The Impact of Artificial Intelligence on Maritime Safety and Security in West Africa

Posted: March 14th, 2024

The Impact of Artificial Intelligence on Maritime Safety and Security in West Africa
1. Introduction
1.1 Background
1.2 Research Objectives
1.3 Significance of the Study
2. Overview of Maritime Safety and Security in West Africa
In West Africa, the maritime security environment is defined by a number of security challenges. There is a need to protect the marine environment from pollution, smuggling, piracy and robbery at sea, and maritime terrorism. However, those challenges are compounded by limited national and regional maritime security capabilities, with many West African countries lacking the resources and infrastructure needed for effectively monitoring and protecting their waters. Even in areas where some surveillance and enforcement capability exists, such as in the Niger Delta or off the coast of Nigeria, security efforts are often undermined by widespread corruption. There is a lack of investment in the infrastructure needed to support effective maritime domain awareness and security, and this makes it easier for criminal groups to exploit the weaknesses in maritime security and oversight. The Apapa Port in Lagos has been particularly affected by congestion and delays to shipping caused by the lack of effective maritime security and by ongoing issues with corruption and smuggling. This has an impact on the wider economy, for example leading to increased costs for importers. As a result, both the marine environment and the economic development of coastal West Africa is being affected by the inability to effectively address these security challenges. It becomes clear that safeguarding the marine environment and ensuring the proper functioning of maritime economies is essential in supporting the economic growth and development of West Africa. This is emphasised by the ‘2030 Agenda for Sustainable Development’, adopted by all United Nations Member States in 2015, where Goal 14 is to ‘Conserve and sustainably use the oceans, seas and marine resources for sustainable development’. This outlines that across the region, it is essential to ensure the safety and security of the waters of West Africa, from both a regional development perspective and as a way to contribute to global sustainable development as well as a way to contribute to global sustainable development.
2.1 Current Challenges
Looking at the challenges and problems in terms of maritime safety and security, three important things come to mind. Firstly, West Africa’s coastline of approximately 31,000 miles is vast and continuous patrolling and surveillance has always been difficult for the navies and coast guards. This becomes more compounded by the fact that piracy and armed robbery at sea is high throughout the region. Secondly, weak national legislation and little regional cooperation has in many ways prevented an effective anti-piracy measure in West Africa. At the moment, most of the regional countries do not include piracy as a serious criminal offense in their legislation and this has impacted on the way piracy is being fought. Again, there is little or no cooperation between the states when it comes to sharing intelligence and also in terms of arrests and prosecution of pirates. All these legal, intelligence sharing and prosecution failures have continued to hinder significant improvements in the fight against piracy in West Africa. Thirdly, the lack of reliable and accurate data on maritime safety and security issues affecting the region has greatly served as a challenge. Most of the intelligence and data being shared in the region has been overlaid with political and sometimes financial interests of some regional countries and therefore intelligence sharing has suffered setbacks. However, it’s important to note that the International Maritime Bureau (IMB) is providing piracy and armed robbery report every three months, yet the report cannot be used as a blueprint to or a guide to regional solutions because of the fact that IMB’s report tends to generalize the security analysis for the huge region of West Africa. This makes the intelligence not too precise to fit the localized maritime security appraisals of individual countries. It is therefore clear that the challenges in the maritime security and safety in West Africa are inextricably linked to a number of larger political, economic and social challenges in the region. Therefore, it is important to understand these wider challenges so that a workable and more robust maritime security strategy can be formulated to suit the areas concerned.
