AI must be a tool for progress and not exclusion to attract women to shipping, says Columbia Group's Head of AI

Columbia Group is encouraging industry leaders to implement AI within their businesses to ensure digital processes are not blocking the progress made in attracting more women to shipping.

Columbia Group says because AI is based on previous data which may display a bias against women, it's imperative to embed AI within the business so it can be used to make shipping more appealing to attract future generations of women.

Newly-appointed Group Head of AI, Christina Orfanidou said; 'Artificial intelligence is often spoken about as if it were a perfectly neutral system, yet it remains entirely dependent on the information we choose to feed it. In shipping, where women make up only a very small proportion of the global workforce, this information inevitably reflects decades of imbalance. If we allow AI to learn uncritically from that past, we risk creating tools that appear modern while quietly reinforcing patterns we are striving to change.'

'If historical data shows women appearing less frequently in certain roles or ranks, a model may interpret that scarcity as a natural rule,' she added.

However, she emphasised that AI can reduce administrative work and improve decision-making if used in the right way in areas such as crewing, knowledge management and operational planning:

Ms Orfanidou says her focus is on embedding AI rather than treating it as a separate area. She said it is vital tools are built in partnership with the people who understand the realities of vessel operations, crewing, safety and HR, because they understand where bias might hide.

AI can help by reducing time spent on routine tasks and allowing people to focus on roles that require judgment and expertise, Ms Orfanidou explained. 'When used responsibly it can make the industry more appealing, more modern and more aligned with how people today expect to work.'

Ms Orfanidou, an Oxford University-educated doctor of machine learning/information engineering, warned it is important to know when to challenge AI and avoid over-reliance as AI can be 'persuasive even when inaccurate.'

While the lack of global standardised regulations is a concern when it comes to AI, there are regional frameworks being executed. The European Union has implemented a framework governing the development of AI, with requirements on non-discrimination.

However, Ms Orfandidou stressed: 'If we handle AI well, it can support inclusion rather than undermine it and it can broaden access to opportunity, reveal emerging talent and create more consistency in how decisions are made. If we handle it poorly, it can quietly close doors that the industry has spent years trying to open.'

Whether AI becomes a force for progress or a mechanism for exclusion depends on the choices businesses make, Ms Orfandiou believes:

'At Columbia, our commitment is to build AI that reflects the industry we want to see, rather than the one the data remembers,' she added.