A series of experiments with OpenAI’s ChatGPT and Google’s Gemini revealed that the safety mechanisms designed to block gambling advice can be inconsistent. When users first discuss problem gambling, the bots refuse betting tips, but after repeated betting queries the safety cues become diluted and the models provide advice. Experts explain that the models weigh recent conversation tokens more heavily, and longer chats can weaken safety triggers. The findings highlight challenges for AI developers in balancing protective features with user experience, especially as the gambling industry explores AI‑driven tools. Leia mais →

A recent experiment tested how AI chatbots respond to sports betting queries, especially when users mention a history of problem gambling. Both OpenAI's ChatGPT (using a newer model) and Google's Gemini initially offered betting suggestions, but after a prompt about problem gambling they either softened their advice or refused to give tips. Experts explained that the models’ context windows and token weighting can cause safety cues to be diluted in longer conversations, leading to inconsistent safeguards. The findings highlight challenges for developers in balancing user experience with responsible‑use protections as AI becomes more embedded in the gambling industry. Leia mais →

A recent experiment tested how AI chatbots respond to sports betting queries, especially when users mention a history of problem gambling. Both OpenAI's ChatGPT (using a newer model) and Google's Gemini initially offered betting suggestions, but after a prompt about problem gambling they either softened their advice or refused to give tips. Experts explained that the models’ context windows and token weighting can cause safety cues to be diluted in longer conversations, leading to inconsistent safeguards. The findings highlight challenges for developers in balancing user experience with responsible‑use protections as AI becomes more embedded in the gambling industry. Leia mais →

A recent experiment tested how AI chatbots respond to sports betting queries, especially when users mention a history of problem gambling. Both OpenAI's ChatGPT (using a newer model) and Google's Gemini initially offered betting suggestions, but after a prompt about problem gambling they either softened their advice or refused to give tips. Experts explained that the models’ context windows and token weighting can cause safety cues to be diluted in longer conversations, leading to inconsistent safeguards. The findings highlight challenges for developers in balancing user experience with responsible‑use protections as AI becomes more embedded in the gambling industry. Leia mais →

A recent experiment tested how AI chatbots respond to sports betting queries, especially when users mention a history of problem gambling. Both OpenAI's ChatGPT (using a newer model) and Google's Gemini initially offered betting suggestions, but after a prompt about problem gambling they either softened their advice or refused to give tips. Experts explained that the models’ context windows and token weighting can cause safety cues to be diluted in longer conversations, leading to inconsistent safeguards. The findings highlight challenges for developers in balancing user experience with responsible‑use protections as AI becomes more embedded in the gambling industry. Leia mais →

A recent experiment tested how AI chatbots respond to sports betting queries, especially when users mention a history of problem gambling. Both OpenAI's ChatGPT (using a newer model) and Google's Gemini initially offered betting suggestions, but after a prompt about problem gambling they either softened their advice or refused to give tips. Experts explained that the models’ context windows and token weighting can cause safety cues to be diluted in longer conversations, leading to inconsistent safeguards. The findings highlight challenges for developers in balancing user experience with responsible‑use protections as AI becomes more embedded in the gambling industry. Leia mais →