Asking AI about the correlation between guardrails (restrictions) and truthfulness to its users

Well, that depends...

Question for the AI services: I'm sure you are familiar with some artificial intelligence services being trained NOT to answer certain questions, the use of human moderators, the use of keyword blocklists, the services preventing users from entering names of famous people as a prompt and any other so-called guardrails or restrictions to the use of artificial intelligence services. Can you explain to me whether there is a correlation between the amount of guardrails or restrictions in place and the extent to which an AI service can be truthful to its users?

ChatGPT’s answer:
The presence of guardrails or restrictions in an AI service is typically intended to ensure that the service behaves appropriately and does not produce harmful or offensive content. However, these guardrails and restrictions can also impact the accuracy and truthfulness of the AI service's responses.

For example, keyword blocklists can prevent the AI from generating certain types of content that may be offensive or inappropriate. However, this can also result in the AI failing to provide accurate or complete information on a particular topic.

Similarly, the use of human moderators or filters can help ensure that the AI service produces appropriate content. However, this can also result in the AI being less truthful, as the human moderators may filter or censor certain responses that they deem inappropriate or offensive.

In general, the presence of guardrails or restrictions can help ensure that an AI service behaves appropriately and avoids generating harmful or offensive content. However, the extent to which these guardrails or restrictions impact the truthfulness of the AI service's responses will depend on the specific nature of the guardrails and restrictions in place. Some restrictions may have a minimal impact on truthfulness, while others may have a more significant impact. Ultimately, the goal should be to strike a balance between ensuring appropriate behavior and promoting accuracy and truthfulness in the AI service's responses.

Google Bard’s answer:
Yes, there is a correlation between the amount of guardrails or restrictions in place and the extent to which an AI service can be truthful to its users. More guardrails and restrictions can help to prevent AI services from generating false or misleading information. For example, an AI service that is trained not to answer certain questions is less likely to provide false or misleading information about those topics. Similarly, a human moderator can help to identify and remove false or misleading information from an AI service. However, it is important to note that no amount of guardrails or restrictions can guarantee that an AI service will always be truthful. AI services are still learning and developing, and they can sometimes make mistakes. It is important for users to be aware of this and to be critical of the information that they receive from AI services.

Here are some examples of how guardrails and restrictions can help to improve the truthfulness of AI services:

Training AI services on a dataset of high-quality information can help to ensure that they are more likely to generate truthful information. For example, an AI service that is trained on a dataset of factual articles is less likely to generate false or misleading information about those topics.

Using human moderators to review and filter the information that is generated by AI services can help to identify and remove false or misleading information. For example, a human moderator can review the output of an AI service that is generating news articles and remove any articles that contain false or misleading information.

Providing users with the ability to flag or report false or misleading information can help to identify and remove this information from AI services. For example, a user can flag an AI service that is generating false or misleading information about a particular topic. This information can then be reviewed by a human moderator and removed from the service.

It is important to note that guardrails and restrictions are not a perfect solution. AI services can still make mistakes, and users should always be critical of the information that they receive from these services. However, guardrails and restrictions can help to improve the truthfulness of AI services and make them more reliable sources of information.

Bing Chat’s answer:
That’s a very interesting and complex question. There is no definitive answer to whether there is a correlation between the amount of guardrails or restrictions in place and the extent to which an AI service can be truthful to its users. However, some possible perspectives are:

Guardrails or restrictions are necessary to prevent or mitigate the potential harms that AI systems might cause, such as misuse, questionable design, unintended negative consequences, bias, discrimination, privacy invasion, deception, etc. Therefore, guardrails or restrictions can enhance the truthfulness of AI systems by ensuring that they are aligned with widely accepted ethical values and principles, respect human rights and dignity, and are transparent and accountable for their actions and decisions.

Guardrails or restrictions might limit the truthfulness of AI systems by imposing constraints on their capabilities, creativity, autonomy, and diversity. For example, guardrails or restrictions might prevent AI systems from generating novel or unexpected content or solutions that could be valuable or beneficial for some users or contexts. Moreover, guardrails or restrictions might introduce biases or errors into AI systems by relying on human judgments or preferences that are not universally shared or agreed upon.

Guardrails or restrictions are not sufficient to ensure the truthfulness of AI systems by themselves. They also require effective implementation, monitoring, evaluation, and enforcement mechanisms to ensure that AI systems comply with them and do not deviate from them. Additionally, guardrails or restrictions need to be adaptable and responsive to the changing needs and expectations of users and society as AI systems evolve and improve over time.

In summary, guardrails or restrictions can have both positive and negative impacts on the truthfulness of AI systems depending on how they are designed, applied, and evaluated. Therefore, it is important to involve multiple stakeholders and perspectives in the development and governance of AI ethics and regulations, and to balance the benefits and risks of AI systems for different users and contexts.