From AI recruiting tools to industrial automation and robotic assistants, new digital technologies are transforming the modern workplace. Many of these systems promise to improve efficiency, productivity and well-being – but how do they actually affect the people who interact with them every day?
This is a complex question with no clear answers. But more and more research has begun to explore the nuanced ways technology is impacting the workplace and workforce, shedding light on both its many benefits and significant risks.
How AI is transforming hiring?
One of the most significant areas where technology has transformed the workplace is before new candidates even walk in the door. AI tools can help recruiters screen resumes, review cover letters, and even conduct virtual interviews. But these tools can also introduce new complexities and biases into the hiring process.
AI hiring tools can influence who applies: In one study, researchers asked more than 500 US-based adults to imagine applying for a job through a system that uses AI. They found that applicants who were already excited about the prospective employer and felt positive about AI in general were more likely to complete an application. Candidates who are apprehensive or distrustful of AI, or who are less enthusiastic about the employer, are less likely to complete their applications if interaction with AI is required. This suggests that incorporating automated tools into the hiring process may affect the experience of different applicants differently, influencing who ends up applying in potentially surprising ways.
Automated screening can perpetuate bias: While the potential for AI-based systems to support human biases is well known, a new study found that even when explicitly gender-related information (such as names or pronouns) is removed, today’s advanced machine learning models can still accurately to determine the applicant’s gender. Additionally, the study found that after controlling for job-related characteristics, when elements of an applicant’s resume did not match their gender—i.e. when a woman’s CV includes traditionally masculine characteristics – they are less likely to be called back for an interview.
People are less offended by algorithmic than human discrimination: Given the proliferation of AI-driven biases, will companies feel pressured to stop using these tools? At least one paper suggests that it might not: Across a series of eight studies, researchers found that people tend to be much less angry when they learn that an algorithm discriminates than when a human makes the same discriminatory decision, meaning that you are less likely to accuse an organization of discrimination if it is supported by an automated tool.
How does digital monitoring affect employees?
Of course, the hiring process is hardly the last time a new employee is likely to find themselves interacting with a digital system. The past few years have seen an explosion in employee monitoring tools, from keystroke tracking apps to wearable GSP monitors. And while proponents tout the potential of these tools to increase efficiency and transparency, recent research has painted a more nuanced picture.
Electronic monitoring can harm both workers and employers: A team of researchers conducted a meta-analysis of the results of more than 50 different academic studies and found that electronic monitoring reduces employee job satisfaction and increases stress levels. They also found that monitoring had no effect on performance, but slightly increased the chances that an employee would engage in counterproductive behaviors, such as working less than expected, wasting resources, or treating coworkers and supervisors poorly. This is consistent with other recent research that suggests that monitoring workers makes them more likely to break the rules because it reduces their sense of responsibility for their own actions.
Monitoring can also increase engagement: However, effective monitoring can also have a positive effect. A study that looked at data from more than 200 higher education employees found that electronic performance monitoring can increase worker engagement. This is at least in part because digital tools are often perceived as fairer than traditional monitoring systems, leading workers to identify more strongly with their organizations and thus feel more invested and engaged in their work.
What is it like to work alongside a robot?
Beyond simply being monitored by digital tools, employees are increasingly likely to work with, receive advice from, or even be managed by an automated system. At the individual level, research has identified a number of factors that may influence how people respond to their new robotic colleagues.
People respond better when automated systems feel authentic: When working with automated tools like chatbots or recommendation engines, authenticity is key. In a series of five studies, researchers found that people responded much more positively when a tool was presented in an authentic way, and in particular when its human origin was emphasized. Conversely, anthropomorphizing autonomous technologies by giving them human qualities actually makes them seem less authentic, degrading people’s experience of interacting with them.
Another study found a similar effect in the context of algorithmic management: if workers are managed by an algorithm (such as Uber’s algorithm that automatically assigns work, provides performance feedback, and makes other supervisory decisions), they are more likely to react angrily to negatively feedback if the robotic interface is anthropomorphized. This is because we subconsciously attribute greater agency to human-like systems, and as a result are more likely to hold them “responsible” for giving us negative feedback.
People prefer to take advice from algorithms for certain types of decisions: Three other recent studies examined the context in which employees felt more or less comfortable accepting advice from an automated tool. One paper found that for predictions or estimations, people prefer to take advice from algorithms than from people – but when it comes to making decisions based on those predictions, people prefer to take advice from people. Conversely, another series of experiments found that when it comes to delegating decisions over which people really want to retain control, they are often more willing to cede decision-making power to an AI than to a human.
In addition, research shows that people want to understand why and how AI makes its decisions. In a field study examining the use of AI diagnostic tools in a large hospital, medical professionals were less likely to incorporate information from AI if it deviated from initial human judgments without providing a clear reason. But when AI-generated diagnoses were accompanied by an explanation, doctors were much more likely to listen to them.
Workplace automation comes at a cost: Along with impacting the experience of individual workers, the rapid growth of automation is also having a significant effect on macro-level social, political, and economic trends. An analysis of 14 years of U.S. Census data mapped to the growth of industrial robots at the county level found that the automation of formerly human jobs was linked to increases in drug overdose deaths, suicides, homicides and mortality from cardiovascular disease. Moreover, beyond direct health outcomes, automation in the workplace can promote negative sentiments in surprising ways. For example, data from more than 30,000 Americans and Europeans suggests that as people become more concerned about automation threatening their job security, they tend to develop more anti-immigrant sentiment.
How is automation changing the composition of the US workforce?
While automation certainly has the potential to improve the lives of workers, this common fear—that automation poses a threat to job security—is far from unfounded. In fact, data shows that increasing investment in AI and other automated technologies could have a significant impact on the composition of the workforce.
Automation increases demand for educated workers and flattens organizational charts: At a firm-by-firm level, the researchers found that investment in AI tended to correlate with hiring more highly educated workers. In addition, companies with greater automation tend to have flatter organizations, with more junior workers and fewer mid- and senior-level employees.
Automation reduces low-paying non-service jobs: At the economy level, an analysis of US employment data found that increased automation has led to a decrease in the availability of low-wage automated jobs. Interestingly, this shift has been accompanied by an increase in non-automated low-wage jobs (ie, service jobs where humans cannot be replaced by robots). But that increase isn’t enough to offset the decline in jobs that don’t have an interpersonal component. What’s more, the study found that job losses due to automation are greatest among non-Asian people of color, shedding light on the complex interplay between racial equity, economic trends and technological advances.
As with the growth of any new technology, the recent explosion in digital tools in the workplace is neither all good nor all bad. Rather, optimism and enthusiasm for progress must be balanced with recognition of the very real—and not always positive—impact these tools can have on the people who interact with them. As new research examines these diverse effects, leaders are constantly checking their assumptions, avoiding oversimplification, and working to ensure that their decisions are guided not just by knee-jerk reactions or intuition, but by the latest data and evidence.