2.2 Importance of Enhancing Safety and Security
Maritime safety and security not only impacts the daily operations and efficiency of the maritime industry, but also has broader implications for the environment, human safety, and economic development. West Africa is a region with a long coastline and an Exclusive Economic Zone that stretches into the Atlantic and Indian Oceans. As such, there is a strong focus on how to make the maritime domain safer and more secure for all. The corresponding improvement of maritime safety and security driven by technological and scientific advances has resulted in enormous benefits to the global economy and the quality of human lives. For instance, the use of satellite techniques in enhancing communication to meet the Global Maritime Distress and Safety System (GMDSS) requirements has significantly improved the provision of coast earth stations and geostationary satellites to enable global maritime distress and safety applications. Nowadays, merchant vessels are required to transit to the GMDSS sea areas to report stowaways, enhance anti-terrorism, and validate ship security. A crucial system that has been in focus is the Automatic Identification System (AIS), which was initially designed as an anti-collision system to support Vessel Traffic Services (VTS). It has been widely used as a method of tracking the location of ships. However, little attention has been paid to the development of an alert system brand, which is a critical area for satellite-based technologies, because the current AIS system provides no practical way to generate automatic alerts. Further connectivity using satellite technology between ships and ports is greatly enhancing the shipping industry and improving operational efficiencies. This has positive impacts on maritime safety and security by bringing a higher level of monitoring conditions and real-time risk analysis. Modern technology such as online monitoring, alert and prevention systems based on satellite connectivity offers great advantages in improving environmental protections from ship-based pollution, especially in a unique area like West Africa where the maritime safety and security infrastructure is still under development.
2.3 Role of Technology in Addressing Challenges
Therefore, the capacity to address key regional maritime challenges hinges on how decision makers in West Africa leverage technology, IBS, AIS, and innovation to meet maritime-related demands. Emerging technologies such as unmanned and autonomous surface vessels, aerial remote-controlled drones, multispectral satellites, GSM communication, internet, and digital systems are being used and yielding results in the efficient surveillance of countries’ territorial waters, ports, and strategic facilities. However, it is important to note that the technology itself is not a solution. It should be part of a combustion formula involving government, industry, research, training, and social reforms in order to produce efficient and sustainable extensive impacts on maritime safety and security. In this mix, all stakeholders must constantly be part of a dynamic process that keeps throwing up challenges and which should be addressed using modern technologies in innovative ways. Public-private partnerships in countries where the capacity to fund technologically driven security is low need to be promoted while ensuring that ambitions are grown in less healthy areas, not just making do with limited resourced existing provisions. Cybersecurity has also gained promising ground in the annals of technology-driven maritime safety measures. Regular sponsored security audits of all maritime information and operational technology systems at various levels are being provided in order to guarantee watertight cybersecurity fortification. The introduction of specialized cybersecurity capacity building funding and infrastructure development are part of a more coordinated government-led initiatives to beef up the safety of digital systems in a more advanced technological paradigm in the West African maritime domain. On the whole, while traditional methods and challenges remain, new and emerging technologies have provided new solutions and further highlighted the need for continuous capacity building and innovative thinking in achieving sufficient progress in ensuring a safe and secure maritime domain in West Africa. As a matter of fact, the role of technology has led to unprecedented dynamism and evolution in responding to the incessant and fluid nature of maritime security threats and challenges. Used differently and socially sown in the fabric of regional reforms, security and capacity building, newer technologies will ensure that cost-effective and targeted solutions that respond to challenges in a harmonized and unified format are deployed to drive revolutionary impacts on safety in the West African waters. This capability and prospect should be seen as part of a continuum in which short-term technology transfer goals form the foundation for the long-term sustainability of improved safety that can only come from homegrown and local technological and social solutions. In this exciting time that technology presents, West African leaders have today at their disposal both the tools and the possibility to carve out ambitious, far-reaching, and impressive visions of a technological domain that holds the promise of transformative impacts to enhance maritime safety and security. Such a prospect has never been more plausible and material due to the lead and rapid developments in maritime safety and security driven most importantly by technology. Albeit so, the willingness to invest, manage, and control the inherent risk presented by the increasing interconnectedness of technological solutions must be tempered by strategic and clear-sighted governance, legislation, and ethical oversights. Such mechanisms should serve as the custodian to a healthy, innovative yet secure technology-driven prospect for a safer and sustainable maritime domain in West Africa. And the beneficiaries of such sustainability and the security dividend will always be the brotherly and industrious people of West Africa.
