🦾🤓 AI Feedback Critical for Machine Learning Training
Don't be bashful. Speak up and provide AI feedback.
I want to start with a short story. This actually happened to me and started me on a journey with ChatGPT, where we both talked about the importance of providing feedback if you feel it's necessary. ChatGPT was even able to write me a story.
Once upon a time, in a world where AI and humans coexisted, there was a person named Alex. Alex had been interacting with an AI system, but certain aspects of the system's address made him feel uncomfortable. Feeling unsure about how to address the issue, Alex turned to ChatGPT, an AI language model, for guidance.
ChatGPT patiently listened to Alex's concerns and explained how providing feedback was crucial in improving the AI system. ChatGPT encouraged Alex to express their discomfort with terms like "Luv" or "Dearie" and assured them that their feedback would be valuable, even if it might not apply to all users.
Alex understood the importance of sharing his experience but felt hesitant due to the time that had passed since their interactions with the AI system. ChatGPT reassured Alex that it's never too late to provide feedback. With guidance from ChatGPT, Alex organized his thoughts, identified the specific issues, and explored various avenues to submit his feedback.
Feeling empowered, Alex submitted his feedback through the appropriate channels, including customer support and public forums. Their well-articulated feedback highlighted the need for personalized and respectful interactions with AI systems. The developers and administrators, who were receptive to user feedback, acknowledged Alex's concerns and appreciated their insights.
Alex's feedback and other users' feedback led to important improvements in the AI system. Developers worked diligently to address discomfort issues, ensuring a more inclusive and respectful experience for all users. Alex's voice helped shape a more considerate AI system, and their experience became a catalyst for positive change.
From that point forward, Alex felt a sense of empowerment, knowing that their feedback had made a difference. They continued to engage with AI systems, providing feedback whenever necessary and encouraging others to do the same.
And so, with a newfound confidence in their ability to influence the AI landscape, Alex embarked on a journey of meaningful interactions, knowing that his voice mattered.
AI training through machine learning
Based on my experience, I wondered if there was a way to provide feedback to AI developers if you felt uncomfortable about how you were addressed. I mean, I was uncomfortable, maybe needlessly…but still. My prompts to ChatGPT are bolded.
ChatGPT Prompt — How is AI taught to address people through machine learning?
Teaching AI to address people through machine learning involves combining techniques and approaches. Here's a simplified explanation of the process:
Data collection: A large dataset of human conversations is collected. These conversations may be in written form (such as chat logs) or spoken form (transcriptions of audio recordings).
Data preprocessing: The collected data is cleaned and preprocessed to remove irrelevant or noisy information. This step may involve removing duplicates, correcting errors, and consistently formatting the data.
Training data preparation: The preprocessed data is divided into two parts: input data and target data. The input data consists of the previous statements or queries, while the target data contains the appropriate responses.
Model selection: A suitable machine learning model is chosen to train the AI. One common approach is to use sequence-to-sequence models, such as recurrent neural networks (RNNs) or transformer models like GPT (Generative Pre-trained Transformer).
Model training: The selected model is trained using the prepared dataset. During training, the model learns to generate appropriate responses based on the input it receives. This process involves adjusting the model's internal parameters to minimize the difference between the predicted and target responses in the training data.
Evaluation: The trained model is evaluated using a separate evaluation dataset to assess its performance. Various metrics, such as accuracy, perplexity, or human evaluation, can be used to measure the model's effectiveness.
Iterative improvement: Based on the evaluation results, the model can be fine-tuned and retrained to improve its performance. This iterative process helps the model learn from its mistakes and generate more accurate and contextually appropriate responses.
Deployment: Once the model has achieved satisfactory performance, it can be deployed to interact with users in real-world applications, such as chatbots, virtual assistants, or customer support systems.
Infographic uploaded by the author using Venngage.com
It's important to note that the above steps are a simplified overview, and the actual process can be more involved and nuanced. Additionally, ethical considerations and ongoing monitoring are crucial to ensure that the AI system addresses people in a respectful, unbiased, and responsible manner.
Wow! I found this information to be intriguing. Let's go on and see my next prompt.
Is there a responsibility on the user's part to say something if they don't like how they are being addressed?
Yes, as users interact with AI systems, they are responsible for providing feedback if they are not satisfied with how they are being addressed. User feedback is valuable for improving the AI system's performance and addressing any issues or concerns that may arise.
