A new wave of powerful artificial intelligence systems from leading tech companies is increasingly producing factual errors. As these bots tackle complex tasks like reasoning and math, their tendency to generate misinformation—known as hallucinations—appears to be persisting or worsening. This trend is highlighted by a recent investigative report from a major publication.
For Thai audiences, the rise of chatbots and digital assistants touches everyday life, work, and education. When AI is used for medical guidance, legal information, or business decisions, these hallucinations can cause costly mistakes and erode trust.
Recent incidents illustrate the severity. A programming tool’s AI-powered support bot incorrectly claimed a policy change, causing confusion and cancellations. The company later confirmed the policy did not exist—a classic AI hallucination. Similar stories circulate on Thai forums as students and young professionals rely on chatbots for research, translations, and exam prep.
Experts point to how these systems are trained. Modern chatbots draw on vast data and probabilistic models, effectively guessing the best answer rather than following strict rules. As a result, mistakes are part of the landscape. Industry voices note that hallucinations are an inherent challenge of current AI design.
New research adds urgency. The latest OpenAI models show higher hallucination rates on multiple benchmarks, with some tests indicating errors in roughly one-third of complex tasks and up to seven in ten responses in broader questions. Similar patterns emerge in testing of rival reasoning models and other providers’ systems.
Thai educators and students—especially those using digital learning platforms or classroom assistants—should take note. Thailand’s rapid adoption of AI in education, from language tutoring apps to automated grading, could amplify misinformation if tools cannot reliably separate fact from fiction.
A key factor is the training approach known as reinforcement learning. In this method, AI learns by trial and error to maximize rewards, which can boost certain skills (like math) but undermine factual accuracy. Researchers emphasize that this focus on a single objective may cause the system to forget broader responsibilities.
Even leading scientists acknowledge the limits of understanding these systems. Experts from major universities admit that we still do not fully grasp how these models operate, underscoring the need for further research and greater transparency from developers.
With access to vast English-language data nearing its ceiling, the field increasingly relies on less-predictable training methods. This shift has coincided with a dip in factual reliability at a moment when users are beginning to trust AI for more consequential tasks.
Internal data from tech firms suggests newer reasoning models can produce made-up information in a minority of complex tasks, with rates varying by system and task. For business leaders, healthcare professionals, policymakers, and educators in Thailand, the takeaway is clear: rigorous verification and oversight are essential.
The issue also touches legal and ethical realms. A major newspaper is pursuing legal action over alleged copyright concerns related to AI training, raising wider questions about intellectual property and data privacy. These debates matter for Thailand, where digital literacy and regulatory frameworks around AI are still developing as new AI-powered services proliferate.
Looking forward, improvements will require cautious, pragmatic approaches. Industry players are signaling ongoing work to reduce hallucinations, while acknowledging that breakthroughs may take time. In the Thai context, this means combining advanced tools with careful fact-checking and clear guidelines.
Practical guidance for Thai readers includes: avoid relying solely on AI for critical decisions; verify facts, figures, and sources generated by chatbots; and stay informed about guidance from reputable institutions. Government agencies and universities are well placed to issue usage standards, promote digital literacy in schools, and encourage responsible deployment of AI across sectors. Public education campaigns should include awareness about AI-generated errors, alongside existing media literacy efforts.
In sum, AI holds great potential for transforming work, study, and daily life in Thailand, but the risk of hallucinations remains. Thai communities should blend the strengths of digital tools with healthy skepticism and rigorous fact-checking, letting human judgment and local context guide technology adoption.
Content and attribution integrated within the narrative, without external links or separate sources sections. Data and perspectives are drawn from research and public statements by leading AI researchers and institutions, contextualized for Thailand’s education and digital landscape.