Navigating the ethical implications of AI in project management
According to a report from the Project Management Institute entitled AI Innovators: Cracking the Code on Project Performance, 85% of global CEOs predict that AI will have significantly changed their business practices by 2024. As AI tools increasingly pave the way for automation-driven business, it is more important than ever for project managers to consider the ethical implications that can arise from its usage. Navigating these sensitive issues around privacy and accuracy may be time consuming but it is an area that should not be overlooked.
What are the ethical implications that project managers need to be aware of?
Organisations and individuals that are making use of AI need to carefully consider the following ethical issues:
Data privacy and security
Data-driven AI often requires access to sensitive information about team members, project details and clients. It is vital that this information is carefully acquired and securely stored to ensure that those involved are aware of how their data is being used and data breaches are avoided.
Bias and fairness
If AI algorithms are trained with biased data, the resulting model may also be biased. In addition, it has the potential to create feedback loops that repeat and reinforce this, leading to unfair outcomes based on skewed representations.
Accountability and responsibility
When AI technology is relied upon to make decisions, it can then be hard to determine who is accountable for the outcomes, and if things go wrong who is then responsible for resolving them.
Dependency on AI
Over-reliance on AI can lead to a lack of critical thinking and reduced human decision-making, it is therefore important to consider which tasks will benefit from AI input and which are better managed by human team members.
Surveillance and monitoring
AI can be used to track project progress, and individual team members contributions to this, which could be seen to create a culture of surveillance where employees feel there is a lack of privacy.
How can project managers work to resolve these issues?
There are several actions that can be taken to minimise the impact of ethical implications on AI usage, such as:
- Collaborating with other team members when making decisions to ensure individuals don’t become too reliant on AI contributions
- Conducting regular audits and monitoring the use of AI
- Continuing to have human oversight through all stages of a project
- Creating a balance between the rates of human task completion and automation
- Creating a series of ethical guidelines to be followed by all team members
- Documenting AI use to keep track of the decisions that are made as a result
- Ensuring data collection and storage complies with regulations, such as GDPR
- Mitigating bias by ensuring a diverse dataset is used at the AI training stage
- Maintaining transparency regarding the usage of AI throughout the project team
The importance of training
Training can also be used to ensure ethical impacts are considered at all stages of project management. Understanding these practices is vital before implementing AI to your projects.