Why not? I can think of a couple possible explanations, but none that hold up to scrutiny. I’m probably missing something.
This isn’t directly related to engineering, but consider the narrow domain of medicine. You have human doctors, who go to medical school, see patients one at a time, and so on.
Then you have something like Doctor Watson, one of IBM’s goals for the technology they showcased in the Jeopardy match. By processing human speech and test data, it could diagnose diseases on comparable timescales as human doctors, but have the benefit of seeing every patient in the country / world. With access to that much data, it could gain experience far more quickly, and know what to look for to find rare cases. (Indeed, it would probably notice many connections and correlations current doctors miss.)
The algorithms Watson uses wouldn’t be useful for a human doctor- the things they learned in medical school would be more appropriate for them. The benefits Watson has- the ability to accrue experience at a far faster rate, and the ability to interact with its memory on a far more sophisticated level- aren’t really things humans can learn.
In creative fields, it seems likely that human/tool hybrids will outperform tools alone, and that’s the interesting case for intelligence explosion. (Algorithmic music generation seems to generally be paired with a human curator who chooses the more interesting bits to save.) Many fields are not creative fields, though.
This isn’t directly related to engineering, but consider the narrow domain of medicine. You have human doctors, who go to medical school, see patients one at a time, and so on.
Then you have something like Doctor Watson, one of IBM’s goals for the technology they showcased in the Jeopardy match. By processing human speech and test data, it could diagnose diseases on comparable timescales as human doctors, but have the benefit of seeing every patient in the country / world. With access to that much data, it could gain experience far more quickly, and know what to look for to find rare cases. (Indeed, it would probably notice many connections and correlations current doctors miss.)
The algorithms Watson uses wouldn’t be useful for a human doctor- the things they learned in medical school would be more appropriate for them. The benefits Watson has- the ability to accrue experience at a far faster rate, and the ability to interact with its memory on a far more sophisticated level- aren’t really things humans can learn.
In creative fields, it seems likely that human/tool hybrids will outperform tools alone, and that’s the interesting case for intelligence explosion. (Algorithmic music generation seems to generally be paired with a human curator who chooses the more interesting bits to save.) Many fields are not creative fields, though.