Rapid advancements in artificial intelligence have sparked concerns about its potential to replace human intelligence in various aspects of our lives and the economy. As AI-driven technologies continue to evolve, the incorporation of AI in drones has become a significant point of interest.
While the benefits of AI-driven drones are evident in enhancing productivity and performance, iTOO Special Risks, a specialty risk insurer, acknowledges the emergence of new, insurable risks that demand attention. According to Greg Dillon, lead for events and drones at iTOO Special Risks, the growing interest in AI technology in drones is driven primarily by the desire to enhance operational efficiency and enable autonomous functions within predefined parameters.
“As drones become more ‘self-aware’, the potential applications of this technology expand, particularly in sectors such as agriculture,” explains Dillon. “However, with the rise of autonomous drones, there are also new risks that must be considered and addressed through comprehensive insurance coverage.
“Looking at the main types of AI, reactive machines are AI systems with no memory and are task-specific, meaning they always produce the same output for a given input. Moving forward, we encounter the more evolved machines with limited memory, representing the next stage in AI’s evolution. With this progression, we anticipate a growing necessity for insurers to comprehend these advancements and steer the market accordingly. The ultimate goal is to develop AI drones that possess self-awareness, which is where things get intriguing,” Dillon says.
The Commercial Drones Operators Policy available in the market covers the drone itself as an asset as well as potential liability arising from incidents involving third parties. However, the inclusion of AI and AI-enabled devices in the equation necessitates a fresh perspective to anticipate the impact of emerging risks. Dillon envisions a future where AI-empowered drones play a vital role in diverse fields, including disaster response, agricultural monitoring, and complex data analysis in commercial and industrial sectors.
“For example, an AI-enabled drone capable of inspecting accident sites before initiating rescue operations takes on the role of an individual and should be insured accordingly, as it, too, faces inherent risks,” he says.
Given these developments, both insured parties and the specialist insurance industry must proactively assess and manage potential emerging risks through well-designed policy instruments.
Dillon emphasises that AI advancements are occurring at a remarkable pace, and it is imperative for the entire value chain, including clients, brokers and underwriting teams, to stay abreast of proper risk assessment and pricing methodologies to keep pace with this rapidly expanding market.
Governments are also recognising the various applications of AI-driven drones, especially in enhancing citizen safety. Dillon cites an example of the premier of Gauteng, who expressed interest in using hundreds of drones for crime-fighting efforts. “While these applications represent valuable advancements, the integration of AI in drones introduces certain risks that demand meticulous management and mitigation,” warns Dillon.
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AI has the potential to revolutionise route planning and optimisation in the context of drone technology. Drones integrated with AI algorithms can process and analyse extensive datasets, including weather conditions, traffic patterns and package weight, to identify the most efficient delivery routes. This pivotal role of AI will help in risk mitigation and in ensuring secure operations. Equipped with advanced computer vision and sensor technologies, AI-powered drones can detect and avoid obstacles along their flight paths, such as buildings, trees or other aircraft. These remarkable capabilities significantly reduce the risk of accidents and collisions, ensuring a safer environment for drone operators and the public.
For example, drone delivery companies in the US and elsewhere are already empowered by AI to make data-driven decisions and continuously optimise their operations. By collecting and analysing extensive data, including delivery times, customer preferences and traffic patterns, AI algorithms can identify areas for improvement and optimise various aspects of the delivery process. This data-driven approach ensures more efficient and streamlined operations, enhancing the overall effectiveness of drone deliveries.
In conclusion, Dillon highlights the importance of being proactive in addressing emerging risks associated with AI-driven drones. By collaborating with the relevant regulatory bodies, industry stakeholders, governments and technology experts, the insurance industry can develop comprehensive and future-proof policies that will enable society to harness the full potential of this transformative technology while safeguarding against its inherent risks.
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