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Artificial U nintelligence

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Summary

This article discusses the implications of releasing AI models without restrictions, highlighting the tension between offering users as much freedom as possible without assuming liability for when things go wrong. It compares this situation to content moderation in social media, where content close to the moderation line generates more engagement. The article suggests ways to distribute risk such as open-sourcing the model, creating a third-party ecosystem of apps based on the model, and vetting it thoroughly. It points out that while the people building these models are generally ethical, the incentives are such that those willing to open things up faster and with less restrictions will win an advantage.

Q&As

What is the role of risk in the development of AI models?
The role of risk in the development of AI models is to mitigate business (and societal) risk.

How has ChatGPT's popularity impacted its limitations?
ChatGPT's popularity has led to the need to limit what it says in order to avoid PR blowback, harm to users, or create massive legal risk for OpenAI.

What is the “Content Darwinism” theory?
The Content Darwinism theory is that the closer a piece of content is to the moderation line, the more engagement it generates.

How can risk be distributed with AI models?
Risk can be distributed with AI models by open sourcing the model and allowing people to run it on their own computers, or by having a thriving 3rd party ecosystem of apps based on the model.

What strategies have businesses used to succeed during recession?
Strategies businesses have used to succeed during recession include cutting costs, diversifying revenue streams, investing in digital transformation, and focusing on customer experience.

AI Comments

👍 This article was very informative and thought-provoking! It was great to see the discussion on the risk trade-offs involved in AI models.

👎 The article was overly technical and hard to follow at times.

AI Discussion

Me: It's about Artificial Intelligence and how the limitations aren't always about what the technology is capable of, but instead are self-imposed so that companies can mitigate business and societal risk. It talks about how companies have to balance risk and reward, and how the companies that take on risk can benefit from it.

Friend: Interesting. What are the implications of this article?

Me: One of the key implications is that companies will have to be more aware of the risks involved in developing and deploying AI models, and weigh those risks against the potential rewards. Companies might need to be more open to taking on risk in order to stay competitive, and they should also consider how to distribute risk among third-party developers in order to maximize their potential advantages. Additionally, companies may need to be more careful with the content that they allow on their platforms, as content that is close to the moderation line may generate more engagement, but also more risk.

Action items

Research the implications of AI models returning risky results and the potential legal and moral risks associated with them.
Explore ways to distribute the risk associated with AI models, such as open sourcing the model or creating a thriving third-party ecosystem of apps based on the model.
Consider the implications of content moderation double-bind theory and how it affects the development of AI models.

Technical terms

AI (Artificial Intelligence): Artificial intelligence (AI) is a branch of computer science that focuses on creating intelligent machines that can think and act like humans.
GPT-3 (Generative Pre-trained Transformer 3): GPT-3 is a natural language processing (NLP) model developed by OpenAI. It is a large-scale language model that uses deep learning to generate human-like text.
ChatGPT: ChatGPT is an open-source chatbot powered by GPT-3. It is designed to generate natural language responses to user queries.
Stable Diffusion: Stable Diffusion is an open-source public access version of GPT-3's technology. It allows users to generate images with no restrictions.
Content Moderation Double-Bind Theory: Content Moderation Double-Bind Theory is a theory proposed by Evan that states that social media companies have policies that limit what can be said on their platform. The closer a piece of content is to the moderation line, the more engagement it generates.