Semester 2, academic year 2024/2025
By Jasmin Daniele An
The recent years showed a rapid growth in the use of artificial intelligence (AI) in various areas, such as recruiting, healthcare and marketing. With the increasing use of AI in gathering information and decision-making, concerns arise regarding potential biases embedded in AI systems that might result in unfair outcomes. Contrary to the common belief that algorithms are objective, AI systems can introduce biases influenced by human cognitive biases that might reflect and further amplify existing social inequalities and harmful stereotypes. This disproportionally affects marginalized groups.
On the other hand, previous studies also show that human judgement is inherently flawed and prone to biases, whether intentional or unconscious. With this argument, practitioners have utilized AI systems to assist or even substitute human decision-making with the aim to increase objectivity.
This debate around the question whether humans or AI show stronger biases is not new and existing research shows evidence for both directions. This research project therefore aims to provide more insight into if and how social biases differ between humans and AI. Specifically, the focus lies on gender and age biases as well as their intersectional bias where both age and gender bias overlap. To assess implicit biases in the context of occupational roles, the visual wiki survey tool PictoPercept will be used for both groups. This innovative method addresses existing methodological challenges in measuring implicit biases, for instance by enhancing accessibility through visual stimuli and mitigating social desirability effects.