Why Maritime AI Must Serve Seafarers – and Not Replace Them

In all industries, the emergence of AI brings unprecedented opportunities for progress and precision– while at the same time causing alarm among professionals who fear they might be replaced and lose their livelihoods. In this respect, the maritime industry is no different, as AI redefines shipping across numerous key parameters. Many mariners view this as a hostile takeover and a lack of confidence in their capabilities. This article presents the case that maritime AI is not intended to substitute seafarers, but rather support them in taking situational awareness, route optimization, fuel efficiency and sustainability to the next level.

Pressure at Sea: Pinpointing the Relevance of Maritime AI 

The modern maritime industry is under increasing pressure to improve on several key fronts. Perceived as having the capability to generate meaningful change, AI-powered solutions are being adopted by countless fleets worldwide to assist in fulfilling ambitious goals:

• Regulation Compliance: Trading fleets must adhere to regulations such as FuelEU Maritime and CII, which require them to lower their carbon emissions and become more energy efficient. Vessels must also analyze their data, track their progress and conduct annual reporting to governing entities. AI not only helps vessel managers improve fuel efficiency and optimize routes from an energy perspective, but also to categorize and translate vast amounts of data into easy-to-understand reporting.  
• Reducing Collisions at Sea: Despite heightened awareness, collisions and ‘near collisions’ are still a major problem for shipping, with over 200 incidents occurring on an annual basis – causing casualties and harming ships and cargo. Alongside traffic density and unforeseen weather conditions, the leading cause for accidents remains human error. It is generally accepted that AI-based lookouts and predictions can help fleets worldwide lower collision rates.   
• Minimizing Delays and Cutting Costs: Today’s global supply chain challenges increase delays and often force vessels to change their route planning while at sea to deal with unforeseen situations. Every delay and change of route carry financial implications, and predictive AI can minimize such surprises and improve planning before leaving port and while in transit. 

The Crew Resists: Viewing AI as a Potential Threat

There are numerous reasons that some seafarers – including senior officers – view AI as a threat to their profession. For starters, many envision AI as rapidly transitioning shipping towards total autonomy, with proof coming in the form of autonomous ships that require little to no crew on board. 

But that’s not all. AI is disruptive, and naturally, many seafarers who are accustomed to achieving positive results by using dependable methods, are not necessarily open to major changes that may redefine their roles and alter traditional ways of working. Furthermore, some mariners may feel threatened by technologies that recognize and interpret data faster than humans can. And not least, many raise concerns regarding the issue of accountability. If the crew adopts an AI-based recommendation that turns out to be false, who is responsible – man or machine? 

While it is clear that these are all legitimate concerns, industry leaders stress that AI systems should be viewed not as decision makers, but as decision supporters. Fully autonomous ships remain a distant reality, and crew professionalism remains of the utmost importance as the vessel depends on seasoned decision-making, human responsibility and accountability. Optimal results are achieved through a fine balance between AI and experienced crew capabilities, and not through an over-reliance on precision-based technology.

Working Together: The Positive Impact of AI and Humans 

Less collisions, better fuel efficiency and optimal route planning – these three parameters can be revolutionized by vessel crews who can leverage their experience by relying on AI data analysis, predictions and real-time insights for higher performance:

Collision Avoidance

When it comes to sudden maneuvering due to unforeseen risks, humans must be in control, calling the shots. Yet AI-driven situational awareness provides the captain and bridge team with valuable real-time data that the human eye cannot detect. For example, Orca AI’s SeaPod uses advanced computer vision to spot potentially dangerous objects from afar, way beyond the human visibility range, including small boats, buoys, partially submerged containers and more. Early detection is key for collision avoidance, as it gives the crew ample time to make an optimal decision.

Furthermore, while AI bridge lookout systems like SeaPod have enhanced detection capabilities, they can also reduce false positives, prevent “false alarm” scenarios and minimize the workload on the bridge. This results in crews that are not overworked, who can execute their assignments with maximum freshness and alertness in low visibility conditions, in congested waters and when approaching port and docking. 

