ChatGPT is a lot of things. It is by all accounts quite powerful, especially with engineering questions. It does many things well, such as engineering prompts or stylistic requests. Some other things, not so much. Twitter is of course full of examples of things it does both well and poorly.

One of the things it attempts to do to be ‘safe.’ It does this by refusing to answer questions that call upon it to do or help you do something illegal or otherwise outside its bounds. Makes sense.

As is the default with such things, those safeguards were broken through almost immediately. By the end of the day, several prompt engineering methods had been found.

No one else seems to yet have gathered them together, so here you go. Note...

The goal of this post is mainly to increase the exposure of the AI alignment community to Active Inference theory, which seems to be highly relevant to the problem but is seldom mentioned on the forum.

This post links to a freely available book about Active Inference, published this year. For alignment researchers, the most relevant chapters will be 1, 3, and 10.

Active Inference as a formalisation of instrumental convergence

Active Inference is a theory describing the behaviour of agents that want to counteract surprising, “entropic” hits from the environment via accurate prediction and/or placing themselves in a predictable (and preferred) environment.

Active Inference agents update their beliefs in response to observations (y), update the parameters and shapes of their models Q and P (which can be seen as a...

I recently watched Squid Game—both the original Netflix series and MrBeast's real life version. Then I watched every video I could find about how MrBeast's Squid Game was made. I was surprised to learn that MrBeast used a whole bunch of CGI (computer-generated imagery). I had taken its realty at face value.

There are four places I know of where MrBeast used CGI.

• The sky above the big dirt field wasn't originally sky. The scenes were actually filmed in an indoor stadium.
• The smoke effects of players who got eliminated were added in post-production.
• A dust effect where a woman fell was CGI.
• The big platforms for Tug-of-War and Glass Bridge weren't real at all. Both events took place close to the ground. In those scenes, almost everything the players didn't physically

(Note: This post is a write-up by Rob of a point Eliezer wanted to broadcast. Nate helped with the editing, and endorses the post’s main points.)

Eliezer Yudkowsky and Nate Soares (my co-workers) want to broadcast strong support for OpenAI’s recent decision to release a blog post ("Our approach to alignment research") that states their current plan as an organization.

Although Eliezer and Nate disagree with OpenAI's proposed approach — a variant of "use relatively unaligned AI to align AI" — they view it as very important that OpenAI has a plan and has said what it is.

We want to challenge Anthropic and DeepMind, the other major AGI organizations with a stated concern for existential risk, to do the same: come up with a plan (possibly a branching one, if there...

I wanted to ask ChatGPT how to optimize a few normal routines. One of my questions was about how to brush teeth. My conversation with ChatGPT:

What's the best way to brush teeth?

The best way to brush teeth is to use a soft-bristled toothbrush and fluoride toothpaste. To brush your teeth effectively, follow these steps:

1. Wet your toothbrush and apply a small amount of toothpaste to the bristles.
2. Place the toothbrush at a 45-degree angle against the gums and move the brush back and forth in a gentle circular motion to clean the teeth and gums.
3. Brush the outer surfaces of all of your teeth, using the same back-and-forth motion.
4. Use the tip of the toothbrush to clean the inside surfaces of the front teeth, using a gentle up-and-down motion.
5. To clean the

Bets and bonds are tools for handling different epistemic states and levels of trust. Which makes them a great fit for negotiating with small children!

A few weeks ago Anna (4y) wanted to play with some packing material. It looked very messy to me, I didn't expect she would clean it up, and I didn't want to fight with her about cleaning it up. I considered saying no, but after thinking about how things like this are handled in the real world I had an idea. If you want to do a hazardous activity, and we think you might go bankrupt and not clean up, we make you post a bond. This money is held in escrow to fund the cleanup if you disappear. I explained how this worked, and she went...

Definition. On how I use words, values are decision-influences (also known as shards). “I value doing well at school” is a short sentence for “in a range of contexts, there exists an influence on my decision-making which upweights actions and plans that lead to e.g. learning and good grades and honor among my classmates.” 

Summaries of key points:

1. Nonrobust decision-influences can be OK. A candy-shard contextually influences decision-making. Many policies lead to acquiring lots of candy; the decision-influences don't have to be "globally robust" or "perfect."
2. Values steer optimization; they are not optimized against. The value shards aren't getting optimized hard. The value shards are the things which optimize hard, by wielding the rest of the agent's cognition (e.g. the world model, the general-purpose planning API). 
   
   Since values are not the