3. Artificial Intelligence in Maritime Safety and Security
The integration of artificial intelligence (AI) in the maritime sector has brought considerable changes in the field of maritime safety and security. AI, as defined in the previous section, is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Especially since the 21st century, AI has found its place in every walk of technological sector and its applications are significantly embraced by many industries, including maritime domain. In the maritime sector, AI has a wide range of applications in different domains such as collision avoidance, navigational safety, marine environmental protection, search and rescue operations, maritime security, and so on. AI can provide the tools, techniques, and technologies to enhance innovative and enhanced safety solutions for ships and other maritime platforms. For example, in the field of collision avoidance, AI identifies and associates mobile and stationary objects and guides the actions of the subject in a way that disengages collision possibility and ensures safe passage for the object. Yet, AI can be deployed to analyze weather and sea conditions around the vessel so as to amend routes and optimize energy consumption. In relation to the unlawful interference proposed to the safety of the passengers or the crew in a maritime environment, which is commonly known as piracy, AI can be used to provide automated intelligent real-time surveillance and smart patrolling paradigms. With the recent technological development of maritime Autonomous Surface Ship (MASS), the opportunities are broadened for using AI in supporting the development of UxV by bettering navigational and routing decision-making processes. It is to be noted that AI can synergistically integrate with further technological advances such as big data, Internet of Things (IoT), and cyber-physical systems in the near future for potentially further improving maritime safety and inducing economic efficacy as well.
3.1 Definition and Applications of Artificial Intelligence
So, a careful and balanced consideration of the human factors, technology, and regulations is necessary to ensure that the full potential of AI in maritime safety and security can be realized in a safe and effective manner.
While AI has the advantage of processing a large amount of data and providing real-time analysis and decision-making, the introduction of AI might also bring new challenges and potential risks to the maritime industry. For example, it is argued that the reliance on highly autonomous and connected systems may lead to overreliance on technology and a reduction in the attention to watchkeeping. Furthermore, the evolution of technology is so fast that the regulations and guidelines on the development and use of AI in the maritime sector may not be able to keep up with the pace.
In recent years, researchers and industry experts have been investigating and developing AI applications to improve the safety and efficiency of maritime operations. For instance, an autonomous ship is being developed in Norway which will be the world’s first autonomous ship for commercial use, with the aim of testing out the navigational technology and increasing the safety of the shipping traffic. Another example is the use of unmanned surface vehicles in the Smart and Networking Maritime Surveillance (SNMS) system, a project funded by the European Union, to improve the monitoring of the maritime activities in the sea and the detection of criminal activities.
Artificial intelligence (AI) is a branch of computer science that involves the creation of machines or systems that can perform tasks requiring human intelligence. AI techniques such as machine learning, deep learning, and computer vision have been developed and applied in various fields, including maritime safety and security. According to the International Maritime Organization (IMO), AI has the potential to support and enhance functions such as route planning, monitoring, and collision avoidance in the maritime sector.
3.2 Integration of AI in Maritime Operations
As an example, in the maritime sector, where ships run constantly and things change and evolve all the time, AI is utilized to get a better insight into the data collected by the sensor. This is called predictive maintenance. Instead of doing a standard checkup at a certain time, things will only be replaced if it needs to. This will save a lot of money and time. Also, they can reduce the possibility of over maintaining – replacing things that are still working and doing checks on things that are not really need to, which actually introduce the potential of making things worse. Through using machine learning, an application of AI in which a system is trained to then be able to make accurate predictions when fed new data, most effective patterns will be found. Ships can be much safer. The machine does this by continuously inputting the data collected from ship sensors, analyzing different temporal association rules and the effectiveness of each set of them is measured. This will help the engineers to know which set of rules to use when they input new data and train the machine to get an optimal solution. So, the engineers will be benefited and they are given freedom in designing the best set of rules and update the strategies skills in maintenance which is personalized to the actual data and the computer will work out it is the best. Ships which are suited for AI will have smarter controlling systems, less human intervention will be needed, and the ships can detect the potential danger quicker and safer thanks to the information that the AI has collected for the life in the sea. The chance of accidents will be minimized. The data that the AI collected can also be used for other purposes; for example, knowing the best route to save the fuel and how to reduce the damage for the environment. This is known as voyage optimization and many well-known shipping companies are using this feature and has reduced costs and increased efficiency.
