36 Joshua Powell – The Relationship Between AI Perceptions and Job Displacement Fear

Joshua Powell (He/Him) is from Richmond, IN and he graduated this past semester with a degree in Communications.  This work was prepared for Emmy Price’s ENG W230 class.  Professor Price states, ” Josh’s thorough analysis of the relationship between AI perceptions and job displacement fear provides valuable insights into a critical issue facing today’s workforce, especially within the context of college students. Josh was able to connect skills from his statistics class as he analyzed his data throughout this project. The clarity of Josh’s methodology and the significance of his findings demonstrate strong research skills and a thoughtful approach to addressing a complex topic.”

The Relationship Between AI Perceptions and Job Displacement Fear

Abstract

This paper explores the relationship between AI perceptions and job displacement fear. It focuses on analyzing opinions from college students to find out if there is a significant correlation between AI perceptions and job displacement fear. The objectives were to: 1) identify and evaluate job displacement fear levels and perceptions of AI among college students, and 2) determine whether a significant correlation exists between job displacement fear levels and perceptions of AI among college students. Data was collected through a quantitative survey method of 46 Reddit users from college subreddits (e.g., r/Indiana University, r/Purdue) who voluntarily chose to take part in the research. Data was analyzed using a regression analysis and ANOVA method available through the data analysis ToolPak for Microsoft Excel. The findings indicate that there is a significant negative correlation between AI perceptions and job displacement fear among these participants. Other indications from the findings were that participants who were currently employed had a higher level of job displacement fear than unemployed participants. This research is significant as it could have implications on future policies, education, and overall public awareness of AI perceptions and job displacement fear.

Materials/Methods

Materials & Design

The software Qualtrics was used to create and conduct the surveys. Qualtrics is an easy-to-use software for survey creation and analysis, and it was made available for Indiana University students. The surveys were posted online on the social media website Reddit. The survey contained 7 total questions, which ranged from demographic-focused questions (e.g., age, gender, employment status) to questions about AI perception and job displacement fear. Questions about AI perception and job displacement fear used the 7-point Likert scale to measure responses. In order to analyze results and determine correlation, the data analysis ToolPak in Microsoft Excel was used, as well as Qualtrics built-in analysis tools.

Subjects

46 members of multiple college subreddits (e.g., r/Indiana University, r/Purdue) voluntarily chose to participate in the survey. Demographic data showed that 45.2% of participants were 18-34 years old, while 54.7% were 35 or older. Gender responses showed that 54.8% of respondents identified as Male, while 31% identified as Female, and 14.3% identified as Non-binary/third gender. In terms of ethnicity, 76.2% of participants were White, 11.9% were Asian, 2.4% were Black, while 9.2% were another ethnicity. Of the 46 participants, 76.2% were employed at the time of the survey, while 23.8% were unemployed. 24.4% of participants work or want to work in the technology field, 22% in education, 4.9% in customer service, 4.9% in healthcare, 4.9% in creative arts, 4.9% in marketing and communications, and 34.1% in another field.

Procedure

In order to create and analyze the survey in a short time period of 2 weeks, the software Qualtrics was used. Qualtrics has several user-friendly features that can speed up the process of survey creation, such as its Stats IQ feature which helps with data analysis. To reach the highest possible number of participants, Reddit was used, as it is one of the most popular social media websites on the internet. One of the other main benefits of using Reddit for research purposes is the existence of subreddits for specific demographics, such as r/College and r/Indiana University. To reach out to participants, several posts were created which included a link to the survey and notified participants that their responses would be kept anonymous. To determine correlation, the data analysis ToolPak in Microsoft Excel was used. The data analysis ToolPak in Microsoft Excel is an easy way to conduct a regression analysis, find descriptive statistics, and create tables, graphs, or charts. In order to measure other statistics, such as demographic data, data analysis tools from Qualtrics were used.

