Diversity: Important, fair, and sustainable – but often overlooked in AI applications

In the era of digital transformation, the intersection of sustainability and AI has emerged as a critical area of research. My research delves into the intricate relationship between these two domains, highlighting their potential to shape a more equitable and sustainable future. One significant facet of this is diversity. But diversity, as a vital component of the social dimension of sustainability, is frequently sidelined in the discourse surrounding digitalization and AI, despite its potential to synergize with these technologies in forging a fairer and more sustainable world. Digital solutions frequently lack inclusivity and emancipation, exacerbating disparities in access and opportunity. AI tools, likewise, often perpetuate bias and inequality by being trained on homogeneous datasets, overlooking factors such as gender, ability, and ethnicity. To address this oversight, it is imperative to incorporate diversity and sustainability education into the training of future IT specialists and AI engineers. Developing ethical awareness and the ability to critically reflect on biases within AI systems is essential to avoid reproducing biases and stereotypical thinking. This is why my research emphasizes the urgency of recognizing diversity as a key enabler of fairness and sustainability within the digital transformation landscape.