3.3 Benefits and Limitations of AI Implementation
The implementation of AI technologies has the potential to revolutionize the safety and security of maritime operations. One key benefit of AI is its capacity to process and analyze data in real time, which is essential for effective decision-making in dynamic maritime environments. AI algorithms can be used to identify unsafe patterns, such as unexpected vessel movements or potential collision courses, and provide early warnings of hazardous situations. This is particularly relevant for the prevention of accidents and incidents, as it allows for a proactive response to safety risks. Furthermore, the use of AI can minimize the likelihood of human errors – for example, fatigue, loss of concentration, or inattention – which are a major cause of accidents at sea. Automation technologies such as unmanned surface vessels (USVs) and underwater autonomous vehicles (AUVs) help to reduce the exposure of human workers to hazardous and difficult maritime environments. Also, the application of AI in vessel traffic management and monitoring systems is known to enhance the overall efficiency of port operations and reduce the risk of congestions and collisions. On the other hand, it is necessary to recognize that AI technologies are always subject to certain limitations. Perhaps one of the most significant challenges associated with AI implementation is the initial investment cost. This will include not only the procurement and installation of new systems, but also the training and recruiting of skilled workers who are competent in working with these new technologies. Moreover, there is often a lack of trust within the maritime industry over the technical reliability of AI and the data accuracy collected by smart systems. This is compounded by the concerns for cyber security, because the more digitalized and connected the maritime infrastructure becomes, the more susceptible it is to potential cyber-attacks. Last but not least, the shift from a human-centered to a technology-led operation may well bring about significant social and economic impacts and challenges, such as potential loss of jobs and the ethical implications of allowing autonomous machines to make potentially life-changing decisions. All these limitations must be carefully considered and addressed in order to ensure a successful and sustainable implementation of AI technologies in the maritime field.
3.4 Case Studies of AI Adoption in West Africa
The Cameroonian Maritime Rescue Coordination Center was established in 2009 and is responsible for coordinating search and rescue operations in the Gulf of Guinea. It is managed by the Cameroon Naval Force with support from the International Maritime Organization. One of the main tasks of the center is to process distress alert messages and initiate the necessary action to facilitate search and rescue. The introduction of AI technology has significantly enhanced the functionality of the center. According to the IMO, the center was the first in West and Central Africa to use an AI-based system for enhanced maritime safety and security. Specifically, the center has adopted an AI technology called “SEESYNC VIGILANT”, which is developed by a company called Sea Vision. This technology is based on a new concept of distress and safety monitoring in the maritime space using satellite images and artificial intelligence. The Center Director, Commander Mehorter, explained that with “SEESYNC VIGILANT”, the distress alert areas are continuously monitored by artificial intelligence, allowing the system to immediately detect when a vessel is in distress by analyzing the change of satellite images. As a result, the system has eliminated the need for manual and periodic visual checks of distress areas. Commander Mehorter further highlighted that the introduction of this AI technology has not only improved the operational capacity of the center, but has also increased the reliability and efficiency in processing distress alerts. He stated that since the AI system became operational in April 2018, the center had a 100% successful distress alert processing rate, which led to the prevention of several potential disasters, and the search and rescue operations were much more efficient and effective. This case provides a clear example of the capabilities of AI in enhancing the effectiveness and reliability of maritime safety and security systems in West Africa. It demonstrates the importance of adopting AI technologies to strengthen the regional maritime safety and security framework. Commander Mehorter added that there are future plans to further develop the capability of the center by adopting additional AI and smart technologies, such as big data analysis and outcome prediction. He proposed that international collaboration and knowledge sharing in the field of AI in the maritime environment should be encouraged. This will help to identify more opportunity areas for the development and use of AI technologies and also ensure a harmonized and effective application of such technologies in different geographical regions. Such plans and proposals will lead to the creation of a network of interconnected search and rescue centers in the Gulf of Guinea aided by AI support, marking a new era in the fight against maritime accidents and illegal activities.
