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 are they affecting the people who interact with them every day?
This is a complex question with no clear answer. But a growing body of research has begun to examine the subtle ways technology affects workplaces and the workforce, shedding light on both its many benefits and significant risks.
How is artificial intelligence changing recruitment?
One of the most important areas where technology has changed the workplace is before new candidates even walk in the door. AI tools help recruiters screen resumes, review cover letters, and even conduct virtual interviews. But these tools can introduce new complexities and biases into the hiring process.
AI recruiting tools can influence who applies: in one study, researchers asked more than 500 adults in the United States to imagine being employed by a system that used artificial intelligence. They found that candidates who were already excited about their future employer and had positive feelings about AI were more likely to apply. Candidates who were anxious or distrustful of AI, or who did not have positive feelings about the employer, were less likely to complete their application if they had to interact with AI. This suggests that incorporating automated tools into the hiring process can affect the experience of different candidates differently and affect who applies to whom.
Automated screening can perpetuate misconceptions: AI-based systems can perpetuate human stereotypes well knowna new research Today’s sophisticated machine learning models have found that they can accurately identify a candidate’s gender even when gender-specific information (names, pronouns, etc.) is removed. Furthermore, the study found that after controlling for job-related characteristics, a candidate’s resume is less likely to be called back for an interview if elements of the candidate’s resume don’t match their gender—that is, if a woman’s resume contains traditionally masculine traits. .
People are less offended by algorithms than by human discrimination: Will companies feel pressured to abandon these tools as AI-driven trends become popular? At least one piece of paper suggests it might not: Researchers found across eight studies that people are less angry when they learn that an algorithm is discriminatory than when a person makes the same discriminatory decision. for discriminatory purposes if perpetuated by automated means.
How does digital surveillance affect employees?
Of course, the hiring process isn’t the last time a new employee will find themselves interacting with digital systems. Over the past few years, there has been an explosion of employee monitoring tools, from push-button applications to wearable GSP displays. While proponents hail these tools’ potential for increased efficiency and transparency, recent research paints a more nuanced picture.
Electronic surveillance can be harmful to both employees and employers. Research team a meta-analysis More than 50 academic studies have found that electronic monitoring reduces employee job satisfaction and increases stress levels. They also found that while monitoring had no effect on performance, it slightly increased the likelihood that an employee would engage in counterproductive behaviors such as working less than expected, wasting resources, and misbehaving with coworkers and supervisors. It is compatible with others recent research This makes monitoring employees more likely to break the rules because it reduces accountability for their own actions.
And being in control can increase participation: That said, effective supervision can have a positive impact. A study A study of data from more than 200 higher education employees found that electronic performance monitoring can increase employee engagement. This is at least partly because digital tools are perceived as more fair than traditional monitoring systems, leading employees to identify better with their organization and thus be more invested and engaged in their work.
What is it like to work alongside robots?
In addition to being monitored by digital tools, employees can interact with, consult with, and even manage automated systems. At the individual level, research has identified a number of factors that may influence how people react to their new robotic co-workers.
People respond better when automated systems feel authentic. When working with automated tools like chatbots or recommendation engines, authenticity is key. Daanch a series of five studies, researchers found that people responded more positively when tools were presented authentically, especially when their human origins were highlighted. Conversely, turning autonomous technologies into human beings, giving them human-like characteristics, makes them seem truly meaningless and degrades the human experience.
Another study found a similar effect in the context of algorithmic management: If employees are managed by an algorithm (e.g., the Uber algorithm that automatically assigns work, provides performance feedback, and makes other supervisory decisions), they are more likely to react angrily to negative things. feedback if the robot interface is anthropomorphized. This is because we subconsciously treat human-like systems with more authority, and as a result, they are more likely to be “responsible” for reacting negatively to us.
People prefer to consult algorithms when making certain types of decisions. Three other recent studies examined the circumstances under which employees are more or less comfortable accepting advice from automated tools. One piece of paper People prefer to consult algorithms over people when making predictions or calculations, but when making decisions based on those predictions, people prefer to consult people. On the contrary, different series of tests When it comes to delegating decisions that people really want to retain control over, they find that they are more willing to hand over decision-making power to AI rather than humans.
Additionally, research shows that people want to understand why and how AI makes decisions. Inside field research A study of the use of AI diagnostic tools in a large hospital found that medical professionals were less likely to reflect input from AI if they deviated from a human’s initial judgment for no apparent reason. But if AI-generated diagnoses were accompanied by explanations, doctors were more likely to listen to them.
Workplace automation has the following costs: In addition to affecting the employee experience, the rapid growth of automation has had a significant impact on macro-level social, political, and economic trends. An analysis According to 14 annual U.S. Census data, drug overdose deaths, suicides, homicides, and cardiovascular death rates have increased in line with the statewide increase in industrial robotics, which is associated with the automation of previously human jobs. was found to be related. Also, in addition to direct health outcomes, workplace automation can produce surprising negative emotions. For example, data The survey of more than 30,000 Americans and Europeans found that anti-immigrant attitudes increased as people worried about automation threatening job security.
How is automation changing the composition of the US workforce?
While automation has the potential to improve workers’ lives, the common fear that automation threatens job security is unfounded. In fact, data suggests that growing investment in artificial intelligence and other automated technologies could have a significant impact on the composition of the workforce.
Automation increases the demand for educated workers and flattens the organizational chart. At each company level, researchers found investing in artificial intelligence is associated with hiring more educated workers. Additionally, companies with more automation tend to have flatter organizations, with more junior employees and fewer middle and senior employees.
Automation reduces low-wage, non-service jobs: Economically, a analysis U.S. employment data show that increased automation has led to fewer automated, low-wage jobs. Interestingly, this shift has been amplified by low-wage jobs that cannot be automated (that is, service jobs that cannot replace humans with robots). But this growth is not enough to offset the decline in non-interpersonal jobs. What’s more, research shows that job losses to automation are greatest among non-Asians of color, shedding light on the intricate connections between racial equity, economic trends, and technological advances.
As with any new technology boom, the recent explosion of digital tools in the workplace is neither good nor bad. But optimism and enthusiasm for progress must be balanced with an acknowledgment of the real effects these tools have on the people who interact with them – not always positive. As new research examines these diverse effects, leaders must constantly check their assumptions, avoid oversimplification, and work to base their decisions on the most up-to-date data and evidence, not knee-jerk reactions or gut feelings.