apto.ai. Apto.ai is a Generative AI-powered No-Code platform designed to empower developers—especially those with limited coding experience—to build enterprise-grade digital solutions. After working in banking and as a management consultant, he has been in tech for a decade.