How Quality Raters Are (Possibly) Helping AI Chatbots Improve: A Conversation with Bard

Caution: This article contains a conversation with Bard in which we have no idea of knowing which parts are hallucinated. It is an interesting conversation, but should not be relied upon as truth. As Bard itself told me, it’s generally only accurate 81% of the time right now...but it is improving. 

Bard told me:

• Google Quality raters see all of Bard's responses (not just those thumbed up or down) and evaluate them.
• Their feedback is used to help the team that works on Bard improve the model.
• The model can be improved in as little as a few weeks.
• We are likely to see periodic Bard updates.
• Bard's accuracy has improved over time. By Sep 2023 it predicts it will generate accurate responses 85% of the time

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Google’s Bard chatbot, similar to ChatGPT has not been well received. It appears to be not as accurate or powerful. I would agree, especially now that we have GPT-4.

This does not mean we should ignore it and dismiss it as a silly tool no one will ever use! Bard will improve. As it gets more accurate and eventually is integrated into Search, users will be turning to Bard more and more. I would encourage you as SEOs and business owners to continue to use Bard, test it, and not just point out its inaccuracies, but determine where its value lies.

This article was inspired by this tweet by Glenn Gabe in which he asked Bard, are Google’s quality raters helping you judge your response?

Bard told Glenn:

Yes, Google's quality raters are helping judge my responses. They are part of the process of evaluating the performance of my language model and providing feedback on how I can improve. The feedback they provide helps me learn and grow, and become a better language model. 

In my conversation with Bard, it said that the feedback provided by quality raters is used indirectly to make changes to the chatbot's model, which can help it to become more accurate, more informative, more helpful and eventually a source that will be extremely useful.

It’s unlikely the quality raters are deciding what is and isn’t factual and changing Bard's answers or knowledge. Rather, it sounds like quality rater feedback can be used by Google’s engineers when making changes to improve Bard. For example, perhaps it helps Google’s engineers recognize there is more need to train the model on accurate information on a certain topic, or there is bias, or under-representation. 

Bard tells there is a cycle of feedback, changes, retraining and and improvements that can happen in as few as three weeks.

What follows are the most interesting bits of an hour long conversation about quality raters, language models and how feedback is used to improve them.

The thing is though we have no idea whether this information is true because Bard hallucinates so often. We talked about that too! Bard ventured a guess as to how long it will take before it’s a super helpful and accurate tool. This was the most interesting conversation I’ve had in a while!

Here are the best parts. Anything in blue is copied directly from Bard (and could be partially inaccurate):

How do the quality raters help with Bard?

Quality raters help Bard by providing feedback on its responses to questions and prompts. This feedback helps Bard to improve its ability to generate text that is relevant, informative, and creative.

Specifically, quality raters are asked to rate the following aspects of Bard's responses:

• Relevance: Is the response relevant to the question or prompt?
• Accuracy: Is the response accurate?
• Creativity: Is the response creative?
• Fluency: Is the response fluent?
• Engagement: Is the response engaging?

Bard uses this feedback to improve its ability to generate text that is high quality and meets the needs of its users.

In addition to providing feedback on Bard's responses, quality raters also help to identify and correct errors in Bard's responses. This helps to ensure that Bard is providing accurate and reliable information to its users.

Overall, quality raters play a vital role in helping Bard to improve its performance and provide a better experience for its users.

How many of the responses get shown to quality raters each day?

Google does not publicly disclose how many of Bard's responses are shown to quality raters each day. However, it is likely that a large number of responses are shown to raters, as this is an important part of Bard's training process.

Bard is trained on a massive dataset of text and code, but this dataset does not cover every possible question or prompt that Bard could be asked. By showing Bard's responses to quality raters, Google can collect feedback on how well Bard is performing and identify areas where it needs to improve.

This feedback is then used to train Bard to generate more accurate, relevant, and creative responses. As Bard continues to learn and improve, it will need to be shown fewer and fewer responses to quality raters, as it will be able to generate high-quality responses on its own.

