How To Build Trust with Your Employees Through Data Dignity and Collaborative Intelligence
People are talking more and more about data dignity and collaborative intelligence–especially since AI really took off. But the discussion often revolves around these concepts with consumers in mind–which, of course, is crucial. But people aren’t always ‘just’ consumers, they’re employees, too.
How can these concepts be translated to benefit the relationship between employers and employees? Does data dignity hold up in that space? And how can collaborative intelligence be used to improve trust within a business?
In this article, we’ll explore this slightly different angle of these concepts, with a focus on the trust between employees and employers.
We’ll give some practical tips on how to integrate data integrity within a business, and make collaborative intelligence more tangible, too.
What is data dignity?
Data dignity refers to the idea that individuals should have control over, and be able to benefit from, the data they create directly or indirectly. It’s a framework that advocates for the rightful ownership, control, and remuneration for the contribution of personal and professional data in various systems, especially in digital platforms.
Data dignity in the workplace specifically is still being shaped and will look different in every company. In essence, it involves thoroughly briefing employees on the nature of the data to be collected, its intended use and who will have access to it, with an option to opt-in or opt-out. We’ll dive deeper into that further on.
What is collaborative intelligence?
Collaborative intelligence refers to the synergy between human and machine capabilities to enhance decision-making and problem-solving in a work environment.
With this, human creativity, leadership, and experience can complement the speed, scalability, and data-processing abilities of artificial intelligence and other technological tools.
Through a collaborative framework, employees and AI agents work together. AI takes care of repetitive or data-intensive tasks, freeing up human headspace to focus on more strategic, creative, and higher-value activities.
AI is already being used in different departments, such as AI for recruitment, marketing and sales. There’s a tool for virtually every team.
The deal about data and trust in the workplace
People are more and more cautious of what data they share and how it is being used–and that is no different in the modern workplace.
We’re asking ourselves, ‘Why do they need to know that?’ on a regular basis, and without a transparent answer, trust fades quickly, especially when it’s your employer who doesn't have a clear-cut answer. It might feel like strict surveillance, or we wonder if they’re making money from our data.
Everybody knows data is considered the new oil, but employees might feel short-changed if they don't see any tangible benefits from the data they provide.
How employers use employee data
Employers might use data on employees for a number of reasons.
- Performance monitoring
An employer could use data to monitor and analyze employee performance, finding strengths and areas of improvement. This could help tailor professional development programs and other HR strategies.
- Operational efficiency
Data helps in streamlining operations and identifying bottlenecks–especially if you can analyze data per employee. This could help facilitate better workflow management.
- Compliance and legal obligations
A common use of data is to check whether employees are complying with legal and regulatory obligations.
- Safety and security
Data collection can play a huge role in ensuring the safety and security of both personnel and organizational assets.
How data dignity can increase trust in the workplace
The keyword here is transparency–on an individual, case-by-case level. Employers need to be ready to provide clear, comprehensible explanations regarding the purposes behind data collection.
This starts in the interview stage and onboarding sessions. If you’re asking employees about specific information (apart from standard info like their name), have a readily available answer on what the data will be used for. Further down the line, there’s a lot more you can do with data dignity in the workplace. Here’s how to build trust around data:
Show how data affects the day-to-day, and the long-term
When data is being used to improve efficiency or check compliance, illustrate clearly how data-driven insights will lead to better working conditions or other direct benefits. Show how data contributes to organizational goals.
Transparency about employee monitoring
Be honest about what is being monitored and how. It’s best that employees don’t find out after the fact that something is being monitored.
Be proactive
The key here is to be proactive. If employees need to go on a quest for these answers, there’ll already be some mistrust. From day one, clearly communicate where they can find info on how their data is used and who they can ask for more clarification.
Define data value in the workplace
While fair value-sharing is difficult in all settings, and especially in the relationship between an employer and employee, at the very least, the value of efficiency can be shared.
Involving employees: Involve employees in discussing data practices, and where they have control, give it to them.
Could you really ‘pay’ employees for their data?
This is a tricky one. Not just for determining the value of individual pieces of data, but also for how to navigate tax implications for payments based on this.
Solutions like the Toku token tax solution can resonate well with the ethos of transparency and fair value exchange.
For instance, consider a scenario where a company employs a blockchain-based rewards system to incentivize employees' innovative contributions. Here, employees earn digital tokens, which can be exchanged for various benefits.
However, the tax implications of these digital transactions can be murky and complex. By deploying a Toku token tax solution, the company can provide a clear, compliant, and transparent method of handling the tax obligations arising from the distribution and exchange of these digital tokens.
This not only simplifies the tax management process for both the employer and employee but also aligns with the principles of data dignity.
Empowering your employees
If it’s not absolutely vital for employees to share specific information, make it easy for them to opt-out. In this, the implementation of data subject access request software is paramount. This software allows employees to have a tangible grasp of the data collected from them by providing a streamlined channel to request access to their data.
Employer-employee pact on data
You could consider creating an employer-employee pact on data. This could involve an easy-to-read document with clear, fair, and transparent data policies.
Collaborative intelligence and trust in the workplace
It’s safe to say that not everyone is yet on board with all things AI. Some people fear it will impact their job, or that they'd even lose their job. Others don't trust the answers it might give or the way it came to those answers.
But the truth is, AI isn't going anywhere, so collaborative intelligence is something you use to get ahead of the competition now, or you’ll be catching up later.
Now, how can artificial intelligence and digital experience increase trust between humans and between humans and organizations?
While collaborative intelligence very much stands at the crossroads of human innovation and artificial intelligence, it can be used to solve complex problems with a human and machine-like touch.
So, when deployed conscientiously, collaborative intelligence can not only propel operational efficiency but also nurture a culture of trust and openness. Here’s what to keep in mind.
Communicating the benefits
When you do decide to combine strengths, it’s crucial that everybody is on board and fully supports this decision. That starts with highlighting the reasoning behind the decision to work with AI to make work easier or more effective.
Inclusive decision-making and design
It helps to engage employees in the decision-making processes, especially when designing, training, and refining the AI systems they interact with. The more they get to know the behind-the-scenes of the system, the more they’ll trust what comes out.
Continuous learning
Collaborative intelligence is not something that is set in stone yet, nor will it ever be. Find ways to promote a learning environment where your people can learn to use the systems better and learn through the systems.
Set up clear ethical guidelines
One thing you can't skip over is clearly addressing the ethical concerns around AI and machine learning. Listen to the concerns people have, and teach them about responsible use of the technology.
Reinforce data privacy and security issues
Now’s the time to recommit to data privacy and security practices to make sure there’s optimal trust in the collaborative systems you put in place.
How are you addressing AI, data and trust in your business?
It’s an interesting time. Some businesses are taking the lead in nurturing a culture where trust, artificial intelligence, and data go hand in hand, while others are still waiting to see what the rest of the world is doing. What will you do–move forward and establish trust early, or wait it out?
