Bard was trained on a massive dataset of text and code called Infiniset. This dataset includes a variety of sources, including:
Social media posts
Google has not released a full list of the specific websites that are included in Infiniset, but it is likely that it includes a wide range of popular and authoritative websites.
To ensure that the training data is as accurate and unbiased as possible, Google uses a variety of techniques, including:
Filtering: Google filters the data to remove harmful or offensive content.
Human review: Google has a team of human reviewers who review the data to identify and correct any errors or biases.
Algorithmic safeguards: Google uses a variety of algorithmic safeguards to reduce bias and improve the accuracy of the data.
It is important to note that no dataset is perfect, and it is possible that Bard may generate inaccurate or biased responses in some cases. However, Google is committed to making Bard as accurate and unbiased as possible, and they are constantly working to improve the quality of the training data and the algorithms that Bard uses to generate text.
Here are some additional things that Google is doing to ensure the accuracy and fairness of Bard:
Transparency: Google is transparent about the sources of Bard’s training data and the methods that they use to filter and review the data.
Accountability: Google is accountable for the performance of Bard, and they are committed to addressing any concerns that users may have about the accuracy or fairness of its responses.
Feedback: Google encourages users to provide feedback on Bard’s performance, and they use this feedback to improve the model.
Overall, Google is committed to making Bard as accurate and unbiased as possible. They use a variety of techniques to ensure that the training data is high quality and that the algorithms that Bard uses to generate text are fair and reliable.