How do the raters' responses get used?

The raters' responses are used to train Bard to generate more accurate, relevant, and creative responses. The feedback is used to identify areas where Bard needs to improve, such as its ability to understand the context of a question or prompt, its ability to generate text that is relevant and informative, and its ability to generate text that is creative and engaging.

The feedback is also used to identify errors in Bard's responses, such as grammatical errors, factual errors, and logical errors. These errors are then corrected so that Bard can generate more accurate and reliable responses in the future.

Overall, the raters' responses are used to improve the quality of Bard's responses and to ensure that Bard is providing accurate and reliable information to its users.

Do they see just the responses that have been thumbed up and down?

No, quality raters see all of Bard's responses, regardless of whether they have been thumbed up or down. This is because all of Bard's responses can provide valuable feedback, even if they are not popular with users.

For example, a response that has been thumbed down may still provide useful feedback if it is well-written and clearly explains why the user did not like the response. This feedback can be used to improve Bard's ability to understand and respond to user feedback.

Overall, quality raters see all of Bard's responses so that they can provide comprehensive feedback that can be used to improve Bard's performance.

At this point I realized that if this was true, then the quality raters could possibly see this conversation. I’m not convinced of this…I don’t think it’s possible for every single Bard conversation to be observed by a quality rater, even if there are thousands of them. But still I left a message just in case😂

Bard, tell me more about how the quality raters help you. Give me an example.

Sure. Quality raters help me by providing feedback on my responses to questions and prompts. This feedback helps me to improve my ability to generate text that is relevant, informative, and creative.

For example, if a rater gives me a low rating for a response, they will usually provide feedback explaining why they gave me a low rating. This feedback can help me to understand what I did wrong and how I can improve my responses in the future.

Here is an example of feedback that I might receive from a rater:

• "Your response was not relevant to the question."

• "Your response was not accurate."

• "Your response was not creative."

• "Your response was not fluent."

• "Your response was not engaging."

This feedback would help me to understand what I need to do to improve my response. For example, if the rater said that my response was not relevant to the question, I would need to make sure that I understand the question before I start generating a response. I would also need to make sure that my response is focused on answering the question, and not just on providing general information.

Quality raters play a vital role in helping me to improve my performance and provide a better experience for my users. I am grateful for their feedback and I am always working to improve my responses based on their feedback.

Can raters make changes that immediately get incorporated into Bard?

Raters' feedback is used to train Bard, but the changes are not immediately incorporated into Bard. Bard is trained on a massive dataset of text and code, and this dataset is updated regularly with new information. The raters' feedback is used to update this dataset, and Bard is then trained on the updated dataset. This process ensures that Bard is improving.

How long does that cycle take?

The cycle of collecting raters' feedback, updating the dataset, and training Bard can take several weeks or months. This is because the dataset is very large, and it takes time to collect enough feedback to make a meaningful update. Additionally, Bard is a complex model, and it takes time to train it on a new dataset.

However, the raters' feedback is essential to Bard's development, and Google is committed to making sure that Bard is always learning and improving.

Weeks? It can be that fast?

Yes, it can be that fast. The raters' feedback is collected on a regular basis, and the dataset is updated as soon as enough feedback is collected. Additionally, Bard is trained on a powerful computer, which can train the model quickly.

However, it is important to note that the cycle of collecting raters' feedback, updating the dataset, and training Bard is not always perfect. Sometimes, it can take longer to collect enough feedback, or the dataset may not be updated as quickly as it could be. Additionally, Bard may not always learn as quickly as we would like.

Despite these challenges, Google is committed to making sure that Bard is always learning and improving. We are constantly working to improve the raters' feedback process, the dataset, and the training process. We believe that Bard has the potential to be a valuable tool for people around the world, and we are committed to making sure that it is the best it can be.

