AI has globally seen a significant level of hype, growth, and investment with many businesses and employees utilising it to support their day-to-day operations. Within the telecoms sector, we see mobile operators such as Ericsson, Huawei, and Nokia utilising AI to optimise network performance, automate operations, and accelerate innovation. However, amid the hype and implementation, it’s important to take a step back and acknowledge the potential downsides of AI in 5G:
AI’s ability to process vast amounts of data at lightning speed raises significant privacy concerns. With 5G’s enhanced connectivity, there’s an exponential increase in the volume of data transmitted across networks. This data encompasses personal information, behavioural patterns, and sensitive business data. The integration of AI algorithms in processing this data heightens the risk of privacy invasion and unauthorized access. From surveillance technologies to targeted advertising, the convergence of AI and 5G amplifies the potential for data breaches and misuse, undermining individual privacy rights and data security.
The symbiosis of AI and 5G has the potential to streamline the industry in many aspects for mobile operators. However, this digital transformation may come at a cost for employees. AI’s automation capabilities could potentially pose a threat to traditional job roles, leading to widespread role reductions across the sector. Employees may struggle to adapt to the changing skill requirements leaving them potentially jobless. Just as the Luddites in the 19th century were against the utilisation of cost-saving machinery, workers in the modern era may express concerns about the utilisation of AI-driven mobile networks, fearing that they will be replaced by them.
Studies have shown that results generated by AI do not just reproduce biases in data, they can amplify them. This can create unjustifiable difference in model accuracy between geographically dispersed regions. For example, if a model is trained on data primarily from one region regarding network optimisation, it may perform less accurately when utilised in other regions resulting in a poor experience for users. On the topic of regions, we also need to consider how AI is regulated globally. Operators may find themselves caught between different jurisdictions and, in some cases, there may be regulations that are contradictory resulting in an increased level of complexity by implementing AI.
Many discussions exist about how AI can be utilised to better understand and implement security features within 5G, but discussions are limited surrounding how AI can be applied by malicious actors to orchestrate sophisticated cyber-attacks. From a knowledge perspective, AI lowers the bar, allowing less skilled adversaries to carry out cyber-attacks. It can provide malicious actors with a range of AI-generated features such as: malicious payloads, customised phishing emails, and vulnerability identification techniques. The convergence of AI and 5G amplifies the complexity and scale of cybersecurity threats.
In conclusion, the integration of AI and 5G holds massive potential for innovation and progress however, it’s important to be aware of the negative impacts it presents. From privacy concerns to job reductions and cyber vulnerabilities, the convergence of AI and 5G is a double-edged sword. To explore how security is being addressed within 5G networks, including AI-driven threat vectors, take a look at our 5G Security course.