Applying an ethical lens to the use of technology
AI must be used ethically and responsibly, and this consideration should be part of every project analysis, primarily to eliminate two key risks – bias and the responsible use of data, says Brynjolfsson.
One significant risk with AI is that it can amplify biases and misconceptions within an organisation because these systems learn from the data already in use. However, the good news is that it’s easier to correct bias in machines than in humans.
“Ultimately, I’m optimistic that AI-based systems will end up being less biased than the humans they were trained on. It’s very hard to teach a person to stop being biased, although we all try.
“But with AI, you can codify, identify and eliminate bias to a much greater extent,” he says.
Another key concern is the responsible use of data and data provenance. These systems are often trained on data from various sources, so it’s crucial to ensure you have the rights to use that data, both internally and externally, without violating privacy.
The risk of data leaks or misuse must also be mitigated with proper technological safeguards.
Developing new skills
To fully leverage technology, finance professionals need to expand their toolkit and understand how AI can enhance their ability to analyse businesses more comprehensively, argues Brynjolfsson.
He explains that the exciting aspect of AI is that it’s revolutionising how finance professionals understand their organisations.
“Finance has always been data-driven, giving professionals an edge in understanding their business.
“But now, with large language models [LLMs], we can analyse not only quantitative data but also vast amounts of verbal, text and visual data – often the majority of the information within any organisation.”
This means people can give simple instructions to create complex applications, analyses, and summaries that weren’t possible before. It allows for assessing job functions to determine how certain tasks can be automated or augmented.
“A job might consist of 26 tasks, and perhaps six of those tasks disappear. But the remaining 20 overlap with new responsibilities, allowing the individual to be re-skilled for the evolving role.”
This task-based and skill-based analysis provides a way to manage both technology and human capital — arguably the most valuable asset in any organisation.
“As I wrote with Andy McAfee in a Harvard Business Review article a few years ago, ‘AI is not going to replace managers, but managers who use AI will replace those who don’t.’
“This is especially true for CFOs, and it’s something that will impact much of the workforce,” Brynjolfsson concludes.
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