Putting a Face on Algorithms: Personas for Modeling Artificial Intelligence

Karahasanovic, Amela; Følstad, Asbjørn; Schittekat, Patrick

doi:10.1007/978-3-030-77772-2_15

Cited by 2 publications

(1 citation statement)

References 36 publications

(43 reference statements)

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“…This observation is consistent with the findings of Karahasanović et al (2021), who found that the lack of perceived humanity in AI applications can lead to mistrust and discomfort. Furthermore, the quote also illustrates the frustration caused by a failed interaction with AI.…”

Section: User-friendliness: Lack Of Humanity and Disappointing Experi...supporting

confidence: 92%

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

Armutat,

Wattenberg,

Mauritz

2024

icgr

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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.

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Section: User-friendliness: Lack Of Humanity and Disappointing Experi...supporting

confidence: 92%