Just recently I was grocery shopping when I was told that I now have to enter my pin because I'm using MasterCard. I rather liked this because before I could just swipe for anything under $50 or so. I asked the cashier and they said MasterCard just recently started requiring that all payments must use the pin, but Visa and others have not yet required.
General intelligence tends to be on a bell curve, but specialized intelligence tends to be on a power curve. For any given specialty, 80% are below average. In certain types of problem domains, like high function abstract reasoning, you will see absurd differences in ability. You can see in the range of a 1,000,000x difference in the ability to learn something new between the median and the best. One person may literally take seconds and another person will spend a life-time never obtaining what they learned.
I've been bitten a few times by Reddit. I assume fly-by-night ads substituting an ad once it gets validated and popular. One of the times I was reading a discussion on reddit about an issue I was researching when some tab-under ad loaded freaking porn on my work computer while I was at work.
Not to mention that unbiased results are junk. The whole point of a search engine is to find biases that suggest that some information is what you're looking for. When I switch Chrome into incognito mode, Google search results are crap. They return me what's popular for the typical person, not popular for a person like me.
It's starting to come to light that about 30% of jobs are meaningless, in that they don't add to value or possibly add negative value via increased management overhead. The problem is capitalism seems to pervert "value" to mean "money". Prior to a few decades ago, nearly every job had value. Unemployment may be similar, but most of the "jobs" are just busy work. Assuming this is true, we may already be affected by automation.
I would argue if they aren't competent, they can't do the job.
Ideally, yes. The problem is they seemingly can do their job. Most people's competence are gauged by how quickly they can make a symptom go away, not how correctly they fix the root problem. Like a hospital that ranks doctors by how quickly they get through patients, and a doctor just hands out pain killers like candy. All they did is externalize the cost.
I do a lot of work with 3rd-parties and SSL. One of the issues that happens time and again is when I ask for the public key to install, they send me the private+public pair unencrypted via email and now I have their wild-star EV private cert that expires in 2 years. Just because someone can do the job doesn't mean they're competent.
There's a lot of diploma mills mass printing CS degrees and the general populace is grouping in decent schools with the trash. Even within good Uni/Schools, there are a lot of people getting degrees that shouldn't. There's a group of Ivy league CS professors that have been working with psychologist for over 20 years trying to figure out why so many people are so bad at programming in general, not just CS.
What they're currently seeing is 80% of student who apply fail in the first two semesters, 20% drop/fail for various reasons after the first two semesters, of the remaining 16%, 50% graduate only because of perseverance, not ability, and of the remaining 8%, they're on a power curve where 80% are below average. When taken as a whole, ~98% are below average. Does not seem to be a bell-curve at all.
They have done all kinds of experiments, sourcing ideas from all over the world from many CS or psychology professions, but nothing has worked. They can't seem to make it any easier. So far they have only found one predictor that seems highly correlated are predicting if the student will graduate and be good. Logical consistency. They have some tests that are very hypothetical and require using abstract reasoning to solve for a fictional problem. Think of an abstract reasoning test with pseudo-code instead of visual patterns. They look for two things in these tests, logical dissonance and repeat-ability of getting the same answer some many months later. Even if the reasoning is wrong, as long as it's consistent and does not contradict itself, they have a very high chance of being good at CS+programming.
The tests are "decent" at predicting if a student will probably be decent, but nearly perfect for predicting if they'll be a failure. Always easier to be the critic.
In "programming" few masters are experts and few experts are masters. In psychology, advanced knowledge and advanced reasoning are inversely related. You either know a lot and understand little or know little and understand a lot.
People with the strongest abstract reasoning skills have learned how to quickly forget. Turns out that the act of learning requires a lot of working memory. The more you know, the more clogged your working memory becomes because everything you see triggers a memory that keeps your working memory saturated. The less you remember, the faster you learn and the more complex ideas you can learn. Spatial memory uses a complete different part of your memory. You can remember a lot of abstract concepts without negatively affecting your working memory. If you focus on learning abstract concepts and not facts, you will learn faster.
Most people peak in abstract reasoning in their late teens and plummet in their 30s. This seems to be caused from lots of experience that causes the person to learn more. As the person learns more, their abstract reasoning gets used less and less while they continue to grow their knowledge and use their memory. At some point their abstract reasoning hits an inflection point veering down. People who do no focus on knowledge, but instead focus on understanding do not have this issue because they don't gain as much knowledge. They instead increase their abstract reasoning, which allows them to quickly learn new things and just as quickly forget them.
This is why experience is such a worthless metric in a problem domain that requires much abstract reasoning.
An expert is great for "solving" (remembering solutions) old problems, a master is great as solving new problems. Depending on what problems you have, choose wisely. Then you have the whole issue that in tech, specific knowledge has a half-life of 3-5 years. Worthless by the time you become an expert in it, unless you have a niche position for some legacy system.
People can be meta-conscious, but are not always. It's a skill not always exercised. Meta-cognition and abstract reasoning are highly correlated. The Dunning–Kruger effect is currently thought to be caused by a lack of abstract reasoning because one of the abilities of abstract reasoning is to know when you don't know something, which is also considered a highly meta-cognitive skill. Yet most people are highly affected by the Dunning–Kruger effect.