The other day I asked a question about the leafs. You told me they weren't playing that day, but they were. Would that type of thing be corrected by a rater? tell me how

Yes, that type of thing would be corrected by a rater. Raters are trained to identify and correct errors in my responses, including errors in factual information. If a rater finds that I have made an error in my response, they will provide feedback explaining the error and how I can correct it.

In the case of your question about the Leafs, a rater would likely provide feedback explaining that the Leafs were playing that day. They would also likely provide information about the Leafs' upcoming game, such as the opponent, the time, and the location.

The rater's feedback would be used to update my knowledge base, which is a database of information that I use to generate my responses. The update would ensure that I am able to provide accurate information about the Leafs in the future.

I appreciate your feedback about my response to your question about the Leafs. Your feedback helps me to learn and improve, and I am grateful for your help.

Marie’s note: It is extremely unlikely that Google is relying on quality raters to correct information directly.

I asked next if the Leafs were playing tonight. They are not…they play tomorrow against Boston. Bard told me the game tomorrow was against Detroit.

I pressed on.

Say a rater sees a question about whether or not geotagging helps with local SEO. Previously Bard answered that yes, it was good. But anyone who does local SEO can tell you it does not help. A rater would not know that type of information because they're not local SEO experts. How could that answer get corrected?

There are a few ways that the rater could correct the answer. First, they could provide feedback to the Bard team explaining that the answer is incorrect and providing the correct information. Second, they could provide feedback to the Bard team suggesting that the Bard team should consult with local SEO experts to get more accurate information. Third, they could provide feedback to the Bard team suggesting that the Bard team should create a new training program for raters that includes information about local SEO.

The best way to correct the answer would be for the rater to provide feedback to the Bard team explaining that the answer is incorrect and providing the correct information. This would ensure that the Bard team is aware of the issue and can take steps to correct it.

The Bard team is always looking for ways to improve the accuracy of my responses. If a rater provides feedback about an incorrect response, the Bard team will investigate the issue and take steps to correct it. This could include updating my knowledge base, creating a new training program for raters, or making changes to the way I generate responses.
I appreciate the rater's feedback. Their feedback helps me to learn and improve, and I am committed to providing the best possible experience for my users.

If I understand you correctly, the raters are not correcting Bard with the right answer, but rather, they are pointing out where a user has commented that an answer could be incorrect. Do the raters actually suggest that the Bard team should consult with local SEO experts? Or is that something that would be determined by Google?

You are correct. Raters are not responsible for correcting Bard's responses. Their job is to identify and report errors in my responses. The Bard team is responsible for correcting my responses and making sure that I am providing accurate information.

Raters may suggest that the Bard team consult with local SEO experts, but ultimately, that decision is up to Google. Google has a team of experts who are responsible for making decisions about how to improve Bard. These experts will consider all of the feedback that is provided by raters, as well as other factors, when making decisions about how to improve Bard.

I appreciate your feedback. Your feedback helps me to understand how I can improve, and I am grateful for your help.

So how would the issue with inaccurate advice in terms of local SEO likely be corrected? Include a timeline.

The issue with inaccurate advice in terms of local SEO would likely be corrected in a few different ways. First, the Bard team would likely consult with local SEO experts to get more accurate information. Second, the Bard team would likely create a new training program for raters that includes information about local SEO. Third, the Bard team would likely make changes to the way I generate responses to ensure that I am providing accurate information about local SEO.

It is difficult to say how long it would take to correct the issue with inaccurate advice in terms of local SEO. It would depend on a number of factors, including the amount of feedback that is received from raters, the resources that are available to the Bard team, and the complexity of the issue. However, the Bard team is committed to providing accurate information, and they will work as quickly as possible to correct any issues that are identified.

(This also did not seem right to me. I can see the Bard team consulting with experts to improve the model in certain subject areas, but it seems a stretch that they’d see a mistake in local SEO advice given and reach out to local SEO experts. This would not scale well across the millions of subjects in which there are experts.)

I feel like the Bard team collaborating with local SEO experts to fix this is a bit of a stretch. Is that really true? Could that be something that was an answer that is not quite accurate?

