One of the key findings of the work is that claims about AI having a "value system" similar to human preferences may be exaggerated. AI does not possess stable or consistent values, as is often assumed in theoretical models.
The authors of the study argue that AI adaptation—i.e., ensuring the correct and reliable operation of models—is a process far more complex than expected. AI can suffer from issues such as hallucinations (incorrect or absurd conclusions) or mimicry, which leads to unpredictability and makes it harder to manage. These problems make AI behavior much less stable and controllable than many assume.
What’s particularly important is that the study highlights the difficulty of establishing universal principles for AI. When researchers try to draw general conclusions based on limited experiments, they may face issues with extrapolation and the creation of universal solutions. This means that simply applying theories or establishing "values" for AI based on current models can lead to incorrect or dangerous consequences.
Thus, rather than assuming AI has a "value system," the MIT study emphasizes the importance of a more careful and realistic approach to its development and management, given its current limitations and potential for unexpected behavior.