Results

Data analysis was split into two separate stages. The first stage of the data analysis was to use Microsoft Excel to determine whether there was a significant correlation between AI perceptions and job displacement fear among college students.  The second stage was to use Qualtrics’ data analysis tools to collect demographic data. Findings indicated that there was a statistically significant negative correlation (r = -.32 , p = .04, p < .05), though it was weaker than anticipated. This data is included in figures 1 and 2. While the correlation between both variables is somewhat weak (r = -.32), it is still statistically significant (p < .05). These findings support the hypothesis that there would be a negative correlation between job displacement fear and AI perceptions, as a statistically significant negative correlation was found. It is also important to mention that not all 46 respondents answered every question, which resulted in only 41 total observations for questions about AI perceptions and job displacement fear.

In the analysis, it was important to examine the relationship between employed and non-employed college students to see if responses noticeably differed between the two. Therefore, questions about employment status and job fields were included in the survey. Data collected from Qualtrics showed that 31.8% of respondents that are employed said that they were at least somewhat worried about AI-induced job displacement. In contrast, only 14.7% of respondents that are unemployed said that they were at least somewhat worried about AI-induced job displacement. This data is represented in figure 3. These findings support the hypothesis that students who are employed will have a higher level of job displacement fear than unemployed students.

Discussion

The main goal of this research was to determine whether a significant correlation existed between job displacement fear levels and AI perceptions among college students. The findings of this study show a significant negative correlation between both variables. The results from the ANOVA test showed that there was a statistically significant relationship between the variables of AI perception and job displacement fear (p < .05). This research suggests that as AI perceptions increase among college students, job displacement fears decrease. Another key finding in this study was that a higher percentage of employed college students were worried about AI-induced job displacement than their unemployed counterparts. These findings suggest that employment status could influence job displacement fear.

The two hypotheses for this study were that 1) students who are employed will have a higher level of job displacement fear than unemployed students, and 2) there would be a negative correlation between job displacement fear and perceptions of AI among college students. The findings support both hypotheses. However, it is important to recognize the many limitations of this study. Due to the small sample size of 46 participants, sampling bias was the primary limitation. The average age of participants was also older than anticipated, as 54.7% of participants were 35 or older. Therefore, this study is not generalizable to the entire population of college students. Selection/volunteer bias is another limitation, as all respondents voluntarily chose to participate. Previous studies on the public perception of AI have had similar age limitations (Stai et al. 2020), suggesting that future studies focused more on younger audiences are still needed.

Conclusion

In summary, the findings of this study suggest that there is a correlation between AI perceptions and job displacement fear. Findings also suggest that employment status might influence these variables as well. Based on these results, it is possible that there could be a deeper relationship between AI perceptions and job displacement fear. However, this study cannot determine causation between these variables or determine what causes AI perceptions to change. Many researchers have argued in the past that fears about AI are often exaggerated in order to affect public perception (Cave et al. 2018). More research must be conducted in the future to determine what causes AI perceptions to change. However, this study’s findings are still statistically significant and could be used in future AI-related studies, as well as educational purposes.

References

Ansari, A, & Ansari, A. 2024. Consequences of ai induced job displacement. International Journal of Business, Analytics, and Technology. https://ijbat.com/index.php/IJBAT/article/view/18/31

Cave, S, Craig, C, Dihal, K, Dillon, S, Montgomery, J, Singler, B, & Taylor, L. 2018. Portrayals and perceptions of AI and why they matter. The Royal Society. https://doi.org/10.17863/CAM.34502

Fitria, TN. 2023. Artificial intelligence (AI) technology in OpenAI ChatGPT application: A review of ChatGPT in writing English essay. ELT Forum: Journal of English Language Teaching. http://dx.doi.org/10.15294/elt.v12i1.64069

Liu, Y, Meng, X, & Li, A. 2023. Ai’s ethical implications: Job displacement. Advances in Computer and Communication. http://dx.doi.org/10.26855/acc.2023.06.006

Stai, B, Heller, N, McSweeney, S, Rickman, J, Blake, P, Vasdev, R, … & Weight, C. 2020. Public perceptions of artificial intelligence and robotics in medicine. Journal of endourology. https://doi-org.proxyeast.uits.iu.edu/10.1089/end.2020.0137