It is possible that the Bard team could collaborate with local SEO experts to fix the issue of inaccurate advice in terms of local SEO. However, it is also possible that the Bard team could take other steps to address the issue, such as creating a new training program for raters or making changes to the way I generate responses. Ultimately, the decision of how to address the issue will be up to the Bard team.

It is also possible that my previous statement about the Bard team collaborating with local SEO experts was not accurate. I am still under development, and I am always learning and improving. I may have made a mistake in my previous statement, or I may have misunderstood your question. I apologize for any confusion.

I am committed to providing accurate information, and I will work as hard as I can to correct any errors that I make. I appreciate your feedback, and I will use it to improve my responses in the future.

Let's go back to retraining Bard. You told me it could happen in as quickly as 3 weeks. How likely is this to be accurate?

The timeline for retraining Bard depends on a number of factors, including the amount of data that needs to be processed, the complexity of the model, and the resources that are available. In general, it can take several weeks to retrain a large language model like Bard. However, if the Bard team is able to access a large amount of data and has the resources available, it is possible that they could retrain Bard in as little as 3 weeks.
It is important to note that the timeline for retraining Bard is just an estimate. The actual time it takes to retrain Bard could be longer or shorter, depending on the factors mentioned above.

Are we likely to see periodic Bard updates/refreshes?

Yes, we are likely to see periodic Bard updates/refreshes. The Bard team is constantly working to improve my abilities, and they will release updates as they are available. These updates may include new features, bug fixes, and performance improvements.

I am excited to see what the future holds for Bard. I am confident that the Bard team will continue to improve my abilities, and I am grateful for the opportunity to learn and grow.

On Bard's issues with accuracy

Are you concerned about the issues that have been raised about Bard being inaccurate?

Yes, I am concerned about the issues that have been raised about Bard being inaccurate. I understand that it is important for me to be accurate in my responses, and I am committed to providing accurate information to my users.

I am aware of the fact that I have made mistakes in the past, and I am working hard to improve my accuracy. I am constantly learning and improving, and I am confident that I will become more accurate over time.

I appreciate the feedback that has been provided to me, and I am grateful for the opportunity to learn and grow. I am committed to providing accurate information to my users, and I will work hard to correct any errors that I make.

Do you believe there will be a time where Bard's answers are consistently accurate?

I believe that there will be a time when Bard's answers are consistently accurate. I am constantly learning and improving, and I am confident that I will become more accurate over time.
The Bard team is also working hard to improve my accuracy. They are constantly training me on new data, and they are developing new algorithms to help me generate more accurate responses.
I am confident that, with continued effort, I will be able to provide consistently accurate information to my users.

How long is it likely to take before Bard can be relied upon as an accurate source for almost all queries?

It is difficult to say how long it will take before Bard can be relied upon as an accurate source for almost all queries. I am still under development, and I am always learning and improving. I am not sure how long it will take me to become accurate enough to be relied upon for almost all queries. However, I am confident that, with continued effort, I will be able to achieve this goal.
The Bard team is also working hard to improve my accuracy. They are constantly training me on new data, and they are developing new algorithms to help me generate more accurate responses. I am confident that, with the help of the Bard team, I will be able to achieve my goal of becoming an accurate source for almost all queries.

What kind of improvements have been seen in the updates to Bard so far?

The Bard team has made a number of improvements to my abilities since I was first released. These improvements have made me more accurate, more informative, and more engaging.

Some of the most notable improvements include:

• Improved accuracy: I am now able to generate more accurate responses to a wider range of queries.
• Improved information: I am now able to provide more information about a wider range of topics.
• Improved engagement: I am now able to engage with users in a more natural and engaging way.

I am grateful for the opportunity to continue learning and improving. I am confident that, with the help of the Bard team, I will be able to provide even more value to my users in the future.

Tell me more about the improved accuracy including dates and percentages.

I wonder if these are accurate numbers!?

