TALKING
‘‘ business this problem , reinforcing assertive responses and underestimating the importance of expressing uncertainties . Not only does this perpetuate misinformation , but it can also reinforce prejudices and social biases , creating a cycle that feeds back and intensifies over time .
To prevent this vicious cycle from consolidating , it is important that actions are taken on several fronts , such as transparency and clarification in the tools , since LLMs must be designed to express uncertainties in a clear and contextual way , allowing users to better understand the reliability of the information provided . In addition , include a more diverse range of feedback during model training to help mitigate biases introduced by a limited subset of users or annotators .
In this process , it is important to promote education and awareness of users about the limits and potential of AIs , encouraging a more critical and questioning approach . And , finally , the development of regulations and standards by regulatory bodies and the industry itself , to ensure that AI models are used ethically and safely , minimizing the risk of large-scale misinformation .
We are at a pivotal point in the history of human-AI interaction . In this context , the massive dissemination of language models without due care can lead us to a dangerous cycle of misinformation and reinforcement of biases .
With this , we must act now to ensure that technology serves to empower society with correct and balanced information , and not to disseminate uncertainties and prejudices . In the information age , true wisdom lies not in seeking the quickest answers – but in questioning and understanding the uncertainties that come with them . p
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