AI has rapidly evolved and is reshaping how societies, governments, and institutions function. Early AI systems relied on rigid rule-based logic that could only follow instructions written by humans.
Today’s generative models are more flexible, learning from broad datasets, producing novel outputs, and adapting to real-world patterns. This has transformed AI from a predictable automation tool into a central actor capable of creativity and decision-making, creating both opportunities and risks for civic institutions.
As AI continues to evolve, its role in cybersecurity becomes increasingly complex. It comes with clear pros and cons, shaped by how it is used and who is using it. Understanding both sides of this reality is essential because it helps us navigate the negative impacts we are already seeing and guides us towards the improvements that will strengthen our systems in the future.
The Evolution of Artificial Intelligence (AI)
In the 1950s, AI was far less advanced. Researchers built simple programs that manipulated symbols using fixed rules. One example, widely considered as the first true AI program, was built between 1955 and 1956 and could prove mathematical theorems by following coded logical steps.
As the decades passed, ambition and methods evolved. In the 1970s and 1980s, researchers focused heavily on expert systems, but these systems were brittle and performed poorly outside their coded rules. By the 1990s, advances in computing power and the growth of digital data influenced a shift toward machine learning.
In the 2000s and beyond, advances in neural networks and deep learning opened new possibilities, allowing AI to recognise patterns, interpret language, and eventually generate entirely new content.
Today, AI systems draw on massive datasets, statistical learning, and complex algorithms to produce text, images, and insights that directly influence how societies function.
Artificial Intelligence (AI) and Cybersecurity
The line between innovation and insecurity gets thinner by the day as technologies continue to evolve. With so much work now happening online, the systems that keep organisations safe are increasingly shaped by artificial intelligence.
Threat Detection
On the bright side, modern security tools can scan vast streams of data, detect unusual patterns, and alert teams to threats before they escalate. This kind of support is especially valuable for advocacy groups with limited technical resources. Yet there is another side to it.
Security Attacks
In the same vein, the intelligence that strengthens defences can also be used to break through them. Cybercriminals now rely on AI to generate convincing phishing attempts, create deepfakes, develop malware that learns from each failed attack, and slip past detection systems that once seemed dependable.
What emerges is a complicated reality where AI improves protection but also enables more advanced threats. In civic space, this makes awareness and readiness essential, as the very tools that empower their work can also expose them to new vulnerabilities.
Artificial Intelligence (AI) and Civil Society
Within the civil society space, artificial intelligence has become both a helpful companion and a growing source of concern.
Pros
Data Processing
On the positive side, many organisations now use AI to process large volumes of research data, enabling faster, more informed decision-making.
Communication
AI-powered chatbots and automated systems also help advocacy groups engage citizens in real time, answering questions and sharing essential updates far more efficiently than traditional, slower online communication channels. Yet these benefits sit alongside challenges that are becoming increasingly difficult to ignore.
Cons
Inaccurate Information
AI tools can generate inaccurate or misleading information, posing a serious risk to organisations whose work relies on credibility and evidence.
The reason for this gap in results is that AI models are trained on vast amounts of data from across the internet, which can include both accurate and biased information, making it challenging for AI to consistently produce correct, unbiased outputs.
Additionally, AI models often predict the next data point based on patterns, yielding results that are closely related but not entirely accurate.
Bias
AI models, like humans, are products of their environments, so bias may naturally exist depending on how these intelligence systems were programmed.
If the initial Racial, gender or age biases embedded in some AI models can also lead to certain groups being misrepresented or excluded altogether, which clashes with the values of fairness and inclusion that civil society stands for. Beyond this, the extensive access AI systems have to sensitive organisational data exposes NGOs and community groups to higher cybersecurity risks.
Misrepresentation
As deepfakes and AI-generated misinformation spread, defending the truth becomes harder. While AI offers real value, its vulnerabilities are increasingly prominent, forcing civil society to address challenges it did not create yet must now learn to manage.
As the digital world continues to evolve, artificial intelligence will remain a defining force in how civil society operates, protects itself, and engages with communities.
Final Thoughts
Artificial Intelligence is not the enemy. As seen above, it is one of the key drivers in advancing cybersecurity and supporting civil organisations.
Ultimately, the goal is to understand these tools and use them with intention. If issues such as inaccurate information, pre-existing bias, and the use of AI tools to spread propaganda can be addressed through solutions like fact-checking, model retraining, legal frameworks penalizing deepfake creation, and tracking systems to identify perpetrators, then civil society may be able to harness AI’s benefits with minimal risk. This approach can help mitigate risks and ensure that technology supports, rather than undermines, its mission.