It is clear that Another ethical issue is that by loading “sensitive” information about a company into an AI, the developers of that AI will iran whatsapp number data have access to it. And then they will be free to use it as they wish – keep in mind that everything you input may be publicly available.
So, don’t share sensitive data without permission. It’s important to make sure that the data used to train a generative AI model is obtained legally and with the consent of the other party, and that it doesn’t violate laws and regulations. Most publicly available generative AI services (like ChatGPT) don’t disclose what datasets they train on. So we don’t know who actually owns the output.
Always think about privacy when feeding data to AI
This also means that we cannot verify the extent to which the output is biased. AI bias is a real problem. Models learn stereotypes from training data. They are capable of creating extremely convincing lies. Never trust AI-generated content as your only source of information, especially when it comes to scientific research.
Problems with AI are easy to spot. Content created entirely by a neural network is often quite mediocre:
- long and complex paragraphs, copied pieces;
- awkward formal cliches and long sentence structures;
- adjective overload;
- facts based on someone’s subjective opinion.Text from a neural network is easy to identify – long structures in sentences and overload of adjectives
Code of Ethics for the Use of Artificial Intelligence
It is recommended to use removal of the old annual declaration of a deputy from the register and submission of a corrected one generative AI with a license issued by the company. This is important from the point of view of liability and property rights. But even in this case, you should not completely copy the content or code from the neural network. Always edit, change and supplement the material to achieve uniqueness of the content.
- Data reliability is paramount . You shouldn’t blindly trust everything that a neural network produces, as the accuracy of this information is quite questionable, especially on topics that change quickly.
- Never copy the entire output of a neural network . You can generate content, but always remember to improve the result to get a truly new idea.
- AI is great for quick, shallow research on topics or testing ideas . Don’t use it to prove your ideas.
- Most information is “sensitive” content . Anything you feed the neural network as input can become available to competitors or current and potential customers.
- Never share any personal data with AI tools like ChatGPT . This includes your customers’ personal data – names, email addresses, phone numbers, and anything else that is considered personally identifiable information.
Using neural networks: benefits and harms
It is up to you to decide what ethical principles to cn leads adhere to and what standards your company operates by. However, asking a neural network to generate content from scratch is not the answer.
Find as much information on the topic as you can on your own. Read videos, documents, blogs, drafts, etc. and combine them to create a solid information base. Then write a few sections yourself and ask the AI to expand on the rest of the content. Align the entire text with a consistent style and add relevant examples and keywords.
The examples below will help you understand the difference between good and bad use of AI.