"Navigating the Challenges: A Systematic Literature Review on the Limitations of Emotional Artificial Intelligence."
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Abstract
In recent years, notions like artificial intelligence and emotional intelligence have gained a lot of traction in the relevant literature. Artificial intelligence (AI) is thought to increase worker productivity by encouraging creative problem solving and acting as a multifunctional instrument. While much is known about AI's ability to create value through innovation, little is known about how emotional AI's limitations affect innovative work behavior (IWB). Emotional artificial intelligence (Emotional AI) has received a lot of interest as a possible tool to enhance workplace relationships, encourage employee welfare, and increase productivity. Before being widely used in the workplace, emotional artificial intelligence (AI) needs to be thoroughly considered due to its serious disadvantages, even with its potential benefits. The study looks into the primary dangers to identity and restrictions that Emotional AI poses in the workplace.....
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References
Altig, D., Baker, S., Barrero, J. M., Bloom, N., Bunn, P., Chen, S., ... & Thwaites, G. (2020). Economic uncertainty before and during the COVID-19 pandemic. Journal of Public Economics, 191, 104274.
Barrero, J. M., Bloom, N., & Davis, S. J. (2021). Why working from home will stick (No. w28731). National Bureau of Economic Research.
Barry Gruenberg. 1980. The happy worker: An analysis of educational and occupational diferences in determinants of job satisfaction. American journal of sociology 86, 2 (1980), 247–271.
Bridgelall, R., Stubbing, E., 2021. Forecasting the effects of autonomous vehicles on land use. Technol. Forecast. Soc. Change 163, 120444. https://doi.org/10.1016/j. techfore.2020.120444.
Buhalis, D. & Leung, R. (2018). “Smart hospitality – Interconnectivity and interoperability towards an ecosystem.” International Journal of Hospitality Management, 71, pp. 41 –50.
Chaturvedi, A., Kumar, S., & Rathore, R. (2021). An Assesment of Export Potential of Indian Mentha Oil in International Market.
Chuang S (2020) An empirical study of displaceable job skills in the age of robots. Eur J Train Dev. https:// doi.org/10.1108/EJTD-10-2019-0183
Desouza, K.C., Dawson, G.S., Chenok, D., 2020. Designing, developing, and deploying artificial intelligence systems: lessons from and for the public sector. Bus. Horiz. 63 (2), 205–213. https://doi.org/10.1016/j.bushor.2019.11.004.
Dumay J, Guthrie J, Puntillo P. IC and public sector: a structured literature review. J Intellect Cap. 2015;16(2):267–84.
Frick, N. R., Mirbabaie, M., Stieglitz, S., & Salomon, J. (2021). Maneuvering through the stormy seas of digital transformation: the impact of empowering leadership on the AI readiness of enterprises. Journal of Decision Systems, 30(2-3), 235-258.
Gabriel Grill and Nazanin Andalibi. 2022. Attitudes and Folk Theories of Data Subjects on Transparency and Accuracy in Emotion Recognition. Proceedings of the ACM on Human-Computer Interaction 6, CSCW1 (2022), 1–35
Gavin Tay and Bern Elliot. 2019. Maverick* Research: Emotion AI Will Become You Without Your Knowledge. https://www.gartner.com/document/3975557? ref=gfeed
Grundner, L., & Neuhofer, B. (2021). The bright and dark sides of artificial intelligence: A futures perspective on tourist destination experiences. Journal of Destination Marketing & Management, 19, 100511.
Hern A (2018), May 16 Facebook lets advertisers target users based on sensitive interests. The Guardian. https://www.theguardian.com/technology/2018/may/16/ facebook-lets-advertisers-target-users-based-on-sensitive-interests
Jeon, H., Seo, W., Park, E., Choi, S., 2020. Hybrid machine learning approach for popularity prediction of newly released contents of online video streaming services. Technol. Forecast. Soc. Change 161, 120303. https://doi.org/10.1016/j. techfore.2020.120303.
Langvik, E., Karlsen, H. R., Saksvik-Lehouillier, I., & Sørengaard, T. A. (2021). Police employees working from home during COVID-19 lockdown: Those with higher score on extraversion miss their colleagues more and are more likely to socialize with colleagues outside work. Personality and Individual Differences, 179, 110924.
Luke Stark and Jesse Hoey. 2021. The Ethics of Emotion in Artifcial Intelligence Systems. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (Virtual Event, Canada) (FAccT ’21). Association for Computing Machinery, New York, NY, USA, 782–793. https: //doi.org/10.1145/3442188.3445939
Luke Stark, Amanda Stanhaus, and Denise L Anthony. 2020. “I Don’t Want Someone to Watch Me While I’m Working”: Gendered Views of Facial Recognition Technology in Workplace Surveillance. Journal of the Association for Information Science and Technology 71, 9 (2020), 1074–1088
Malik N, Tripathi SN, Kar AK, Gupta S (2021) Impact of artificial intelligence on employees working in industry 4.0 led organizations. Int J Manpow. https://doi.org/10.1108/IJM-03-2021-0173
Mas FD, Massaro M, Lombardi R, Biancuzzi H. La performance nel settore pubblico tra misure di out-put e di outcome. Una revisione strutturata della letteratura ejvcbp. 2020;1(3):16–29.
Massaro M, Dumay J, Guthrie J. On the shoulders of giants: undertaking a structured literature review in accounting. Account Auditing Account J. 2016;29(5):767–801.
McStay, A. (2020). Emotional AI and EdTech: serving the public good?. Learning, Media and Technology, 45(3), 270-283.
Mirbabaie, M., Bunker, D., Stieglitz, S., Marx, J., & Ehnis, C. (2020). Social media in times of crisis: Learning from Hurricane Harvey for the coronavirus disease 2019 pandemic response. Journal of Information Technology, 35(3), 195-213.
Nazanin Andalibi and Justin Buss. 2020. The Human in Emotion Recognition on Social Media: Attitudes, Outcomes, Risks. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–16. https: //doi.org/10.1145/3313831.3376680
Russell, S. J. & Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia.
Secinaro S, Calandra D, Secinaro A, Muthurangu V, Biancone P. Artifcial Intelligence for healthcare with a business, management and accounting, decision sciences, and health professions focus [Internet]. Zenodo; 2021 [cited 2021 Mar 7]. https://zenodo.org/record/4587618#.YEScpl1KiWh.
Sohrabpour, V., Oghazi, P., Toorajipour, R., Nazarpour, A., 2021. Export sales forecasting using artificial intelligence. Technol. Forecast. Soc. Change 163, 120480. https:// doi.org/10.1016/j.techfore.2020.120480.
Wilson HJ, Daugherty PR (2019) Creating the Symbiotic AI workforce of the future. MIT Sloan Management Review 61(1):1–4. https://sloanreview.mit.edu/article/ creating-the-symbiotic-ai-workforce-of-the-future
Yao, S., Wang, X., Yu, H. & Guchait, P. (2019). “Effectiveness of error management training in the hospitality industry: Impact on perceived fairness and service recovery performance.” International Journal of Hospitality Management, 79, pp. 78 –88.
Zickuhr, K. (2021). Workplace surveillance is becoming the new normal for US workers. Washington Center for Equitable Growth. https://equitablegrowth. org/research-paper/workplace-surveillance-is-becomingthe-new-normal-for-us-workers/. Institute for Research on Labor and Employment University of California, Berkeley, 2521, 94720-5555.