Artificial Intelligence – Gender-Specific Differences in Perception, Understanding, and Training Interest

Authors

  • Sascha Armutat Bielefeld University of Applied Sciences and Arts
  • Malte Wattenberg Bielefeld University of Applied Sciences and Arts https://orcid.org/0000-0001-5628-2877
  • Nina Mauritz Bielefeld University of Applied Sciences and Arts

DOI:

https://doi.org/10.34190/icgr.7.1.2163

Keywords:

Artificial Intelligence, Ai gender bias, prevalent stereotypes, gender discrimination, need for transparency, knowledge gaps, socialisation based vicious circle

Abstract

In light of the growing importance of Artificial Intelligence (AI) in science, business, and society, broad acceptance is crucial. However, recent studies indicate a significant underrepresentation of women in the emerging AI-driven professions of the future job market. This hampers the innovation potential of technologies due to the lack of diverse perspectives in development. Gender-specific differences also manifest in the perception of AI: Men tend to view AI applications more positively, rate their own AI competencies higher, and have more trust in the technology compared to women. However, both genders agree on the critical importance of the comprehensibility of AI decisions and are equally willing to pursue further education in the field of AI.

This study aimed to investigate gender-relevant aspects in the perception and understanding of AI, as well as the need for further education and opportunities for communication and exchange on the topic of AI.

To achieve this, focus groups with female students were conducted in May 2023. The analysis of the conversation data and materials used was carried out using an inductive coding method.

Overall, women perceive knowledge as the key to generating more interest in AI. However, they also identify obstacles such as discrimination, gender stereotypes, and a lack of gender equality. Additionally, they desire more practical examples, improved communication regarding the advantages and disadvantages of AI, as well as more democratic and transparent decision-making processes.

The paper emphasizes that an inclusive educational environment requires awareness and education for women, along with measures against discriminatory barriers and stereotypes. Furthermore, it suggests the early involvement of women in the development of AI applications and the establishment of clear rules to ensure gender equality in the workplace. These study findings provide valuable support to companies in the gender-specific planning of awareness and training processes for introducing AI.

Author Biographies

Sascha Armutat, Bielefeld University of Applied Sciences and Arts

Prof. Dr. rer. pol. Sascha Armutat

is professor for human resources management and organization at the Faculty of Business at Bielefeld University of Applied Sciences and Arts since April 2016. He represents the topics of Human Resource Management, Organization and Leadership in teaching. He researches especially on questions of strategic human resources management in the context of agility and digitization, employer branding and strategic workforce planning.

Malte Wattenberg, Bielefeld University of Applied Sciences and Arts

Malte Wattenberg

is research assistant at the "Denkfabrik Digitalisierte Arbeitswelt" at Bielefeld University of Applied Sciences and Arts, Germany. His work and research focuses in particular on the requirements of the digital transformation in companies as well as digital business models and social media communication.

Nina Mauritz, Bielefeld University of Applied Sciences and Arts

Nina Mauritz

studied Business Psychology (B.Sc.) and Business Administration (M.A.) and has been a research assistant in various research projects at the "Denkfabrik Digitalisierte Arbeitswelt" at Bielefeld University of Applied Sciences and Arts, Germany since 2015. Her research focuses on the topics of Industry 4.0, skills development and artificial intelligence from an occupational science perspective. She also lectures in the fields of marketing and psychology.

Downloads

Published

2024-04-18