Most of the skills and abilities described by meta-cognition are extremely weak in most people. While they can have meta-cognition, they're not very good at it. On the other hand, people who claim to have lucid dreams are highly correlated with strong meta-cognitive abilities and abstract reasoning. There seems to be a positive linear correlation with lucid dreaming and frontal grey matter density in the part of the brain responsible for abstract reasoning. They three seem to go hand-in-hand with little deviation, but not causation as far as they can tell.
Changing the definition of conscious to mean what meta-consciousness means would make most people not very conscious, by deffinition.
psychologists have a decent understanding of what babies can and cannot understand
This does not include outliers. My abstract reasoning at the age of 6 was beyond what most adult programmers will ever peak at, yet "abstract reasoning does not start to develop until about age 11". Whatever. In my case, I was born with learning disability that forces me to use Abstract reasoning for nearly everything. The other parts of my brain don't work correctly. I actually have an inverse issues that I don't learn well from concrete examples, but I learn very well from abstract examples. This is the opposite of young children and it's always been this way for me.
My brother taught himself Algebra at the age of 9, and he didn't even have any Algebra books. He just got bored with Arithmetic and created a system of number manipulation to keep himself preoccupied. By the time he was a freshman, he was breezing through AP Calc and actually helping to teach the class. He completed the entire year of work in a few days while in class.
My mom was a middle child in a large family and had a lot of experience with young children, along with being the neighborhood baby sitter. She said that I almost never cried, even when only a few weeks old. Even after birth I was noticeably quieter. The doctor took note and thought I may have had some disability, but my mom noticed I like to make noises and shortly realized I made different noises for different wants. A simple example is when I wanted to feed, I would periodically make a sucking noise. If nothing happened in a short while , I would make a short whine+grunt to get attention, then make the sucking noise again. It wouldn't be until some fairly longer time later that I would actually start to cry like a normal child if I didn't get fed.
She always got asked about how she kept me so quiet. I also had a great propensity to keep myself preoccupied, rarely ever wanting attention or interaction from others.
My first sibling has a very strong personality the moment he was born. When the doctor/nurse, can't remember was handing them to my mother, the doctor did something and my brother let out a grunt that sounded like he was pissed off. It startled the person. My sibling was very impatient from those early moments. Made grunting sounds that quickly graduated into whining then crying. Made it very clear what they wanted the situation fixed. The crying shutoff like a light once they realized they were about to get what they wanted.
I know I experience suffering from pain, but I cannot show that other people experience suffering, only that they react. I assume that harming others would cause them to suffer and is therefore unethical without warrant. But that's the crux of this whole problem. How do we know if a computer is suffering? We can know it reacts, but cannot know if it's perceiving.
If my cat hears the key-chain jingle of the laser pointer, he'll come running from where ever he was hiding, look at my hand and figure out where it's pointing, then look in that direction for the dot. He knows my hand is the cause, but he doesn't care.
Your sarcasm fails and you failed to understand the logical implied nuances that made jimbolauski's post irreverent. Once you understand what he actually said and not take it at face value, then you'll understand my reply. Hint "You only feel 'fun' because your brain says something is fun. Nothing is really fun." Who the f*ck cares if it's all fake, I still experience it. In other words "I think, therefore I am"
The article talks about someone who could technically see, just not very well and was legally blind. I was talking about someone who had near zero optical neural stimulation.
We're nothing more than information in the space-time fabric that follows well defined algorithms either discretely or statistically. The entire Universe is just one massive computer and we just occupy a subset of space-time. You may want to learn about the abstractness of how our perception works. What you see as the color "red" is not a color but a concept that is not blue or green.
Red is defined as "not blue or green"
Green is defined as "not red of blue"
Blue is defined as "not red or green"
Welcome to how the brain works. Even concrete concepts are abstract at their core.
I should expand on what "familiar" means for pattern recognition. It's the pattern that I can most easily reason about. I visualize patterns. Think of it like an N dimensional "shape" of the sort. The more defined the shape is with the least about of mental effort, the more "familiar" it seems to me. I say this because the less effort I put into reasoning about something while coming to a "clear image", the more times I *must* have encountered the pattern. I assume reinforced neural path ways or something.
When I encounter a pattern that I am less familiar with, my thoughts branch all over the place. The more branching that occurs, the less reinforced the idea is. The more I encounter an idea, the more it gets reinforced into the way I naturally think.
There are man other aspects of meta-cognition that I need to use, but this is the most simplified explanation that captures the whole idea.
It gets really weird when I "remember" something that I never actually did. I've only been aware of this a few times, but one of them was when my reasoning changed for a certain problem domain and I started to "remember" a false implementation, but a better implementation. I only realized this after a few seconds of discussing with a co-worker. I noticed a lack of meta-memory about the thoughts and found it very strange. The ideas kept flowing as I normally create ideas in real-time, but I had nothing to associate with them. I realized I must have learned something new that changed the way I thought. Jumped into the code to actually look at what I did, and figured out what I learned that changed the way I thought. By remembering this small factoid of what changed the way I thought, I could consciously pretend to not be aware of that fact and re-create my prior logic again.
