AI chatbots such as ChatGPT carry risks for users because some of their replies can be flawed, including what many call hallucinations. Prabhakar Raghavan, the senior vice president and head of search at Google, spoke about this in an interview with the German outlet Welt am Sonntag. The message was clear: these systems can produce responses that sound convincing but are not based on real facts. The way the technology is built makes it possible for these mistakes to slip through, especially when interpreting complex or ambiguous prompts.
The expert emphasized that developers face a challenging task: to minimize the frequency of such misfires. The large language models behind these tools are so capable that it is hard to predict every possible behavior. Still, the goal is to test the technology at a scale that reveals patterns of error and then fine tune the models to improve accuracy over time. In practical terms, this means iterative testing, data curation, and careful tuning of how the system handles uncertain information.
A Google executive urged users to stay vigilant when evaluating results produced by AI chatbots. Trust is earned only when information is reliable and verifiable. The goal is to lead in the industry through responsible information practices and transparent handling of uncertainties. That approach, the company argues, is essential to maintaining public confidence as these tools become more widespread in everyday tasks.
The discussion comes as Microsoft has invested heavily in OpenAI, the maker of ChatGPT. The investment signals a shift that has captured market attention: a powerful mix of search capabilities, natural language dialogue, and the ability to generate text or summarize information on request. This combination influences how people search for and consume information, pushing competitors to rethink their own offerings while aiming to preserve user trust and safety as they scale up usage.
Industry observers note that China’s major technology firms, including the owner of Alibaba’s AliExpress, are exploring the development of domestic equivalents to ChatGPT. Such efforts reflect a broader push by global tech players to build multilingual, locally tuned AI systems designed for large-scale commercial use. The strategic race to create reliable, high-performing chatbots is shaping how search, e-commerce, and customer service platforms will operate in the coming years.
As AI assistants become more common across devices and services, experts stress practical steps for users. Cross-checking information with multiple sources, confirming critical details with verifiable data, and recognizing the limits of machine reasoning are all prudent habits. Companies are likewise doubling down on safety audits, model governance, and user education so people know what to expect from these technologies. The bottom line is simple: AI can assist with tasks, but human judgment remains essential for high-stakes decisions, especially in areas like health, law, and finance. With vigilant use and continuous improvement, the promise of AI chatbots can be realized without compromising trust.