Vastly oversimplifying: They’re not intelligent, they’re pattern matchers - when you give them “tricks” they find the best match in their training set, but if you’re the least bit creative you’ll just get matches to other similar tricks which usually are different.
Put another way: I have a couple of hand saws, I can cut limbs with them, even cut down whole trees, but a chainsaw is faster. Just because a chainsaw can also cut off my leg doesn’t mean it’s an uncontrollable dangerous evil tool, it means you need to be more careful with it than a handsaw. It also means something that would be 20 minutes of exhausting saw work can be done in 20 seconds (or less) with a properly setup chainsaw.
The important distinction is “trained to believe” versus “configured to answer as though it believes.” A model doesn’t necessarily have a private belief system. You can make two instances of essentially the same underlying model produce substantially different answers by changing their instructions, training data, reward criteria, or information sources.
For example, you could create three AI systems and give all three the question:
“Should the government provide universal healthcare?”
One could be optimized around libertarian principles, another around social-democratic principles, and another instructed to provide a politically neutral analysis. They could all know essentially the same facts while reaching different conclusions because they’re being asked to evaluate those facts using different frameworks.
There is also a more subtle issue: belief-curated AI doesn’t have to contain obvious propaganda. Selection of which facts to emphasize, which uncertainties to mention, which counterarguments to steelman, and even what questions it considers relevant can systematically push users toward a particular worldview.
The models I have worked with have user configurable base instructions, so you can “train” your AI to answer like Ghandi crossed with Martin Luther King, or to channel MechaHitler.
Vastly oversimplifying: They’re not intelligent, they’re pattern matchers - when you give them “tricks” they find the best match in their training set, but if you’re the least bit creative you’ll just get matches to other similar tricks which usually are different.
Put another way: I have a couple of hand saws, I can cut limbs with them, even cut down whole trees, but a chainsaw is faster. Just because a chainsaw can also cut off my leg doesn’t mean it’s an uncontrollable dangerous evil tool, it means you need to be more careful with it than a handsaw. It also means something that would be 20 minutes of exhausting saw work can be done in 20 seconds (or less) with a properly setup chainsaw.
Took this from ChatGPT when I asked it about it
The important distinction is “trained to believe” versus “configured to answer as though it believes.” A model doesn’t necessarily have a private belief system. You can make two instances of essentially the same underlying model produce substantially different answers by changing their instructions, training data, reward criteria, or information sources.
For example, you could create three AI systems and give all three the question:
“Should the government provide universal healthcare?”
One could be optimized around libertarian principles, another around social-democratic principles, and another instructed to provide a politically neutral analysis. They could all know essentially the same facts while reaching different conclusions because they’re being asked to evaluate those facts using different frameworks.
There is also a more subtle issue: belief-curated AI doesn’t have to contain obvious propaganda. Selection of which facts to emphasize, which uncertainties to mention, which counterarguments to steelman, and even what questions it considers relevant can systematically push users toward a particular worldview.
The models I have worked with have user configurable base instructions, so you can “train” your AI to answer like Ghandi crossed with Martin Luther King, or to channel MechaHitler.