Artificial intelligences are prediction machines. They can tell you the probability it will rain today, but they cannot tell you whether or not you should pack an umbrella. That’s because the umbrella decision requires more than just prediction — if the probability of rain is 10%, some people will choose to carry an umbrella, but others won’t. Why will different people behave differently even though they are faced with the same information? Because they have different preferences. In this case, some people care much more than others about getting wet. Only you or someone who knows you well can judge the costs and benefits of carrying an umbrella. Making that decision for you requires both a prediction and a judgment based on your preferences.
How Large Language Models Reflect Human Judgment
OpenAI used a simple form of human feedback.
June 12, 2023
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Summary.
Artificial intelligence is based around prediction. But decision making requires both prediction and judgment. That leaves a role for humans, in providing the judgment about which types of outcomes are better and worse. But large language models represent a key advance: OpenAI has found a way to teach its AI human judgment by using a simple form of human feedback, through chat. That opens the door to a new way for humans to work with AI, essentially talking to them about which outcomes are better or worse for any given type of decision.