International Journal of Internet, Broadcasting and Communication

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
권호 표지
DOI QR코드

DOI QR Code

Research on the evaluation model for the impact of AI services

  • Received : 2023.07.13
  • Accepted : 2023.07.22
  • Published : 2023.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study aims to propose a framework for evaluating the impact of artificial intelligence (AI) services, based on the concept of AI service impact. It also suggests a model for evaluating this impact and identifies relevant factors and measurement approaches for each item of the model. The study classifies the impact of AI services into five categories: ethics, safety and reliability, compliance, user rights, and environmental friendliness. It discusses these five categories from a broad perspective and provides 21 detailed factors for evaluating each category. In terms of ethics, the study introduces three additional factors-accessibility, openness, and fairness-to the ten items initially developed by KISDI. In the safety and reliability category, the study excludes factors such as dependability, policy, compliance, and awareness improvement as they can be better addressed from a technical perspective. The compliance category includes factors such as human rights protection, privacy protection, non-infringement, publicness, accountability, safety, transparency, policy compliance, and explainability.For the user rights category, the study excludes factors such as publicness, data management, policy compliance, awareness improvement, recoverability, openness, and accuracy. The environmental friendliness category encompasses diversity, publicness, dependability, transparency, awareness improvement, recoverability, and openness.This study lays the foundation for further related research and contributes to the establishment of relevant policies by establishing a model for evaluating the impact of AI services. Future research is required to assess the validity of the developed indicators and provide specific evaluation items for practical use, based on expert evaluations.

Keywords

Acknowledgement

This work was supported by Hansei University Research Fund of 2022.

References

  1. Yoo Soonduck. "A Study on the Method of Deriving AI Activation Policy," Journal of the Korea Internet Broadcasting and Communication Society 20, no. 5 (2020): 187-193.
  2. Sowon Jeon, Jihee Lee, and Jongtae Lee. "A Study on User Acceptance Intention of AI Services: Focusing on Factors Influencing the Perception of Need for Conversational AI Services," Journal of Technology Innovation 22, no. 2 (2019): 242-264.
  3. Misuraca, Gianluca, and Colin Van Noordt. "AI Watch-Artificial Intelligence in public services: Overview of the use and impact of AI in public services in the EU," JRC Working Papers JRC120399 (2020).
  4. Park Soo-ah, and Choi Se-jeong. "Factors Influencing Satisfaction with Artificial Intelligence Speakers and Continuous Usage Intention: Focusing on Functional and Emotional Factors," Information Society and Media 19, no. 3 (2018): 159-182. https://doi.org/10.52558/ISM.2018.12.19.3.159
  5. Amazon Web Services(AWS) web site, 2022
  6. sas web site, 2022
  7. Changhwa Baek, Jaeho Choi, and Sungwook Lim. "Consideration and Suggestion of AI Service Characteristics and Quality Measurement Items," J Korean Soc Qual Manag Vol 46, no. 3 (2018): 677-694.
  8. Van der Horst, Dan, and Saskia Vermeylen. "Spatial scale and social impacts of biofuel production." Biomass and bioenergy 35, no. 6 (2011): 2435-2443. https://doi.org/10.1016/j.biombioe.2010.11.029
  9. Jinyeol Kim. "Reviews on Policy 'Impact Assessment System' and Consumer Impact Assessment," Consumer Policy Trends 109 (2020): 1-25.
  10. Nguyen, Tuyet-Mai, and Ashish Malik. "A two-wave cross-lagged study on AI service quality: The moderating effects of the job level and job role," British Journal of Management 33, no. 3 (2022): 1221-1237. https://doi.org/10.1111/1467-8551.12540
  11. Naumov, Nikola. "The impact of robots, artificial intelligence, and service automation on service quality and service experience in hospitality," In Robots, artificial intelligence, and service automation in travel, tourism and hospitality. Emerald Publishing Limited, 2019.
  12. Yoo, Soonduck, Jungihl Kim, and Kwangsun Ryu. "Using big data strategy for the development of the communication industry," In International Conference on Web-Age Information Management, pp. 349-359. Springer, Cham, 2014.
  13. Hangyul Seo, Sangjun Nam and Seongjun Lee. (2019). Evaluating mobile communication service efficiency in OECD countries: using data envelope analysis methodology. Journal of the Korean Society of Communications and Communications, 44(2), 376-386.
  14. Younghee Lee. "Social Control and Acceptance of Technology: The Politics of Technology Impact Assessment," Economy and Society (2007): 246-268.