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Double-edged sword of AI in shipping

Artificial intelligence (AI) is poised to transform the transportation industry, particularly shipping, by optimising routes, reducing fuel consumption, and enhancing safety. However, the rapid development of AI also presents significant risks, including cybersecurity threats, data privacy concerns, and regulatory challenges.

As Han Deng, a partner at Reed Smith, explained in a recent podcast:
“AI can make a significant difference in sustainability across the whole of the transportation industry by decreasing emissions.”

By analysing real-time data on factors like wind speed and current, AI can determine the most efficient routes and speeds for ships, minimising fuel consumption and reducing emissions.

Oliver Beiersdorf, also a partner at Reed Smith, highlighted the safety benefits of AI. “AI can enhance safety features through the use of vision sensors that can respond to ship traffic and prevent accidents,” he said. Additionally, AI can create 3D models of areas to simulate the impact of potential disruptions and identify safety risks. “AI can be used with the transportation industry to assist with safety assessment and management by identifying, managing, and predicting various safety risks,” he said.

Cyber concerns
While the potential benefits of AI for maritime are substantial, the Reed Smith partners said it is essential to address the associated risks. Cybersecurity is a major concern, as cybercriminals can manipulate data inputs to cause AI platforms to misidentify malicious maritime activity.

“Things are just happening so fast that there’s a huge risk,” Beiersdorf said. “Cyber criminals who are becoming more and more sophisticated can even manipulate data inputs, causing AI platforms on vessels to misidentify malicious maritime activity as legitimate trade or safe. Actors using AI are going to need to ensure the cyber safety of AI-enabled systems.”

The unchecked use of AI could create and increase the risk of cybersecurity attacks and data privacy law violations, and frankly, create other risks that we haven’t even been able to predict.”

He added that shipping companies need to update their current cybersecurity systems and risk assessment plans to develop these threats and comply with relevant data and privacy laws. Beiersdorf gave the example of the recent CrowdStrike software outage on July 19, which affected almost every industry. “Interestingly, what we’re talking about there is really software that’s intended to avoid cybercriminal risk. A programming issue can result in systems being down and these types of massive disruptions because … we’re so reliant on technologies.”

Another challenge is the quality of data used to train AI systems. Inaccurate or misleading data can lead to imprecise predictions and for navigation, for example. Additionally, the high cost of AI technology may exacerbate industry fragmentation, as smaller companies may struggle to adopt these tools. “Poor economies will be unable to integrate AI platforms in their maritime … operations, which could fragment global trade. For example, without harmony in the AI use and proficiency, the shipping industry may see a decrease in revenue, a lack of global governance, and the rise of the black market dark fleets,” Deng said.

Investment in quality
To fully realise the benefits of AI while mitigating the risks, the maritime industry must therefore invest in cybersecurity, develop robust regulations, ensure the quality of data used to train AI systems, and promote collaboration and knowledge sharing.

Shipping companies should prioritise cybersecurity to protect their AI systems from attacks that could compromise data integrity and operational safety. This includes implementing strong security measures, regularly updating software, and conducting vulnerability assessments. Additionally, companies should consider investing in cybersecurity insurance to mitigate the financial impact of potential breaches.

Governments could work with industry experts to develop comprehensive regulations that address the unique challenges and opportunities presented by AI in the transportation sector. These regulations should strike a balance between promoting innovation and ensuring safety and security. They should also provide clear guidelines for the ethical use of AI, including data privacy and transparency requirements. Furthermore, regulations should be adaptable to keep pace with the rapid evolution of AI technology.

“The inability of regulators to keep up with this incredibly fast pace is another concern,”

Beiersdorf said. “And regulations are always reactive. AI continues to rapidly develop and regulations do not necessarily effectively address AI in its most current form.”

Additionally, companies should invest in data quality initiatives to ensure that the data used to train AI systems is accurate, reliable, and representative. This includes implementing data governance practices, cleaning and standardising data, and validating data sources. Additionally, companies should consider using data anonymisation and encryption techniques to protect sensitive data.

Collaboration between industry stakeholders, researchers, and regulators is also essential to address the challenges and opportunities of AI in the transportation industry. This includes sharing best practices, conducting joint research, and developing industry standards. As an example, Hamburg Port Authority (HPA) and the Maritime and Port Authority Singapore (MPA) recently signed a letter of intent to further their collaboration in cyber security, digitisation, and decarbonisation. The goal is to establish co-operation projects and activities that will improve the efficiency and sustainability of both ports. The collaboration could facilitate the transmission of cyber security information.

Finally, international co-operation is also crucial to ensure consistent regulations and standards across different jurisdictions.
Source: Baltic Exchange

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