For accountants incorporating AI tools into their organisation, embedding ethical principles from the outset is essential. The key areas to consider will be familiar, as they align with the fundamental ethical principles outlined in the IESBA Code of Ethics:
- Integrity
- Objectivity
- Professional competence and due care
- Confidentiality
- Professional behaviour
These are critical concepts to keep in mind when integrating AI into your processes, to ensure ethics are embedded at every stage.
Hybrid intelligence
The future of finance lies in the synergy between AI and human expertise, known as "hybrid intelligence".
Hybrid intelligence finds a balance between the things that AI and humans are each good at.
Note also, that in a wider sense there are many ethical questions about whether AI could harm humans, or even take over the world, and how to prevent this. However, AI going rogue to the extent that it starts to battle against humankind is mostly beyond the scope of this blog. (If you are interested in an extreme and fictional scenario of this though, you might enjoy Linwood Barclay’s book Look Both Ways!)
Hybrid intelligence supports ethical practices by leveraging AI's efficiency while ensuring human oversight in critical areas, maintaining accountability, and addressing ethical concerns like bias and transparency.
It's vital to consider your organisational policies and how they might need to be designed to ensure that ethics is considered right from the outset.
Ethical guidelines
The EU's Ethics guidelines for trustworthy AI include a pilot version of a "Trustworthy AI Assessment List" which provides more detail on the key requirements for ensuring AI systems can be relied upon. The guidelines outline a number of questions, such as whether the organisation has carried out a fundamental rights impact assessment, to avoid any negative impact on fundamental rights.
Other useful points in the guidelines include asking whether the organisation has considered the allocation of tasks between the human and the AI. If there is human review of the output of AI, this can be used to mitigate the risks of issues arising, albeit there is still the risk of automation bias, leading the human to believe the output from the AI regardless of its robustness.
To ensure the successful integration of AI tools in accounting, it’s crucial to continuously evaluate and adapt ethical guidelines as technology evolves, maintaining a commitment to integrity and accountability. Ensure that AI’s data processing is combined with human expertise for informed decision-making.
Learn more about the ethical issues around AI and accounting with our 4-hour course AI and Ethics, here!
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