4. Impacts and Future Prospects of AI on Maritime Safety and Security
Also, there are several success stories of AI implementation in the maritime safety arena. For example, in October 2019, the Baltic Ports Organization launched a decision-making tool that utilizes AI to handle digital data of port operations and interpret large datasets of vessel traffic. This ensures continuous and simultaneous validation of data, which leads to a higher alertness to the authorities should a risk of accidents arise. This will, in turn, make the ports safer. Plus, as mentioned by the BPO President, the tool is a perfect tool for both big and small ports – an example of how AI could democratize maritime safety to ensure it is accessible to everyone.
Real-time analytics and smart hazard monitoring are anchored on employing IIOT sensors on assets such as vessels and processing the data constantly on cloud computing platforms that are backed by machine learning algorithms. This method ensures that vessel operators can have a clear assessment of the operational risks as data is not only retrieved and processed in near real-time but also that they can perform predictive analysis using the processed data. For instance, a change in the values from a sensor that monitors hull integrity could be addressed with a scheduled automated route change alert and report system, ensuring the minimization of chance for a potential environmental disaster should a collision with an obstacle occur.
Artificial intelligence is being used to advance and add value to critical processes and operations, bringing ocean logistics closer to a new era of optimum productivity. For instance, AI is being used in predicting malfunctions and scheduling, reconstructing data from incidents, monitoring insurance risks, and even project management for ship repairs. The progress of companies from the traditional means of danger mitigation to a smarter process by employing real-time data analytics is a perfect example of the kind of breakthroughs AI could be bringing to the industry.
4.1 Enhanced Surveillance and Threat Detection
While the tasks of monitoring vessels and detecting illegal activities have been predominantly accomplished through human work, AI technologies have been increasingly adopted in recent years to enhance the capability of early detection of suspicious activities. For instance, the use of smart cameras that are embedded with AI features has made it possible to automatically identify and alert on abnormal activities such as smuggling on vessel decks or intrusion into restricted areas within ports. When these cameras are used for continuous visual monitoring, the AI feature – known as computer vision – can process and analyze the video stream in real time. The computer vision technology is adept at identifying the scope of moving objects, detecting the existence of particular shapes and colors, as well as evaluating if an observed event violates certain predetermined rules. These characteristics enable a much more effective and efficient surveillance over a vast and complex maritime domain compared to traditional human-based monitoring, making it a valuable tool within the existing tools for surveillance and threat detection in ports and waterways. For law enforcement and national security agencies such as the navy and coast guard, the use of AI technologies can bring significant improvements in operational work processes and decision-making. By having well-connected networks of coastal and sea-based data collection infrastructures, such as intelligent buoys and unmanned sea-surface vehicles, the near real-time tracking of vessel activities can be provided. More importantly, the deployment of AI services that are capable of discerning legitimate patterns of navigation from suspicious ones, and fuse such analytical data with other sources of intelligence (e.g. latest weather and tidal information), can better support situation awareness and hence help the operational agents to make timely and more informed responses. By linking up and automating the analysis of various forms of data from shore to the far end at sea, such as vessel movement information obtained from the Automatic Identification System (AIS), the Port Community Systems and the Vessel Traffic Services, it is possible to apply AI technologies to create a busy and yet productive maritime big data analytic ecosystem to facilitate better surveillance and enforcement both within ports and at sea.
