Artificial Intelligence in the Workplace

By: Abigail Heister and Kris Hargraves

https://webspace.ship.edu/jacamp/psyberpsych/



What is Artificial Intelligence (AI)?


Why is Learning About AI in the Workplace Important?

Although America includes a vastly diverse population, there always seems to be one topic that everyone is familiar with: Work. Work is a broad term that can include emotional work, yard work, household work, homework, and your daily job. With this in mind, everyone is familiar with at least one subcategory of work. It is something you probably do every day for an extended period of time. For the purposes of this discussion, we are going to highlight career work or work during an everyday job. The majority of Americans wake up and go to their workplace. The workplace is the space in which you complete your work. This could be an office, a factory, a school, a warehouse, etc. In fact, many statistics imply that Americans spend a lot of time at work. They are the first to admit that their work-life balance is poor (What To Become, 2022). This means it is safe to say that Americans spend a lot of time working and in the workplace, sometimes even more than they would like. So, if a place they spend most of their time were to change, it would probably be of interest to a lot of Americans. That is why learning about AI in the workplace is important… It is changing the workplace!

Recently there has been a big shift in the ways some companies and organizations are managed. More and more companies are beginning to use Artificial Intelligence (AI). AI in the workplace “has the ability to make decisions in real time based on pre-installed algorithms and computing technologies constructed based on data analysis to learn and acclimate automatically to offer more refined responses to situations” (Rodgers et al., 2013). As will be discussed throughout this webpage, meaningful work, workplace psychological well-being, perceptions of AI recommendations, mental healthcare, and self-disclosure are all being influenced by AI in the workplace. This can be seen in human resource management (HRM), psychotherapy, factories, warehouses, and many more workplaces. While this revolutionary technology is changing the way managers, human resources teams, and workplaces conduct business, it also means that they are wandering into uncharted territory. How is it going to affect the workplace and the employees in the workplace?

One of the first questions that need to be addressed is: How is AI affecting meaningful work? Meaningful work can be defined as "the perception that one's work has worth, significance, or a higher purpose" (Bankins & Formosa, 2023). If individuals prioritize their work so much that they miss out on other aspects of life, work must have a high value. Will this change if AI is implemented into the workplace? Bankins & Formosa (2023) would suggest that it depends how the AI is implemented. Three paths – task complexity, tending the machine, and amplifying work- are discussed by the researchers. Depending on the path at which AI is implemented will predict whether the change will improve or decrease employees’ perceptions of meaningful work. It all has to do with the type of job, the way in which AI is implemented, and the interactions between the subcategories of meaningful work - task integrity, task significance, skill cultivation & use, belongingness, and autonomy (Bankins & Formosa, 2023).

More than how AI is affecting meaningful work, it important to know AI might affect workplace psychological well-being. Workplace psychological well-being is "the realization of one's true potential at work" (Dekay, 2020). This type of well-being is crucial because Americans spend significant amounts of time at work, so their psychological well-being is undoubtedly affected by the workplace and their work. Unsurprisingly, the factors evaluating psychological well-being - Autonomy, Self-Acceptance, Growth, Relationships, Competence, and Purpose  (Degenais-Desmarais & Savoie, 2012) - have 66% overlap with the subcategories of meaningful work. This overlap suggests that participating in meaningful work has a huge impact on employee psychological well-being. Therefore, similar conclusions can be drawn for the impact of AI on psychological well-being. Depending on the pathway at which an organization/company chooses to implement AI into the workplace, workplace psychological well-being could be improved or decreased. Overall, Bankins & Formosa (2023) and DeKay (2022) do a great job predicting how AI implementation may affecting meaningful work and workplace psychological well-being. Check out the 'meaningful work' tab to learn more about these interactions!

"AI decision-support runs algorithms and makes decisions based off of specific criteria asked for by the relevant organization" (Feldkamp et al. 2023). For example, a company could implement AI decision-support technology into their HRM department. What would this look like? From a personnel selection standpoint, AI decision-support would sift through applicant applications and resumes to recommend which applicants should be invited for an interview. While this method may be quicker and more efficient, how do employees view the recommendation from AI? Feldkamp et al. (2023) were interested in how employees would react to AI decision-support recommendations. In fact, the researchers wanted to know how just, fair, and trustworthy individuals thought AI decision-support recommendations were. How employees view the recommendations given are important for companies to take into consideration. It does not make much sense to implement expensive software if employees are going to reject AI recommendations anyway. More than that, there are many laws in place to ensure job applicants are picked and rejected for fair reasons. AI recommendations in regard to gaining an interview for a job legally have to be fair and just. However, these are all concepts and issues Feldkamp et al. (2023) discuss in their study on perceptions of AI decision-support. Read more about it on the 'decision-support' tab! 

Conversational AI, or chatbots, are revolutionizing many areas of our lives, too and including mental healthcare. Mental healthcare can be defined as any care received for the purposes of improving one's mental health. This can be talk therapy, medication, music therapy, and so on. AIs can gather clinical information, facilitate treatment, and even review clinician performance and give feedback. They can give "evidence-based psychological interventions" (Miner et al., 2019) and broaden the reach of mental healthcare. There are many potential benefits and some potential pitfalls, as with everything, but so far, it seems the pros are outweighing the cons. This has not been clinically implemented or tested yet, but as technology improves and people become more open to trying new forms of therapy, the probability of AIs being implemented into mental healthcare increases. The most important variable, though, is trust. If people do not trust a conversational AI, they will not use it, and if we are to use AIs in therapy, trust must be established. Click the "Mental Healthcare" tab for more information.

Self disclosure has many benefits, including a sense of belonging and validation, support, and decreased negative mood. Self disclosure could be defined as telling someone else about yourself and your life. What if "others" could include an AI? The outcome could be worse, better, or the same. Many studies over the years have demonstrated great results when disclosing to another person, but very few have even considered what the effects may be when disclosing to an AI.

  In the "Self Disclosure" tab, we explain an experiment conducted by Ho et al. (2018) that examined the effects of disclosing information to a chatbot instead of a human and the results may surprise you! 

Real-Life Examples of AI in the Workplace