Many employees are being tasked with utilising artificial intelligence (AI) in their workflow, and they are growing increasingly concerned about the potential bias created by the technology or losing their jobs to it.
In this Q&A interview, Duncan Harris, director in the Gartner HR practice, unpacks what’s behind employees’ fear of AI, and how leaders can help them overcome those fears to realize the full benefits of AI.
What do employees fear when it comes to AI in the workplace?
Our research has identified five unique fears employees have about how their company will apply AI:
* Job displacement due to AI that makes their job harder, more complicated, or less interesting;
* Inaccurate AI that creates incorrect or unfair insights that negatively impact them;
* Lack of transparency around where, when, and how the organisation is using AI, or how it will impact them;
* Reputational damage that occurs because the organisation uses AI irresponsibly; and
* Data insecurity because the implementation of AI solutions puts personal data at risk.
When employees have these fears, they all have a substantial impact on either the engagement of the employee, their performance, or sometimes both.
How can organisations overcome these fears and build trust with employees?
Organisations will see the biggest improvement in employee outcomes if they tackle all five employee fears, however they will also see gains if they address fears individually.
Here are ways organisation leaders can address each unique employee fear:
* Become a partner on AI education to alleviate concerns of job loss. Employees are concerned about losing their job to AI; even more think their job could be significantly redesigned due to AI. Help employees understand the technology by offering training or development on a range of topics, such as: how AI works, how to create prompts and effectively use AI, and even how to evaluate AI output for biases or inaccuracies.
* Co-create solutions with employees to reduce fears about inaccuracy. Employees think that inaccuracy or bias created by AI will negatively impact their role or performance. Companies that show how AI works, provide input on where it could be helpful or harmful, and test solutions for accuracy can allay fears.
* Communicate context to avoid fear of the unknown. Few organisations are being fully transparent about how AI will impact their workforce. Organisations cannot just provide information about AI; they need to provide context and details on what risks and opportunities are influencing their AI policy, and how AI relates to key priorities and company strategy.
* Democratise accountability for AI ethics to minimize reputational risk. Organisations need to formalise accountability through new governance structures that demonstrate they are taking threats seriously. For example, to boost employee trust in organisational accountability, some companies have deputised AI ethics representatives at the business unit level to oversee implementation of AI policies and practices within their departments.
* Operationalise employee data rights to ensure privacy. o increase worker trust, organisations should establish an employee data bill of rights to serve as a foundation for policies. The bill of rights should cover the purpose for data collection, limit the data collected to the defined purpose, commit to use data in ways that reinforce equal opportunity, and recognise employees’ right to awareness about the data collected on them.
Why is it important to build employee trust when it comes to AI?
AI has the potential to create high business value for organisations, but employee distrust of the technology is getting in the way. Leaders involved in AI cite concerns about ethics, fairness, and trust in AI models as top barriers they face when implementing the technology.
Employee concerns are not fear of the technology itself, but fear about how their company will use the new technology.
If organisations can win employees’ confidence, the benefits will extend beyond just AI projects. For example, high-trust employees have higher levels of inclusion, engagement, effort and enterprise contribution.