If the AI is capable of dealing with open world problems, then it is likely also capable of stopping when in doubt and clarifying/exploring instead of pushing ahead in a particular direction. Open world problem solving is highly collaborative: without that skill of collaboration, it won't be able be a good problem solver. That collaborat…
If the AI is capable of dealing with open world problems, then it is likely also capable of stopping when in doubt and clarifying/exploring instead of pushing ahead in a particular direction. Open world problem solving is highly collaborative: without that skill of collaboration, it won't be able be a good problem solver. That collaboration which will make the AI a good problem solver, will also give us control to steer it.
There is one scenario I think of where we might have less control: if we use genetic style algorithms with random mutations to guide development of its "motivation circuits". But then it will be a choice we would have made when setting the system, and not something accidental. Also, such approaches will be very inefficient compute wise.
If the AI is capable of dealing with open world problems, then it is likely also capable of stopping when in doubt and clarifying/exploring instead of pushing ahead in a particular direction. Open world problem solving is highly collaborative: without that skill of collaboration, it won't be able be a good problem solver. That collaboration which will make the AI a good problem solver, will also give us control to steer it.
There is one scenario I think of where we might have less control: if we use genetic style algorithms with random mutations to guide development of its "motivation circuits". But then it will be a choice we would have made when setting the system, and not something accidental. Also, such approaches will be very inefficient compute wise.