(11-13-2016, 01:46 AM)Drashner1 Wrote: Having worked with doctors in a couple of past portions of my career, I'm not really of a mind that they are all that much smarter (or any smarter at all really) than anyone else. At least if we define 'smarter' as 'general problem solving ability'.
A doctor may be able to perform complex surgeries spectacularly well - and be totally helpless when it comes to changing the oil on their car. Or bad at relationships. Or barely able to balance their checkbook.
The same often applies for pretty much any other profession that we tend to culturally associate with 'superior intelligence'. Humans are often especially good in one or more areas but not so good in others.
There is also the impact of things like education, experience, and general interest or personality, all of which can impact how good someone is at something (and how bad they are at other things).
(Note: left laptop at work this weekend so laboriously typing on iPad )
Broadly agreed. As someone who works in a field stereotyped for intelligence (nanomedical PhD) I think the term as a general trait is often not appropriate. Plenty of intelligent activities are very formulaic and could be performed well by anyone with the background knowledge and dedication. This isn't always true, some people are better at spotting patterns and experiencing useful incubation (I.e. answer popping into ones head) but presumably that is the result of biology and learned behaviour, it's just harder to study and replicate as its unconscious.
Jumping off from that we have a clear target for intelligence amplification. Any system, be it a smartphone or neural implant, that can provide instant answers and protocols resembles high intelligence:
Early setting example
Alice frowned at the blank screen on the agribot's flank. The machine was supposed to have weeded the field that morning but had frozen only an hour into the job. Alice's mother was the farm's engineer and could probably fix the bot in no time, but she was out of town for a conference all week. Not wanting to call customer services and deal with their overpriced and overly-friendly chatbots Alice resolved to fix the agribot herself. Slipping on her iShades she logged on to HowToDo.com and uploaded the agribot's specifications. A few minutes later a protocol file landed in her inbox. Opening it caused several new icons to appear in Alice's visual field, some hovered in front of her whilst the rest clustered around the agribot. The largest was the first node in a complex flowchart helping her to diagnose the problem. As the hours passed Alice toiled over the bot; info glyphs explaining the esoteric components of the machine and showing animations of how to check and fix them. Working through the protocol tree Alice eventually smiled in triumph as the agribot burst to life. As the glyphs faded around her she stood and watched the bot trundle along the field, fully operational and back on track thanks to her.
Late setting example
As he walked through the grounds, near bored to tears, a patch of rusty brown amongst the flowers caught Bob's attention. Curious he approached until he was looking down upon the aberration. Long, spindly threads of some earthy material had grown all over the blue roses. He searched his mind trying to recall if he'd ever seen anything like it during his long sojourn on the estate. He drew a blank, quite literally. His natural thoughts flickered through irrelevant connections and his exoself memoir-sense was silent. Drawing closer he began to mutter to himself; "What's this then...weird shape, striated? Yes striated. Funny angles where the threads meet, maybe fifty or sixty degrees all of them. Ah no, fifty-seven point two precisely. Not a fungi...no not biological at all but technological." If Bob cared enough about the source of his conclusions his exoself would have induced a synthetic feeling alongside the answers it was feeding his subconscious. As it was he didn't and so was blissfully ignorant that his thought process was being nudged towards a rational optimum, as well as being supplemented with micro-knowledge downloads. Rapt now Bob was convinced the growth was a mutant strain of soil nanomycelium. There was some self-awareness that he had never studied nanoengineering or horticulture, but Bob was now fascinated by both topics. As a bench extruded under him he spent the rest of the day thinking and learning; half formed questions in his mind were nipped in the bud by didactic snippets merging with his concept map. Scenes of molecules danced in his Cartesian theatre as he contemplated metabolic pathways of diamondoid-based replicators. As evening drew Bob finalised an antibot to deal with the mutant strain (a simple fix for the simple sabotage committed by the groundskeepers). Returning to the house Bob smiled; his schedule was going to have to be rearranged around his new hobby, he looked forward to a long period of doing little besides remembering knowledge for the first time.
*
Argh that all took far too long to type. The takeaway message from the examples is that at the low end IA can be like following a recipe for problem solving. A recipe that is presented in a way that is easy to follow, customised for the user and interactive (e.g. The protocol could say "Check the right Flanginator" and Alice could respond "where is that, what does it do, how does it work?" And the protocol will teach her). At the high end the individual feels like they are solving the problem using their own knowledge, even if they have no prior skills or experience. What's really happening is that a problem-solving and teaching program are monitoring the effort from the exoself and when they predict/detect a sub-optimum/erroneous train of thought or a gap in knowledge they shunt the correction into the user's mind.
Innate IA like genemods likely work by a) making artificial aides unnecessary and B) making the use of even better aides safer and easier. A homo superior doesn't need a user friendly, simplified how-to. Their brains were optimised for speed learning at breakneck pace in communication formats too complex for baselines. They also don't need "low" level IA-scripts to manipulate their thoughts, their high neural plasticity means their brain will grow a perfectly suited neural network to solve the types of problems they are facing. Exoself IA for superiors is going to be more quantitative than qualitative, adding raw processing power and a software hierarchy that their brilliant minds can direct from an executive position.
OA Wish list:
- DNI
- Internal medical system
- A dormbot, because domestic chores suck!