The modern workplace is increasingly multi-generational, with baby boomers working alongside millennials and Generation Z. To bridge the digital fluency gap, many organizations are implementing reverse mentoring programs, where younger employees share their digital expertise with older colleagues.
A recent study from Vanderbilt University examines the dynamics of these exchanges and the benefits for older employees. The researchers observed and interviewed professionals in the recording industry to understand how inter-generational collaboration functions.
Their analysis revealed that the regular influx of interns offers seasoned executives continuous insights into current cultural trends, which directly influence the company’s creative output.
Sharing knowledge
The research showed that companies are becoming increasingly adept at tapping into cultural knowledge through both formal and informal means. Interns play a crucial role in this informal process by simply being present in the office. Their clothing, tools, and language provide valuable insights into youth culture.
This informal process is complemented by formal approaches, such as intern-based focus groups and low-stakes assignments that allow interns to share their cultural knowledge.
However, the research also revealed that inter-generational collaboration is not guaranteed. Tensions between generations, stemming from differences in age and experience, can hinder effective collaboration and mentorship. The researchers urge organizations to address these challenges to enable more effective cooperation between generations.
No easy feat
A recent study from Harvard Business School underlines the challenges involved in extracting knowledge from junior colleagues. The study found that while younger professionals are often more likely to experiment with new technologies, and are therefore often a good source of technical expertise, senior staff should not take for granted that they’ll be a willing and reliable source of expertise.
The study explored the various obstacles that can get in the way of senior professionals improving their knowledge of technologies such as generative AI. They found that while junior colleagues are more likely to experiment with the technology, they shouldn’t be automatically considered to have sufficient expertise to teach their senior peers the lay of the land.
This can result in senior professionals getting a partial understanding of the technology, and especially some of the risks involved in its use, which ultimately undermines their own application of it.
Learning the ropes
The researchers interviewed a group of junior consultants with one to two years of professional experience and limited knowledge of generative AI. These consultants were given access to ChatGPT-4 to help solve a business problem and were asked about potential challenges in working with managers when using this technology.
The junior staff believed that managers would be concerned about the risks generative AI posed to accuracy and explainability. To mitigate these risks, they suggested making changes to human routines at the project level, having managers review the prompts used by junior staff and their results, and establishing clear agreements on when generative AI could be used reliably.
While these suggestions are not without merit, the junior professionals largely overlooked more company-wide measures to mitigate the risks associated with introducing generative AI tools more widely.
Unreliable expertise
After analyzing the responses, the researchers honed in on three specific reasons why junior employees aren’t the most reliable sources of expertise for senior colleagues to tap into.
Firstly, they found that junior employees can’t be relied upon to have a sufficiently deep level of understanding of the capabilities of generative AI.
Secondly, when analyzing the pros and cons of the technology, they were found to focus far more on human routines than on more system-level design.
This was further reflected in their tendency to focus primarily on challenges at a project level rather than looking at things from a company level.
“Historically, the main obstacle to senior staff learning about new technology from more junior colleagues was if they felt their status was being threatened,” the researchers explain. “Our research shows that generative AI presents a different set of challenges. Juniors who are working at a project level are more likely to focus on the specific risks they encounter.”
No short cuts
The fundamental nature of generative AI means that the technology relies heavily on data from an extremely broad range of sources, and the researchers remind us that this presents various risks to businesses at a company level.
While junior staff may gain a degree of understanding of the practical uses of generative AI through trial and error, it’s unrealistic to expect them to have the whole picture in view.
For instruction on the pros and cons of generative AI to be useful, the researchers believe that senior professionals need to focus on systemic and company-wide factors. They should also work directly with developers to ensure that the systemic capabilities are adequate, and especially to ensure the quality of data that is fed into the system.
“Senior professionals need to recognise that there are no shortcuts to learning how to use AI effectively and mitigating the risks. They require proper training,” the researchers conclude.
“They cannot simply follow the lead of junior professionals when adopting AI.”