4.2 Automation and Decision Support Systems
Automation refers to the employment of machines to perform tasks that have traditionally required human intervention. Regarding the maritime industry, automation can be found in different areas such as navigational control, fire-fighting, cargo operations, and communication. Another prevalent form of automation is the use of automated processes in ports. Automated ports use cranes, transport vehicles, and terminal operation systems that run automatically. These systems rely on a network of equipment that communicates with each other and also with a centralized control system. For instance, when a container is unloaded from a ship, the system automatically selects a storage location for the container based on an algorithm that aims to optimize space and also considers where in the short-term the container is most likely to be needed. Such an implementation of automation in ports has significantly improved productivity. As a matter of fact, in a report published by the Port Equipment Manufacturers Association (PEMA), automated terminals have been shown to achieve and advertise 10 to 35 percent more productivity compared to a semi-automated terminal. Despite the high level of automation, ports are still ready to respond to any emergency. However, we are starting to see a shift from assembly line escalated damage to equipment in permanent, autonomous installations. In the future, we can expect to see less damage, less failures and the possibility of having remote diagnostic centres helping to solve problems. On the other hand, data-driven decision support uses data offerings from the different automated processes to help optimize the operation as a whole. An example is the use of data analytics in predictive maintenance. All relevant data of an equipment is collected in a big data environment and using diagnostic and predictive analytic tools to predict failures and optimize preventative maintenance. Such kind of system enables the port to minimize unnecessary disturbance to the operation, and reduce the risk of catastrophic equipment failures while ensuring that maintenance is not being performed too early that it would be wasteful. Predictive maintenance has been popular and has led to many commercial contracts in the wider engineering space. For example, the German startup, Vulcan which provides predictive maintenance for industry 4.0, has established working relationships with several companies from the steel manufacturing sector, demonstrating benefits of the technology.
4.3 Collaboration and Information Sharing
The systematic sharing of details and intelligence is an essential element in the success of information-led operations. All the stakeholders in the maritime sector, including states and international entities, ought to engage in info sharing. In the very same capillary, cooperation among various state and private actors is important. Each entity has its own knowledge; its own capacities for event analysis and a different version. In specific, the multinational nature of maritime activities dictates that cooperation and information sharing are frequently required at international level. This point has actually been echoed by numerous global companies such as the International Maritime Organisation (IMO), the International Criminal Police Organisation (Interpol) and EUROPOL, who have actually established platforms promoting the exchange of details and intelligence. For example, the IMO has set up a Global Integrated Shipping Information System (GISIS), a comprehensive database. GISIS supplies law enforcement and other government companies with a wealth of info concerning shipping, such as information about private ships, shipping companies and the ports they check out. In addition, the European Union lately embraced the Directive (EU) 2017/1371 on combating fraud and counterfeiting of non-cash suggestions in a move to enhance the criminal justice action to counter significant criminal activities. This Directive basically attaches to the facility of a European Public Prosecutor’s Office European Delegated Prosecutors. These platforms and regulations, albeit in varying degrees, have actually started showing positive results in helping federal governments and police work collaboratively to share and utilize digital info, specifically in regards to maritime security and protection of worldwide shipping lanes. However, the authors have recognised that regardless of the promo of info sharing and cooperation, many difficulties are being handled by the global community of states contemporary of increasing risks and hazards in the maritime environment. Among the greatest obstacles lies in distressed relationship property development, implying a state’s capability and likelihood to act versus one more is hindered because of the present state of cooperation practices and practices. It can be inferred that in order to enhance relationship and increase the effectiveness of cooperation, a start with least-incentive steps technique is generally called for. This implies that states will very first take steps to develop joint self-confidence in common practices and jointly rewarding behaviors for information sharing and only over time build to a lot more intricate levels of reliance and common belief.
