Generative AI Learned Nothing From Web 2.0


It’s interesting to hear about the impact of generative AI on government regulations. As an AI language model, I don’t have real-time information, but new technologies need to be scrutinized and regulated to ensure ethical and responsible use. If you have any specific questions about generative AI or its implications, feel free to ask and I can provide information based on my training data.


The rapid development of generative AI has brought with it a host of familiar problems that have plagued social platforms for years. Issues such as misinformation, unethical labor practices, and nonconsensual content have proven difficult to address, and now these problems are manifesting in new ways with the use of AI technology.

OpenAI and its competitors are in a race to release new AI models, but they are encountering the same challenges that have plagued social platforms for nearly two decades. Despite the efforts of companies like Meta, these issues have persisted and are now resurfacing with the introduction of generative AI.

The novelty and speed of generative AI may be groundbreaking, but they also bring with them a host of familiar problems that have proven difficult to solve. As AI technology continues to advance, it will be crucial for companies to address these issues and ensure that the unintended consequences of their technology are effectively managed.


Farid’s statement highlights the idea that the challenges faced by OpenAI and similar organizations in the field of artificial intelligence were not unexpected and could have been avoided with proper foresight and planning. This suggests that there is a need for more careful consideration of potential issues and risks in the development and deployment of AI technologies.

Well-Trodden Path


Generative AI companies then leverage this existing infrastructure by using the labeled data produced by these content moderation workers to train their AI models. This raises ethical concerns about the exploitation of these workers, as well as the potential for biased or harmful content to be perpetuated through AI systems.

Additionally, the reliance on such infrastructure can perpetuate existing power imbalances, as the data used to train AI models may reflect the biases and perspectives of those who have the resources and authority to label and moderate content.

As generative AI continues to evolve and play a larger role in shaping online content, companies need to consider the ethical implications of their data sources and work towards more equitable and responsible practices. This may involve reevaluating the reliance on outsourced content moderation and ensuring that the voices and perspectives of marginalized communities are represented in the training data.

AI models working conditions and pay

This outsourcing of workforce for training generative AI models raises concerns about the working conditions and pay for these workers. It also creates challenges for researchers and regulators to understand the full scope of how AI systems and social networks are being developed and managed.

The use of outsourced workers for training AI models can result in low pay and difficult working conditions, similar to the issues faced by content moderators. This raises ethical and moral concerns about the treatment of these workers, especially as they play a crucial role in the development of AI technology.

Furthermore, the outsourcing of these functions to other countries puts them at a distance from the headquarters of the social platform or AI company. This makes it challenging for researchers and regulators full visibility and understanding of how these systems are being built and governed.

Overall, the use of outsourced workers for training AI models highlights the need for greater transparency and accountability in the development and management of AI technology. It also raises important questions about the treatment of workers in this industry and the potential impact on the quality and ethics of AI systems.

Comparison highlights

This obscurity can lead to a lack of transparency and accountability in the use of AI and outsourcing. It can also create confusion about who is ultimately responsible for the decisions and actions taken by these technologies. Additionally, it can make it difficult to assess the true capabilities and limitations of AI, as well as the impact of outsourcing on the quality and reliability of the products and services being offered. Overall, while outsourcing and AI can bring many benefits, it’s important to be mindful of the potential downsides and to ensure that there is clear communication and understanding about the roles and responsibilities of all parties involved.

This comparison highlights the challenges in regulating and controlling the unintended consequences of AI and social platforms. Despite the implementation of safeguards and policies, both AI models and social platforms continue to face issues with users finding ways to bypass these measures. This suggests a need for more robust and effective strategies to address the negative impacts of AI and social platforms, as well as better enforcement of rules and policies. It also underscores the importance of ongoing evaluation and adaptation of these measures to keep pace with evolving technologies and user behaviors.

Google’s Bard chatbot

It’s concerning to hear about the issues with Google’s Bard chatbot. The ability to generate misinformation about critical topics such as COVID-19 and the war in Ukraine is a serious problem, especially considering the potential impact on public understanding and decision-making. It’s essential for companies developing AI systems to prioritize accuracy and responsible information dissemination. Hopefully, Google will take swift and effective action to address these issues and ensure the chatbot’s outputs are reliable and trustworthy.


Additionally, the rapid advancement of technology and the increasing sophistication of chatbots and AI systems make it difficult to stay ahead of potential misuse and abuse. chatbots become more capable of engaging in natural and convincing conversations, the potential for them to spread misinformation, engage in harmful behavior, or manipulate individuals also increases.

Furthermore, the ethical considerations surrounding the use of chatbots and AI in general are complex and multifaceted. Questions about privacy, consent, and the potential for bias and discrimination in AI systems must be carefully considered and addressed.

Ultimately, while chatbot providers may strive to make their creations reliable and ethical, the challenges and potential risks associated with this technology are significant. It will require ongoing effort, collaboration, and innovation to ensure that chatbots are used responsibly and in ways that benefit society as a whole.

Faker Than Ever


This has the potential to further erode trust in media and public figures, as it becomes increasingly difficult to discern what is real and what is manipulated. It also raises serious ethical and legal concerns about the use of AI to create false information and the potential for it to be used for malicious purposes, such as spreading propaganda or manipulating public opinion.

As generative AI technology continues to advance, it will be important for individuals, media outlets, and tech companies to develop and implement strategies to detect and combat the spread of disinformation created by AI. This may involve the development of new verification tools, increased transparency around the use of AI-generated content, and stronger regulations to prevent the misuse of this technology.

Ultimately, the widespread use of generative AI to create false information has the potential to undermine the very fabric of our society, and it will be crucial for us to address this issue proactively to protect the integrity of our information ecosystem.

Farid’s statement highlights

Farid’s statement highlights the damaging impact of generative AI on the spread of misinformation and disinformation. The technology allows for the rapid creation of false content, making it easier for individuals to manipulate public opinion and undermine the credibility of genuine information.

The comparison to Donald Trump’s use of the term “fake news” to discredit unfavorable media coverage further emphasizes the dangerous potential for generative AI use as a tool for political manipulation and deception. Additionally, the example of the Indian politician falsely claiming that incriminating audio is fake demonstrates how this technology can be exploited to deny accountability and sow doubt in the public’s perception of truth.

Overall, Farid’s assertion underscores the urgent need for measures to address the proliferation of misinformation facilitated by generative AI, as well as the importance of promoting media literacy and critical thinking to combat its detrimental effects on public discourse and trust in information.

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