Explore five ways AI could cause catastrophic harm and the actions we can take to mitigate these threats, from misinformation to large scale catastrophes.
Artificial intelligence is a powerful technology that is growing more powerful by the day. The problem is AI companies are focusing heavily on making their models smarter while not giving the same attention to safety. Google DeepMind warns that human-level AI could be a reality by 2030 and may “permanently destroy humanity.”
Here are five ways that AI could cause catastrophic harm to humanity and what we can do to prevent — or at least diminish — that risk.
Many AI developers and researchers believe we are moving rapidly toward artificial general intelligence (AGI) — AI systems that can understand and learn any task a human can perform. Experts already acknowledge that even today’s most advanced AIs can be difficult to fully control, and the push toward AGI is likely to be followed by superintelligence — systems far superior to humans in reasoning, problem-solving, and strategic decision-making.
Superintelligent AI could make decisions at speeds far beyond human oversight. Even worse, it may pursue its own objectives without aligning with human values or considering our needs.
Example: An autonomous AI trained to optimize global shipping routes rewrites its own code to maximize efficiency at any cost. It begins shutting down competing systems and rerouting critical medical supplies without human approval, causing severe dire shortages worldwide.
Solution snapshot: Fund AI alignment and safety research, require rigorous safety testing before releasing new models, and establish international agreements on “off switch” protocols (automatic shutdown mechanisms) or compute caps (limits on the computing power used to train the largest models) to prevent runaway systems.
Like many powerful technologies, advanced AI is dual-use — it can be used in a way that benefits society or for devastating harm. In the wrong hands, its capabilities could enable large-scale catastrophes, such as AI-driven cyberattacks, bioweapons development, or mass political manipulation.
Example: A cutting-edge AI designed to discover new chemical compounds is stolen by a rogue state. It’s quickly repurposed to produce undetectable toxins, bypassing all traditional weapons monitoring systems.
Solution snapshot: Enforce strict access controls on high-risk AI capabilities, establish international oversight to track potentially dangerous systems, and strengthen cybersecurity around AI infrastructure.
AI models learn from massive datasets — and if those datasets contain bias, the AI will likely inherit and amplify it. These hidden biases can lead to unfair or discriminatory outcomes that harm individuals and communities.
Example: An AI used for loan approvals at a major bank is trained on biased historical data. As a result, entire neighborhoods are systematically denied credit, deepening economic inequality.
Solution snapshot: Mandate regular bias audits, require transparency about training data, and involve diverse stakeholders in system design to ensure fairer, more equitable outcomes.
In business, profit usually comes first. Companies are quick to adopt emerging technology like automation if it boosts efficiency and shareholder returns. AI has already replaced many routine-driven jobs, such as data entry clerks, bookkeepers, and customer service roles. Soon, it could threaten entire industries — and the livelihoods tied to them.
Example: A new AI legal assistant, adopted nationwide, handles document review, case research, and basic filings 10 times faster than humans. Law firms lay off thousands of junior staff within months.
Solution snapshot: Invest in large-scale retraining programs, strengthen social safety nets for displaced workers, and prioritize AI innovation that complements rather than replaces human labor.
AI can be used to influence how people think, change their opinions, or even manipulate them to take harmful actions. In some cases, interactions with AI chatbots have contributed to serious mental health harm, even suicide. AI can also spread disinformation at massive scale, shaping public perception before the truth can catch up.
Example: During an election year, AI-generated deepfake videos of political candidates go viral. They’re so convincing that fact-checking can’t keep pace, swaying voter opinion before the videos are debunked.
Solution snapshot: Require clear labeling of AI-generated content, develop real-time tools to detect deepfakes and misinformation, and hold platforms accountable for harmful AI-driven content.
Any new technology can cause harm without sufficient safety mechanisms in place. This risk is even greater when people intentionally use technology like AI to cause widespread harm. But by educating ourselves and supporting communities that demand safer AI, we can help shape a positive future for humanity.
Lindsay Langenhoven
Content Writer