Browsing by Author "Mazurova, Elena"

Now showing 1 - 3 of 3

Paradoxes Associated with the Introduction of AI-Powered Electronic Systems - A Case Study from Competitive Artistic Gymnastics
(2022) Mazurova, Elena
School of Business | Doctoral dissertation (article-based)
The use of AI technologies in systems supporting human experts' performance in demanding analysis and decision-making situations has expanded rapidly and grown ubiquitous in various fields. While AI-powered systems' introduction provides new opportunities for enhancing work processes, it is an uncertainty-rife, ambiguous, and difficult process that may have numerous implications and significantly influence many facets of a stakeholder's life, requiring radical changes in the organization and people involved. However, many organizations, in their pursuit of greater productivity, efficiency, accuracy, reliability, profitability, speed of work processes, and new advanced capabilities for human experts, undertake it without considering these implications and diverse risks for the organizational system and its stakeholders – with system bias, errors, inaccuracy, non-transparency, disturbing of trust and humans' safety and privacy, cultivation of discrimination, and disruption of human interaction being just a few of the numerous possible effects. Furthermore, AI systems' implementation could become a major source of "paradoxical tensions" in the organization. If unable to cope with these tensions evoked by the implementation, key stakeholders may experience negative functionality-related and emotional consequences of discrepancies between their expectations and the real-world experience of using the technology. Expressing a resulting research interest in the transition from human-based expert systems to AI-powered ones, a rigorous qualitative study of possible risks and implications associated with an AI system's introduction was conducted as a doctoral project. The study, from the perspective of a broad set of stakeholders, was conducted in a unique research context: artistic gymnastics, where Fujitsu has recently introduced an AI-powered system to support the judging, thus aiding in expert evaluation. As the research process progressed, analysis revealed several paradoxical tensions associated with this new electronic judging system's deployment for artistic gymnastics, tensions not previously considered in information-systems studies. Explored in depth in the dissertation, these are articulated as "accurate AI is too exact," "'objective' AI can be biased," "even black boxed AI represents explainability," "an AI-based judging system for artistic gymnastics cannot judge artistry," "a system intended for humans lacks human interaction," "consistency requires AI's adaptability," and "automation requires augmentation and vice versa." Building on the existing body of knowledge of AI, the project contributes to scholarly understanding of the paradoxes associated with IT artifacts and shows that proceeding with a degree of caution in the process of their implementation is still necessary.
Probing Athletes’ Perceptions Towards Electronic Judging Systems: A Case Study in Gymnastics
(2020) Mazurova, Elena; Penttinen, Esko
A4 Artikkeli konferenssijulkaisussa
We study athletes’ perceptions towards the transition to electronic judging systems. Using purposive sampling, we select an area of sports that is undergoing a somewhat disruptive change in the way athletes are evaluated: gymnastics. We draw on interviews conducted with gymnasts to probe their perceptions of electronic judging systems. We find that gymnasts are quite positive towards the implementation of these systems, although they expressed some uncertainties (i.e. how these systems influence the artistic side of gymnastics) and risks (i.e. technical problems) of the technology. The positive side of the transition to electronic judging systems mainly relates to the deficiencies of the human-based judging, it being vulnerable to biases, human error, human fatigue, judges’ personal preferences, and inherent lack of explanation. Our informants expressed that electronic judging systems contain affordances that could efficiently mitigate the said challenges associated with human-based judging.
Stakeholder-dependent views on biases of human- and machine-based judging systems
(2021) Mazurova, Elena; Penttinen, Esko; Salovaara, Antti
A4 Artikkeli konferenssijulkaisussa
Motivated by recent controversy over biases associated with algorithmic decision-making, we embarked on studying various stakeholders’ perceptions related to potential biases in verdicts from human-based and algorithm-based judging. In an empirical study conducted in the domain of gymnastics judging, we found that, while our informants viewed both human- and AI-based judging systems as being subject to biases (of different types), they were quite welcoming of a shift from human-based judging to machine-based judging. Our findings show that the athletes trusted strongly in unknown, “magic” capabilities of AI, thought to be more objective and impartial. This, in turn, encouraged potential acceptance of new technology. While the gymnasts saw AI-based systems in a positive light, judges demonstrated less favorable perceptions overall and less acceptance of AI technology, expressing concern about possible challenges of AI.