Chat GPT: Trust but verify

You've probably heard about the latest breakthrough in LLM from OpenAI, the company behind ChatGPT.

ChatGPT presents itself as a tool for translation, information retrieval, and creative writing, but it's capable of so much more. In fact, it's already making waves in academia and the tech industry, with recent reports of it passing law school exams and even Google's code interview. It's exciting to see the advances in AI, but it's also important to consider the implications for privacy, security, and bias.

One of the well-known limitations of ChatGPT is its tendency to provide incorrect information and carry implicit biases. For example, if you ask it to summarize a show, it may mix up character names or leave out important details. This bias problem is not unique to ChatGPT, as we've seen in the past with Microsoft's Tay chatbot.

Privacy is another concern with the use of LLMs such as ChatGPT, especially with regard to data protection laws. When user input is used to train the model, the inputs become part of the model, which can be difficult to delete. Even if the data is not used for training purposes, the processing of sensitive information by ChatGPT could still violate privacy laws.

Another concern is the risk of model attacks, exploits, and vulnerabilities. For example, a language model trained on a large amount of data could potentially store and leak sensitive information, such as credit card numbers. Additionally, as applications are developed using ChatGPT, there is a risk that users will break out of the limited context and use the model for malicious purposes, such as making malicious backend queries.

It's also worth noting that ChatGPT is not the only player in the game. There are other language models, such as Google's Bard and Meta's OPT-175B, that are also making progress in this area. While ChatGPT is currently the most powerful publicly available model, it's important to keep in mind the potential risks and biases associated with its use.

conclusion

ChatGPT offers many exciting possibilities for making information more accessible and helping people generate ideas and build software more effectively. However, it's critical to address the security, privacy, and bias concerns associated with LLMs. By understanding and openly discussing these implications, we can harness the benefits of AI while mitigating its risks.