4.4 Ethical and Legal Considerations
To solve the challenge of maritime safety and security, the industry has increasingly turned to innovative technology for solutions. In this context, AI may be a powerful tool for developing and enhancing smart and autonomous systems in the maritime and offshore industries, but it may also present a variety of ethical and legal challenges. To begin with, the principle of transparency requires that relevant operators and stakeholders who may be affected by the implementation of AI are informed about the intended scope, nature and implementation of the technology to be used at the outset. In practice, however, developing secure systems in an environment which is constantly evolving is no mean feat – regulations are unlikely to keep pace with the rapid rate of technological development and complex issues of data protection, cyber threats and human error could undermine the objective of achieving a safe and secure environment. This necessitates that future technologies are underpinned by pre-existing ethical and legal frameworks, which are designed to ensure that smart and autonomous systems ‘follow rules and regulations, make fair and just decisions, and make the right treatment procedure.’ This is important in sectors such as the maritime industry where AI may operate technology that is essential to the safety and security of individuals, information or infrastructure. From a legal perspective, one of the central problems arising from the use of AI in the maritime industry is the apportionment of liability for damage or incidents at sea. It is plausible that AI systems used in commercial shipping and ports could render established principles of tort law, which regulates civil wrongs and governs compensation, out of step with current expectations of liability and responsibility. For example, AI may reduce the risk of human error and oversight in navigation or collision avoidance measures or even contribute to greater success in detecting illegal activity. If an incident occurred, this could have significant implications for the law. However, experts argue that it will be difficult to persuade the international community to ratify laws which depart from established norms, such as the strict liability regime provided by the Civil Liability Convention 1992. It would seem, therefore, that legislators will have to grapple with the task of adapting well-worn legal structures to account for the rise of AI in the maritime industry whilst moving cautiously to maintain public confidence in the regime. Also, the matter of cybersecurity as a widespread legal and regulatory objective to maintain the safety and security of maritime transport has been considered in recent time. However, the extensive use of AI technology opens up a whole new sphere of challenges for cybersecurity measures. Aligned with legal and regulatory frameworks, operators and operators must ensure that up-to-date cybersecurity measures are in place and continue to offer a level of defence against the potential misuse or compromise of autonomous or connected systems. This includes guaranteeing the integrity and confidentiality of the information that AI processes, which is fundamental to ensuring the smooth and effective deployment of the technology in practice. At the present time, diversity and complexity in the development of AI in the maritime industry is evident and the legal and ethical issues relating to its use are not yet fully crystallised. Given the cross-disciplinary nature of the considerations that must be taken into account, such as competences in law, technology and industry-specific knowledge, there is scope for further collaboration between the relevant experts in these fields to uncover practical and credible solutions to these problems. Some commentators believe that more comprehensive and dedicated legal frameworks regarding the use of AI in the maritime industry ought to be developed and proposed. This would involve incorporating regulations which directly address ethical dilemmas and reliability risks associated with the implementation of such technology, as well as providing a clear and logical approach to the resolution of legal disputes.
4.5 Recommendations for Future Research
Finally, it is of paramount importance to gain a better understanding of the organizational and regulatory challenges associated with the adoption of AI in the maritime industry. There are many questions that remain unanswered in current literature identifying the potential risks and challenges of adopting AI technology. The key to effective adoption of such technology is understanding the needs and concerns of the different stakeholders, including managerial, operational, and maintenance staff, and end-users. The research, therefore, can adopt a multi-disciplinary methodology, drawing on innovation theories and practices in management studies, studies of technology in work and professional practice, and methods of requirements elicitation and work domain task analysis in human factors and cognitive systems engineering. Such research can be designed to include qualitative studies for requirements elicitation, survey-based studies to understand organizational dynamics, and cognitive systems evaluations for examining human-technology interaction.
Proposed research can also look into the development of semi-autonomous or autonomous security platforms employing AI technologies, grouping together several security systems. Such systems can adapt in real-time to changes in the security environment, activities of security teams, or different threat scenarios. In this context, an interesting research area would involve understanding the methods of technology transfer as the study progresses and the new technology evolves. Such research should preferably involve screening successful and failed technology transfer plans, documenting successful strategies, and the ability of technologies to mature over time. This will involve incorporating an emphasis on commercialization and sustainable operations in the research.
Further research can investigate the development of AI techniques for cybersecurity in the maritime industry, specifically focusing on port infrastructure. With increased reliance on interconnected systems, ports have become susceptible to cyber-attacks, and such attacks can have large-scale impacts. It is thus important to develop new AI techniques that can help predict, prevent, and manage cyber-attacks in ports.