ReducedFuel Consumption

A number of factors impact fuel consumption, namely vessel speed, maneuvering, rerouting and engine maintenance. Maritime AI can equip the crew with precise real-time data – not to mention data-based recommendations – on such parameters. 

By tasking on-board AI with tracking fuel consumption, these advanced systems can generate constant speed optimization recommendations based on the current route, weather and situation at sea. Furthermore, AI systems can compare historical trends and data coming in from other vessels in the same fleet to create better fuel efficiency on any given voyage. Engine data analyzed by AI systems can lead to advice regarding engine settings and preventative maintenance sessions. Finally, with AI’s heightened situational awareness, hazardous objects can be detected much earlier than usual, allowing the crew to avoid sudden maneuvering that burns more fuel.

Ultimately, AI assumes roles that are difficult for humans to execute quickly and on a regular basis; yet execution and decision-making regarding speed, alterations and engine performance always remains in the hands of the crew.

Optimized Route Planning

In the past, route planning stressed the importance of timely ship arrival, relying on static methods that do not view dynamic weather, sea conditions and port congestion as key parameters. Yet today, especially with heightened safety awareness and the IMO’s 2030 net-zero emissions plan, other factors such as fuel efficiency and collision avoidance come into play when planning the ideal route. Complementing this approach is advanced AI technology, whose insights can help ships make routing adjustments in accordance with weather, traffic and other dynamic elements.  

However, as AI systems generate optimized route planning recommendations during the ship’s voyage, the final authority regarding route changes belongs to the captain and crew. Every route planning change contains a multitude of implications, and thus clearly requires human discretion and professionalism – not to mention accountability.

Industry Essentials for Success

In order for maritime crews to truly benefit from AI as they safely navigate their vessels, several essentials must become industry standards: 

• Human-centric system design: In order for maritime crews to have an easier time relying on AI insights, AI systems must feature intuitive, user-friendly design that facilitates seamless interaction. When it comes to technology, simplicity invites engagement. Complexity, on the other hand, increases detachment and frustration. 
• Real-world AI training: The more experience AI systems collect, the better they perform. Once integrated onto a vessel, AI systems can deliver great results from day one, but as they accumulate vast amounts of nautical data, they gradually perfect their classification and prediction capabilities. 
• Supervision and feedback: Real-world AI training requires the supervision of a seasoned crew who can monitor certain actions, are always aware of their AI’s progress at all times, and can give feedback regarding errors that gradually refines alerts and recommendations.

Looking Ahead: What Will the Future Look Like?

As AI integration increases across fleets and vessels, many seafarers may still wonder what the future holds for their profession. 

While AI certainly fuels the autonomous shipping conversation, the truth is that commercial fleets are decades away from actually operating crew-less ships. Even autonomous ships will include essential workerswho will be able to monitor autonomous systems, make decisions and override processes when necessary. This is backed by the IMO and maritime regulatory entities, who stress the importance of human insight and experience even in the most advanced autonomous shipping frameworks. 

“Automation addresses pain points, but does not replace the human need onboard,” says Dor Raviv, Orca AI’s CO-Founder and CEO. “AI empowers people – it doesn’t replace them.”

While marine crews will always be necessary, their roles and methods will surely change. In all probability, on-ship personnel will experience a reduced workload during the voyage, as they rely on AI systems to receive and interpret valuable data. As a result, a main skillset will include effective interaction with AI systems and advanced data interpretation that can facilitate superior decision-making. This requires extensive AI training programs for seafarers, which are already underway in leading naval academies and commercial fleets.

Human Navigation, AI Assistance

In conclusion, ship crews are more essential than ever – even in today’s AI age. As maritime shipping embraces AI with high hopes, industry leaders are setting ambitious objectives in terms of safety, energy efficiency, sustainability and financial effectiveness. Yet to achieve these objectives, AI precision is not enough – there is an acute need for suitably trained seafarers who can utilize AI to make better decisions, achieve higher operational efficiency, comply with complex regulations and adhere to strict economic frameworks.