While AI is in its infancy, we have seen early warnings about how artificially intelligent decision aids could hinder employees’ sense of meaning at work. 

As our workplaces have become increasingly digitalized, the amount of information that employees have to manage has skyrocketed. In already stressful positions, this data abundance can lead to information overload, technostress, and difficulty making decisions.² 

Therefore, it makes sense to introduce a highly effective AI decision-maker that can cut through the noise and choose for employees — right? Not exactly. Evidence shows that when AI tells employees what to do, they tend to grow skeptical of the technology. The end result: they become even less likely to use AI to facilitate their work.² 

If this seems counterintuitive, just imagine having a boss who micromanages all your decisions, but can’t even communicate how they came up with the solution they want you to implement. Sounds frustrating? When AI is given completely free rein, it is easy to end up feeling like a cog in the machine, simply an implementor of a computer’s confusing decisions.

Consider IBM’s Watson for Oncology. This supercomputer could accurately identify 12 common cancers and provide expert-level recommendations for them.³ It was designed to help doctors make more accurate assessments and not purely rely on gut instinct. 

When put into the field, however, IBM Watson didn’t mix well with the doctors. When it made recommendations that agreed with theirs, the doctors saw it as redundant. When it made recommendations that contradicted them, they saw it as faulty. Because its machine learning algorithm was so complex, it couldn’t give justification for its reasoning, which made the doctors less trusting and more stressed. It was a PR nightmare for IBM, whose medical partner later dropped the program.³ Clearly, integrating AI decision aids must be done with human users in mind.

So, what do we do? Balancing management’s pushes to quickly integrate AI and a workforce that needs to find fulfillment in their jobs, we cannot proceed recklessly.

We must first understand the science behind meaningful work, and then integrate AI in a way that doesn’t infringe on employees’ quest for purpose.

To tap into this mysterious question of purpose, we must first understand that human beings fundamentally require three psychological nutrients to feel motivated:⁴

1. Autonomy: The feeling of control over one’s own actions, thoughts, and goals. 

2. Relatedness: The feeling of meaningfully connecting with others. 

3. Competence: The feeling of growth and gaining mastery over skills. 

Together, these three facets make up self-determination theory, an evidence-based motivation framework. Fulfilling these requirements in the workplace has several beneficial downstream implications: employees will feel more intrinsically motivated, which leads to greater performance, job satisfaction, well-being, organizational citizenship, and positive work-related attitudes.⁴ 

In addition to self-determination theory, a bevy of research into workplace fulfillment has found two more essential facets of meaningful work:⁵ 

4. Significance: A perception that one’s work is worth doing (i.e. is intrinsically valuable).

5. Broader purpose: The idea that our work must contribute to something bigger than oneself, or the greater good. 

In essence, work that helps employees grow, build relationships, do things they value, and positively impact the world will be seen as meaningful. If AI decision aids are coming, they must be implemented in a way that doesn’t detract from why we go to work in the first place. But how do we go about doing this?

Human-centric design, with a focus on self-determination theory, can bring employees improved satisfaction, stronger trust, and greater confidence in the decision-making process. When done correctly, it can even make employees more engaged, leading to more efficient and accurate decisions.

Autonomy: putting the power in the employee’s hands 

Autonomy is perhaps the most important facet. When an AI is making all the decisions, how do you feel like you are in control? Thus, it is critical to design some element of choice into the equation. 

Simply providing users with the option to ask for help from the AI, rather than the AI automatically providing information, has been shown to elicit strong feelings of autonomy.⁶ In one study, participants who were allowed to interact with an AI decision aid on their own terms were more satisfied with the bot — and more engaged with it — compared to participants who didn’t have a choice.

To ensure both employee satisfaction and better decision-making, it is essential to strike a balance between AI use and autonomy. If employees feel like an AI is running their life, they’re not likely to use it. But if AI is just another tool in their arsenal, then adding an optional decision aid can empower employees instead of stifling them. 

Competence: show, don’t tell

AI systems are complicated, and thus are difficult to understand. This confusion is a big threat to feelings of competency.⁶ However, if we make room for growth within AI–employee interactions, we can allow employees to feel like they’re learning. 

Instead of keeping AI’s processes a black box, showing employees a simplified, educational version of how the AI came to the solution will  help them: 

1. Understand the system better 
2. Feel like they are learning and improving. 

As AI becomes more complex, it will get more difficult to teach employees exactly what is going on under the hood. Even if it is just the broad strokes, adding an educational element to AI recommendations has been shown to boost feelings of competence. This doesn’t only benefit workers’ well-being; it also can lead to more accurate decision-making, improving outcomes for both employees and their organizations.⁶ 

Relatedness: say hello to your new Robo-friend! 

To tackle relatedness, AI decision aids must take on more human characteristics. For example, simply programming a chatbot to refer to itself as “I” and address the employee by their first name dramatically improves feelings of relatedness.⁶ Additionally, representing the AI with an avatar makes employees feel like they are collaborating with a human, rather than being told what to do by a machine.⁶

Purpose: The final frontier

However, employees’ sense of meaning doesn’t stop with self-determination. As noted above, workers also need a sense of significance and broader purpose to be fully motivated. AI is an incredibly powerful tool on this front, with the ability to scale social change to a shocking degree.⁷ If leaders embrace technological social responsibility, they can align their AI efforts with the social good.⁸ This purposeful use of AI will not only bring transformational positive change, but should also lead to higher feelings of purpose in employees.

We are standing on the precipice of an AI-enabled world. It is difficult to predict what its development will mean for the workplace, the economy, or the future of humanity. Connecting scenario planning and behavioral science, we predict that AI will be used as a decision aid, which could threaten a worker’s sense of intrinsic motivation. 

Leaning on human-centric design, we can mitigate the negative effects of AI decision aids by tailoring them towards satisfying needs for competency, autonomy, and relatedness. Additionally, aligning your company to a broader social purpose will make AI-assisted decisions feel more necessary, just, and meaningful.

The Decision Lab is a behavioral consultancy that uses science to advance social good. Artificial intelligence and its implementation have the potential to radically transform all facets of human life and business.  Working alongside tech giants, we have learned how to leverage big data to create big impact. If you are interested in integrating artificial intelligence into your organization in a human-focused, socially impactful way, contact us.