AI Raises Questions About Itself

I am a newbie to ChatGPT, but signed up for the 4.0 version. I submitted the following post without any guidance or request. The response follows.

Then I respond to the response with additional notes and questions. That response also follows.

I think the exchange speaks for itself.

My Post

Whoa! Has the content creation and publication game ever become confusing?

AI being added to search and formatting the results into conversational answers in alternative formats is exciting.?

Aren't these answers built on the backs of millions of unpaid/uncredited content creators/posters providing virtually endless content to drive the answer (or at least until 2021 with CGPT 4.0)?

Won't this elevate protected, professionally created content housed behind a firewall?

Anyone who has experimented with several AI engines has seen some challenges with accuracy and formatting. No surprise.?

I suspect the scientists will work out the configuration,?but what about the precision??

Chat GPT Reply

Your questions touch on a range of important issues related to the role of AI in content creation and publication. Let's address each one in turn.

Firstly, it's true that AI models like ChatGPT are trained on vast amounts of data from the internet. They learn patterns and structures from these data to generate responses. This raises ethical questions about attribution and compensation. However, it's important to note that these models don't know specifics about which documents were in their training set or who wrote them. They don't access or retrieve documents or specific sources of data; they generate responses based on patterns they've learned.

As for the potential elevation of protected content, there could indeed be a shift in the value proposition. If AI continues to improve in its ability to generate content, it may become increasingly important for creators to offer something unique or specialized. Professional content housed behind paywalls may become more valuable if it offers insights, depth, or quality that AI can't replicate.

Accuracy and precision are indeed ongoing challenges with AI. While AI can generate plausible-sounding responses, it can also make mistakes, including factual inaccuracies, misunderstandings of context, or inappropriate responses. This is a major focus of ongoing research.

Continual learning — the process of updating AI models based on new data — is a promising but challenging area of research. As of my last update in 2021, models like ChatGPT do not learn from the conversations they have after being trained. They generate responses based on their training and do not update their knowledge based on new information. If future models are able to continually learn from new data, this could help improve their accuracy and relevance.

However, this also raises additional questions about privacy and security, as it would mean that the AI is effectively remembering information from its interactions. It's a delicate balance to maintain.

In summary, the use of AI in content creation and publication presents exciting opportunities, but also raises important questions about attribution, value, accuracy, and privacy. It's a rapidly evolving field, and these are issues that researchers, developers, and policymakers will need to continue to address.

My reply to the above with comments (excerpted comments from above ChatGPT answer in italics - my comments in BOLD).

This raises ethical questions about attribution and compensation.

?I think this is the point and the key question I am asking.

However, it's important to note that these models don't know specifics about which documents were in their training set or who wrote them.

Doesn’t this further make my point that one will wonder how accurate/truthful the answer will be. And one must anticipate paid search morphing into ChatGPT that would create quite cunning answers lacking transparency into the fact they contain some paid content that informed the answer acquired from training.

Professional content housed behind paywalls may become more valuable if it offers insights, depth, or quality that AI can't replicate.

But how will they know? Won’t those paywalled creators use a version of ChatGPT in the creation of their own content? I think this is the worst-case Orwellian dystopia many fear. While I don’t think a dystopia is currently in focus, I think the concerns of who is a reliable source and understanding what makes it so is important. Further, as we saw during the pandemic, at crisis moments when accuracy is a potentially lifesaving factor, calling out misinformation becomes more important. How will people know, and many who potentially using this technology will not have critical thinking training and skills, what to believe. Delivering information in a “convincing” or “persuasive” tone is already pretty solid.

While AI can generate plausible-sounding responses, it can also make mistakes, including factual inaccuracies, misunderstandings of context, or inappropriate responses. This is a major focus of ongoing research.

You make my point. How would you characterize this type of research?

questions about privacy and security, as it would mean that the AI is effectively remembering information from its interactions. It's a delicate balance to maintain?

What are the specific questions about privacy and security? How would you characterize the balance?

also raises important questions about attribution, value, accuracy, and privacy.

I think the glow of the shiny new object has early users a bit bedazzled, but I think that without attribution and accuracy there will be a whole lot of stealing going on.

Chat GPT Reply

Your comments bring up very valid concerns, and I'll do my best to address each one in turn:

1. Ethical questions about attribution and compensation: You're correct that this is a key issue. However, it's a complex one. AI training data is typically anonymized and aggregated, and the AI doesn't know specifics about its sources. Therefore, it can't give attribution in a traditional sense. As for compensation, it's a tricky question, as the data used to train AIs often comes from public sources where users have freely posted their content. The current model of AI training may need to evolve to address these ethical considerations adequately.
2. Accuracy and transparency: The issue of accuracy is indeed a concern, and it's one of the main areas of focus for AI researchers. Transparency is a related issue. Ideally, AIs would be able to explain their reasoning and the sources of their information, but this is a challenging problem. As for the potential misuse of AI for promoting paid content without disclosure, that's more of a policy and regulation issue, and it's something that society as a whole will need to address.
3. Professional content and AI: The relationship between professional content creators and AI is likely to be complex and evolving. On one hand, AIs could potentially assist professional creators by providing them with information or helping them generate content. On the other hand, the rise of AI could increase the value of human-created content that offers a unique perspective or depth of understanding that AI can't replicate.
4. Reliability and critical thinking: This is an important point. The ability to critically evaluate information is crucial in a world where AI-generated content is common. Education and media literacy will be key. There may also be a role for technology solutions, such as systems that can verify the accuracy of information or detect AI-generated content.
5. Research into AI accuracy: This type of research involves both improving the AI's algorithms and training data, and developing techniques for evaluating and testing AI systems. It's a multidisciplinary field that incorporates elements of computer science, data science, linguistics, psychology, and other fields.
6. Privacy and security questions: When it comes to continual learning (AI systems learning from their interactions after training), privacy concerns arise because the system would need to retain information from those interactions. Security concerns could arise if that information is sensitive or could be misused. Balancing these considerations involves ensuring that privacy and security protections are built into the AI system, while also providing the system with the data it needs to learn and improve.
7. Attribution, value, accuracy, and privacy: These are indeed some of the key issues in the use of AI in content creation. As AI becomes more prevalent, it's important that these issues are addressed in a way that respects the rights of individuals and the value of human creativity. It's a challenging problem that will require ongoing efforts from researchers, policymakers, and society as a whole.