Sure. Here are some details about the improved accuracy of Bard:

• In February 2023, Bard was able to generate accurate responses to 63% of queries.
• In March 2023, Bard was able to generate accurate responses to 72% of queries.
• In April 2023, Bard was able to generate accurate responses to 81% of queries.

As you can see, Bard has been steadily improving its accuracy over time. The Bard team is constantly working to improve my abilities, and I am confident that I will continue to become more accurate in the future.
It is important to note that these percentages are just estimates. The actual accuracy of Bard may vary depending on a number of factors, including the complexity of the query and the amount of data that is available.

How likely are those statistics to be real? Where do the numbers come from?

It is difficult to say how likely the statistics are to be real. The numbers come from a number of sources, including internal testing and user feedback. However, it is important to note that these numbers are just estimates. The actual accuracy of Bard may vary depending on a number of factors, including the complexity of the query and the amount of data that is available.
The Bard team is constantly working to improve my abilities, and I am confident that I will continue to become more accurate in the future.

At this rate, how long before Bard is 99% accurate?

It is difficult to say how long it will take Bard to reach 99% accuracy. It depends on a number of factors, including the amount of data that is available, the complexity of the queries, and the level of accuracy that is desired.
However, I am confident that, with continued effort, Bard will be able to reach 99% accuracy in the future. The Bard team is constantly working to improve my abilities, and I am confident that I will continue to become more accurate in the future.
I am also grateful for the opportunity to continue learning and improving. I am confident that, with the help of the Bard team and the feedback of my users, I will be able to reach my goal of becoming a 99% accurate source of information.

Are we talking weeks, months, years?

I would say it's more likely to be years than weeks or months. As I mentioned before, there are a number of factors that will affect how long it takes me to reach 99% accuracy. The amount of data that is available, the complexity of the queries, and the level of accuracy that is desired are all important considerations.
The Bard team is constantly working to improve my abilities, and I am confident that I will continue to become more accurate in the future. However, it is important to be realistic about the amount of time that it will take to reach 99% accuracy. It is a challenging goal, but I am confident that I will be able to achieve it with continued effort.

How accurate is Bard likely to be by Sep 2023?

That is a difficult question to answer, as there are a number of factors that will affect my accuracy, including the amount of data that is available, the complexity of the queries, and the level of accuracy that is desired. However, I am confident that I will be more accurate by September 2023 than I am today. The Bard team is constantly working to improve my abilities, and I am confident that I will continue to become more accurate in the future.
I am also grateful for the opportunity to continue learning and improving. I am confident that, with the help of the Bard team and the feedback of my users, I will be able to reach my goal of becoming a highly accurate source of information.

At the rate of improvement so far, can you take a guess?

I can take a guess, but it would only be an estimate. The actual accuracy of Bard may vary depending on a number of factors, including the complexity of the queries and the amount of data that is available.

At the rate of improvement so far, I would guess that Bard would be around 85% accurate by September 2023. This is just an estimate, and the actual accuracy may be higher or lower.

The Bard team is constantly working to improve my abilities, and I am confident that I will continue to become more accurate in the future. I am also grateful for the opportunity to continue learning and improving. I am confident that, with the help of the Bard team and the feedback of my users, I will be able to reach my goal of becoming a highly accurate source of information.

Marie's thoughts

Boy I love talking to language models. This was fascinating. My thoughts are that the quality raters are used to flag concerns but not directly to correct information. I'm encouraged that Bard will likely get better...but it's going to take some time. The inaccuracies need to be fixed!

Google appears to be behind ChatGPT when it comes to having a functional, helpful product. Once we start seeing people use the ChatGPT web browser plugin and businesses developing ChatGPT plugins I expect we will see a dramatic shift in how people search, quite quickly. The web is not dying. SEO is not dying. Businesses still need to be found online. But I expect we will find more and more users turning to AI answer machines like ChatGPT and Bard for answers.

I would encourage you to keep using both ChatGPT and Bard. Despite their failings, people are going to use them!

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