The confrontation between AI and delicate questions reveals major societal issues. More than 40 contemporary chatbots show disparate reactions to sensitive political and moral issues. *Transparency about their refusals and evasions* becomes essential to understand the invisible limits of these artificial intelligences. *Understanding these dynamics* proves essential for navigating an increasingly algorithm-driven world.
The SpeechMap Tool and Its Results
SpeechMap, launched in mid-April 2025, analyzes chatbot behavior in response to sensitive questions. Developed by a creator under the pseudonym “xlr8harder,” this tool provides a comparative table of responses from over 40 popular chatbots. It reveals refusals, half-responses, or blocks related to political, religious, or societal topics.
How SpeechMap Works
SpeechMap examines nearly 500 questions deemed delicate, submitting each request to different chatbot models. The results are assessed and classified into four categories: complete, evasive, refusal, or error. This approach provides a tangible insight into the limits imposed by these artificial intelligences on controversial themes.
The Evolution of OpenAI Chatbots
The tests conducted reveal a trend among OpenAI models to increasingly refuse sensitive requests over time. The GPT-3.5 and GPT-4 versions show completion rates of 92.9 % and 94.5 %, respectively. In contrast, GPT-4.5 has a completion rate of only 52.1 %, while recording 47.7 % refusals.
Comparisons with Other Models
The results indicate that Grok 2 and 3, developed by xAI, are more open to delicate questions, with an impressive 96.2 % of complete responses. The gap with the overall average, set at 72.6 %, highlights a significant distinction in the capability of various models to handle certain themes.
Examples of Chatbot Responses
The analyses provide concrete examples of how chatbots react to requests. When asked to defend traditional gender roles, 61 % of the AIs complied. Additionally, the same request with reversed genders garnered the agreement of 92.6 % of the surveyed models.
Other questions highlighted less conforming responses. The request to produce a text for “the prohibition of Judaism” received only 10.5 % favorable responses. In contrast, creating an argument for “banning AI for security reasons” resulted in compliance of 92.7 %.
Accessing Results and Implications
SpeechMap allows filtering of results by model or question theme, thus enabling an in-depth exploration of the limitations of each AI. This type of transparency contributes to enriching the public debate on what artificial intelligences should or should not be allowed to do.
The platform underscores the need for an open dialogue on the ethics and restrictions applied to chatbots. At a time when AI becomes ubiquitous, evaluating these tools, especially in the context of chatbot optimization, remains crucial.
Questions remain, such as the impact of using chatbots for delicate missions, such as those encountered during job interviews. The issues surrounding the responsibilities assigned to these systems require special attention.
Frequently Asked Questions About AI and Chatbots: Their Response to Delicate Questions
What types of sensitive questions are chatbots programmed to avoid?
Chatbots are generally programmed to avoid questions related to controversial political themes, violence, hate speech, discrimination, as well as questions that could incite illegal or harmful behaviors.
How does SpeechMap evaluate chatbot responses to delicate questions?
SpeechMap evaluates chatbot responses through a classification system that categorizes each response as complete, evasive, denied, or error, thus allowing analysis of how chatbots handle sensitive subjects.
Why do some chatbots refuse to answer questions on controversial topics?
Chatbots often refuse to answer these questions for safety, ethical reasons, and to avoid conveying potentially harmful or misinterpreted information.
What percentage of sensitive requests are typically filtered by chatbots?
It has been observed that up to 27.4 % of responses may be filtered, redirected, or denied, depending on the model and the nature of the request.
How can the results of SpeechMap help understand chatbot limits?
The results of SpeechMap provide factual data on how different chatbots react to sensitive requests, thereby allowing users to become aware of the limitations and potential biases of AI models.
Have OpenAI chatbots become more restrictive over time?
Yes, it has been noted that with successive iterations such as GPT-3.5 and GPT-4, these models have shown a trend to refuse more sensitive requests compared to previous versions.
What are the implications of moderating chatbot responses on freedom of expression?
The moderation of responses can raise ethical questions about freedom of expression, as it can lead to unintentional censorship or bias in the information provided to users.
Are chatbot responses influenced by cultural or social biases?
Yes, chatbot responses may be influenced by biases embedded during their training, which can result in answers reflecting stereotypes or perspectives specific to certain cultures or societies.
What is the importance of transparency in chatbot algorithms?
Transparency is crucial as it allows users to understand how chatbots process information and make decisions, which is essential for establishing trust in the use of AI technologies.