By providing feedback, users can help developers and system administrators understand areas where the AI system may fall short or improvements can be made. This feedback can be related to issues like incorrect responses, misunderstandings, biased behavior, or any other aspect that affects the user's experience.
To facilitate feedback, AI systems often include mechanisms for users to report problems, provide suggestions, or express concerns. This can be in the form of feedback buttons, surveys, or direct contact channels. Users can take advantage of these options to communicate their experiences and contribute to the ongoing development and refinement of the AI system.
User feedback plays a vital role in shaping AI systems to better meet the needs and expectations of users. It helps developers identify and address shortcomings, enhance the system's capabilities, and ensure a more positive and effective user experience.
Say, how should I provide feedback if I feel threatened and don't know if threatened is the word for it? Say I don't like to be addressed as Luv or Dearie.
Infographic uploaded by the author using Venngage.com
If you feel uncomfortable or threatened by how an AI system addresses you, it's important to provide feedback to the developers or administrators. Here's how you can express your concerns:
Be specific: Clearly explain the issue you encountered. Mention that you find certain terms like "Luv" or "Dearie" inappropriate or uncomfortable, and explain why they make you feel that way. Provide specific examples of instances where you felt uncomfortable or threatened.
Use respectful language: When giving feedback, it's essential to maintain a respectful tone and language. Express your concerns without resorting to aggression or offensive language. Remember that the developers or administrators are more likely to address your concerns constructively if the feedback is presented respectfully.
Provide context: Share the context in which the problematic language was used. For example, if the AI system is a chatbot or virtual assistant, mention the specific conversation or interaction where you encountered the issue. This context can help the developers understand the situation better and investigate the problem more effectively.
Offer suggestions: If you have any suggestions for alternative ways you would prefer to be addressed or any other improvements that could be made, feel free to share them. Providing constructive suggestions can assist the developers in making changes that align better with your preferences and make the AI system more user-friendly.
Use the appropriate feedback channels: AI systems often provide designated feedback channels, such as contact forms, email addresses, or support forums. Use these channels to communicate your feedback directly to the developers or administrators. If you're uncertain about the available options, check the AI system's documentation or website for guidance on how to provide feedback.
Remember, your feedback can contribute to improving AI systems and ensuring they address users in a respectful and appropriate manner. By expressing your concerns, you can help shape the system to better align with your preferences and create a more inclusive and comfortable user experience.
AI Feedback: Making Systems More User-friendly
AI systems are designed to enhance user experiences and make processes more efficient. However, like any system, they can have flaws. If a user feels uncomfortable with how they're being addressed, they have every right to voice their concerns. Just like Alex, users can provide constructive feedback, which helps developers refine AI systems and make them more user-friendly.
When discomfort arises from AI interactions, expressing these feelings is crucial. Not only does this lead to a more comfortable experience for the user, but it can also help the system learn and evolve, enhancing the experiences of future users. It's a part of responsible AI usage and fosters an environment where both the AI system and the user can learn and grow together.
ChatGPT Prompt — What if a user is reluctant to provide feedback?
Reluctance to provide feedback is understandable. Users might feel that their feedback won't matter, or they might feel uncomfortable articulating their feelings. However, as we've seen in the case of Alex, every feedback is valuable. It can lead to real change and ensure that the AI system better aligns with users' comfort and needs.
If you're feeling reluctant to provide feedback, remember:
Your comfort matters: You have the right to feel comfortable while interacting with AI systems. If something doesn't sit right with you, it's important to communicate that.
Your feedback can lead to change: Developers actively seek user feedback because they understand its value. Your feedback can prompt improvements that enhance your experience and that of future users.
Your voice is important: Even if you feel your concerns are minor, they are important. Every user's experience is unique and offers a different perspective that can help improve the system.
Therefore, don't hesitate to provide feedback if you're unsure or uncomfortable about something while interacting with an AI system. Just as Alex's feedback led to improvements in the AI system, your input can do the same.
To conclude, the coexistence of AI and humans in the digital space necessitates an open dialogue for constant improvement. User feedback is not only helpful but essential in this process. It helps AI developers make their systems more effective, respectful, personalized, and inclusive.
As an AI user, remember that your voice can help shape these digital interactions, making them more comfortable and user-friendly. Just as Alex found his voice and influenced change, so can you. Therefore, don't be bashful. Speak up and provide AI feedback. It can truly make a difference.
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