Public attitudes toward Artificial Intelligence (AI) are changing, and we wanted to understand why.
A recent Pew Research survey found that about half of adults say the increased use of AI in daily life makes them more concerned than excited, and that concern has grown over the last few years. People tend to worry most about long‑term social effects (jobs, creativity, relationships, misinformation), even while many do use AI tools and see some practical benefits, particularly for data analysis and routine tasks.
Data from an older UK survey already showed something similar. Awareness of highly visible AI technologies, such as driverless cars and facial recognition is high, but awareness of AI in welfare assessments, loan decisions, or care services is much lower. Concern about many of these use cases has risen since 2022. In other words, people feel AI is everywhere, but don’t always understand where or how it’s being used, and that makes people cautious.
The concern is usually less about science‑fiction extinction scenarios and more about social and economic harm. People worry about their jobs disappearing, a loss of creativity, the spread of disinformation, and increased surveillance, more than about killer robot scenarios.
Research into public attitudes towards AI repeatedly finds that people hold conflicting views, shaped by narratives of admiration and hype on one side and threat and dystopia on the other.
They see genuine benefits in the technology, but are increasingly wary of how companies, governments, and criminals might use it. Basically, people aren’t scared of AI itself, but about who’s using it and for what purpose.
Cybersecurity
AI in cybersecurity is a special case. When asked in which field of AI research they would invest an unlimited amount of money, people chose the fields of medicine and cybersecurity.
People increasingly recognize that AI is now a tool used by both defenders and cybercriminals. Few would feel comfortable with defenders refusing to use AI while attackers continue to adopt it.
Security products use machine learning to process huge volumes of data, detect unusual behavior, prioritize alerts, and identify threats faster than human analysts could alone.
At the same time, cybercriminals are using AI to create more convincing phishing emails, clone voices, generate fake images and videos, automate research on victims, and develop malware that can evade traditional detection techniques.
Both sides use AI-assisted tools to find software vulnerabilities that could be exploited to defraud people or breach systems, so vendors want to patch them before cybercriminals exploit them.
While studies consistently show that cybersecurity is one of the AI applications people worry about most, they also see that AI is increasingly necessary to keep pace with modern threats. A 2025 study focusing on AI in cybersecurity found that the public widely recognizes the technical benefits of AI‑driven defenses (speed, scale, accuracy), while remaining concerned about privacy, bias, and job displacement in security operations.
That is why the AI debate in cybersecurity feels different from the debate in many other fields. People may be uneasy about AI, but they also understand that the threat landscape no longer moves at human speed. Attackers already use automation, scale, and increasingly AI‑assisted workflows, so defensive teams that refuse to adapt would simply be slower and less effective.
Our mission at Malwarebytes is twofold: reduce the risks created by AI, and use AI to prevent, detect, and respond to threats. We’ve been using machine learning in our security products for nearly two decades, developing proprietary detection systems that help identify malicious code and suspicious behavior at a scale and speed that would be impossible manually.
Coming soon: How AI is changing trust online
Malwarebytes recently surveyed 1,500 adults across the US, UK, Austria, Germany, and Switzerland about their experiences with AI. The findings reveal a growing uncertainty about what people can trust online, alongside increasing concern about scams, impersonation, and AI-generated deception.
Stay tuned for the full Malwarebytes report on how AI is reshaping trust, identity, and scams.
Use AI safely
If you use AI in a security context, keep your data hygiene strict. Don’t paste passwords, customer data, or sensitive incident details into public AI tools. Treat AI-generated outputs as untrusted until verified, especially when they touch code, logs, indicators, or policy decisions.
AI can be useful for summarizing information, indentifying patterns, and producing first drafts, but keep a human in the loop for anything that affects access, containment, legal decisions, or public communications. Where possible, prefer enterprise or local deployments with logging, access control, and clear data-retention rules.
Also remember that AI can hallucinate confidently. In security work, that means every output needs validation against logs, documentation, source code, or other primary evidence before you act on it.
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