My AI assistant has also created a podcast episode for the following article. If you prefer listening to reading, you can listen to the podcast via the following link (ATTENTION: Podcast is created exclusively by AI, no guarantee for accuracy).

What does giving feedback mean for AI?

The provision of feedback for artificial intelligence (AI) technologies, such as ChatGPT, Perplexity or SwissGPT, involves the transmission of information that we as users return to the AI system. This feedback can be provided in various ways, the most common methods being the following:

1. simple evaluation of the response received from the AI technology by selecting quick responses at the end of the interaction, such as clicking on “thumbs up” or “thumbs down” icons.

2. analyzing our general use of AI technology, including how we ask questions and in particular how we generate follow-up questions.

3. direct feedback on the performance of the AI technology in the form of constructive written feedback and specific correction requests, which we address directly to the AI system via the input field.

4. general feedback via ticketing systems to the developers of the AI technologies, whereby it should be noted that not all developers offer the opportunity to provide such direct feedback to the team.

When giving feedback, it is important that it can also be positive in order to encourage the AI to give similar, correct answers in the future. In the case of negative feedback, care should be taken to ensure that it is formulated as constructively as possible. Constructive feedback goes beyond simply pointing out mistakes by not only pointing out errors, but also offering alternative solutions or suggestions for improvement. This helps developers and AI technology to identify learning patterns and make specific adjustments that help optimize AI capabilities.

How do AI technologies learn from feedback?

Artificial intelligence (AI) technologies are able to learn from data and improve over time. The core of this learning process is based on the principle of feedback: by analyzing user reactions with the AI technology, which show how the technology is used in a real context and where there is a need for adaptation, developers can continuously improve the AI technologies. Even more helpful for the developers is the evaluation of direct user feedback. This allows developers to recognize AI bias, increase the diversity of data sources and adapt algorithms to deliver fairer and more inclusive results. Our user feedback therefore helps the developer to adjust the direction of AI development so that it meets our needs and values.

It should be noted that this improvement process is highly dependent on the quality and quantity of the feedback provided. The more precise and comprehensive the user feedback is, the better and faster an AI technology can be optimized.

Why is giving feedback becoming increasingly important?

In the dynamic world of artificial intelligence (AI), the user plays a decisive role that goes far beyond the mere application of the technology. User feedback is becoming an important design tool that flows directly into the development and improvement process of AI technologies. By sharing experiences, reporting errors or suggesting improvements, we users actively contribute to shaping AI technology. If this reporting of errors or general feedback fails to materialize, AI technologies will still be developed further, but without the involvement of us as responsible users.

Active participation in the feedback process is therefore essential, as it makes it possible to adapt AI technology to the real needs and expectations of us humans. Our user feedback helps to improve the effectiveness, accessibility and usability of AI technologies by providing developers with valuable insights into practical application and user experience.

Why is giving feedback part of the responsible use of AI technologies?

The task of providing user feedback is not only essential for the further development of AI technology in the right direction, but also entails a certain responsibility. Our user feedback should be precise, constructive and honest in order to have a positive impact. Vague or misleading feedback can slow down the improvement process or even steer it in the wrong direction. It is therefore important that we users are aware of how our feedback is used and that we strive to provide clear and helpful information.

At the same time, it is crucial to be aware of the consequences of failing to give feedback, whether positive or negative. In such a case, other people will take the opportunity to express their feedback and we may lose our influence on the further development of the technology. In the worst case, this could lead to a situation where only people with different values, such as criminals, contribute their views. This could result in AI technology developing in an undesirable direction.

How do I give effective feedback?

Giving effective feedback to an AI technology requires clear communication between us users and the AI technology. As with prompting, i.e. creating the requirements for the AI technology, the more precise and detailed the feedback we provide, the better and faster the AI technology can be optimized. For example, it’s more helpful to say, “The pitch of this music recommendation doesn’t suit my taste”, rather than just “I don’t like this song”. Such precise information can help developers to better adjust the AI.

If we don’t have that much time, we should at least use integrated feedback buttons or comment fields to at least provide initial, brief feedback on the quality of the AI response.

What are the biggest challenges when giving feedback to AI technologies?

One of the biggest challenges in providing feedback to AI technologies lies in the quality and precision of the feedback itself. Users often lack the technical understanding to effectively communicate what the AI is doing wrong or how it could be improved. This often leads to vague or emotionally driven feedback that is of little help in improving the AI. To counteract this challenge, it helps to educate users as early as possible about the background and functionality of AI technologies. You can read more about how ChatGPT works in my article“What is ChatGPT“, for example.

Furthermore, when giving feedback, there is always the risk that feedback is influenced by the user’s subjective prejudices, which can lead to a distortion in optimization. So we need to be aware that giving feedback is really a responsible task that we should definitely do, and do it in a correspondingly high quality.

The developers of AI technologies may also face challenges. A common problem is the scaling of the feedback process. With millions of users potentially providing feedback on an AI technology, it is an enormous technical and organizational challenge to collect, analyze and implement this data effectively. To do this, companies need robust data processing systems and advanced algorithms that are able to learn from large volumes of feedback data. Data protection regulations must also be observed, especially if the feedback contains personal or sensitive information. These aspects require careful planning by the developers of the AI technology and continuous monitoring to ensure that the feedback not only helps to improve the AI technology in general, but also complies with ethical and legal standards.

Summary and outlook: Giving feedback as the basis for responsible use of AI technologies

The systematic integration of user feedback in the development and improvement of AI systems is crucial for their success and acceptance. As was made clear in the previous sections, high-quality feedback plays a key role in increasing the performance and accuracy of AI technologies. It enables AI developers to identify weaknesses and continuously optimize AI technologies.

Looking to the future, the importance of feedback in AI development will continue to grow as AI technologies are increasingly used in critical and complex application areas. The challenge will be to develop effective mechanisms that not only ensure high quality feedback, but also enable it to be processed quickly and efficiently.

The importance of responsible and mindful users of AI technologies will continue to increase in the future. As users of these technologies, we must be aware of the associated responsibility and continuously provide feedback, whether positive or negative, to the AI systems. It is essential to understand that responsible use of AI technologies involves more than just observing data protection, critical thinking and transparency. The prudent and responsible use of AI technologies increasingly includes providing regular feedback. This is becoming increasingly important to ensure that AI technologies do not develop contrary to our ethical values.

Companies and developers are therefore called upon to strengthen and continuously improve feedback cultures. This will not only improve the quality of AI systems, but also ensure their social acceptance. The integration of feedback is therefore an essential basis for the sustainable and responsible use of artificial intelligence.

Fancy more?

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This article is also available as a podcast episode

Attention! The podcast was created entirely by my AI-Assistant based on my contribution – no guarantee for incorrect content.