It takes great mental effort to ignore something that I should be aware of. Because I'm used to going with the flow of what's natural, I'm effectively creating cognitive dissonance and deviating from that flow. I eventually refactored the code with my new reasoning applied, not to make it "better" in any measurable way, but to make it easier for me to remember with my new way of thinking.
That's why you need to be meta-cognitive about your thoughts and memory. I actually have a learning disability that makes it extremely difficult to remember facts of any kind, but I can remember meta-facts just fine. Instead of remembering something directly, I remember by focusing on a fact while it's int my short-term memory and creating lots of meta-knowledge about the knowledge I want to remember. Then when it comes time to remember something, I use the meta-knowledge to reason about what the original knowledge was.
A simple example of this is when I was recently reading a book. I stopped on page 127. I have extreme difficulty remembering "127", but I can trivially remember "the first power of two greater than 100, less one". Or with names. I have difficulty remembering a new name, but once I've learned a name, instead of remembering someone's name, I remember that someone has the same name as someone I know. It took me a good part of a year to remember my wife's name, but now that I know her name, I can easily remember other people with the same name.
This scales really well for remembering complex system. I don't need to remember every little detail about a multi-million line of code project. First I focus on learning the problem the system is trying to solve. I do this by changing the way I think. I essentially replay the thoughts in my head until I come to the correct conclusion by default without remembering anything, because I have difficulty remembering. Now that I think a certain way, I just need to reason about the problem domain using that frame of mind. I can quickly think of the potential patterns I could use to solve the problem. The pattern that seems most familiar is probably the correct pattern. Mind you, I can't remember which pattern is correct, I only only gauge how familiar the pattern seems to me. Then I reason about how I would implement that pattern. Using reasoning, I will create a solution to the problem. If my reasoning is consistent, I will recreate the same result. I do this faster than most people can directly remember something. Since I don't actually remember the individual details, I can effectively "remember" absurdly large complex systems.
Essentially I use my abstract reasoning to identify patterns, then I use my meta-cognition to identify familiar patterns, then use my reasoning to implement those patterns. This is how I "remember" almost everything. I effectively do real-time generation via decades of honed abstract reasoning and meta-cognition. I like to think of it more like how Minecraft has infinitely large worlds vs manually painstakingly creating a map by hand. Instead of remembering every little detail about the world, I only need to remember the algorithm to generate the world, then remember the hopefully few parts that deviate from the algorithm.
Being that I naturally use my abstract reasoning for pretty much everything I do in daily living, I can many times solve new problems nearly as quickly as I can "remember" problems. I also need to be extremely consistent with my reasoning. Even slight changes to my reasoning can drastically affect what I "remember".
This begs the question. "What is 'remembering'?" Seeing that I don't actually remember almost anything, yet for all intents and purposes, I do.
I can make a Turing complete system with pulleys, ropes, and some sort of engine. If someone was to make software that could do what you said, then they could do it with the pulleys and engine. Would this system of ropes be considered conscious?
All of the brain structure to see exist by birth, yet they need to learn to see, and if a child does not learn to see by a certain age, they will never be able to perceive even if they regain their sight later in life. The existence of the structure does not mean it is functional.
Please define "feeling" pain. We're all just computers. I know that I can "feel pain", but how can I know another computer, say the brain of an ant, can feel pain and are not just reacting to damage? If you're not careful, then the character you play in the game "Doom" is "feeling pain" and you're torturing him.
Slashdot Mirror
Just recently I was grocery shopping when I was told that I now have to enter my pin because I'm using MasterCard. I rather liked this because before I could just swipe for anything under $50 or so. I asked the cashier and they said MasterCard just recently started requiring that all payments must use the pin, but Visa and others have not yet required.
General intelligence tends to be on a bell curve, but specialized intelligence tends to be on a power curve. For any given specialty, 80% are below average. In certain types of problem domains, like high function abstract reasoning, you will see absurd differences in ability. You can see in the range of a 1,000,000x difference in the ability to learn something new between the median and the best. One person may literally take seconds and another person will spend a life-time never obtaining what they learned.
While I agree with you have a high level, any large distributed or async parallel system will have many different types of non-determinism.
I've been bitten a few times by Reddit. I assume fly-by-night ads substituting an ad once it gets validated and popular. One of the times I was reading a discussion on reddit about an issue I was researching when some tab-under ad loaded freaking porn on my work computer while I was at work.
Not to mention that unbiased results are junk. The whole point of a search engine is to find biases that suggest that some information is what you're looking for. When I switch Chrome into incognito mode, Google search results are crap. They return me what's popular for the typical person, not popular for a person like me.
every customer -- including those who only use its free services -- will receive a new feature called Unmetered Mitigation
and still we average around 5% unemployment
It's starting to come to light that about 30% of jobs are meaningless, in that they don't add to value or possibly add negative value via increased management overhead. The problem is capitalism seems to pervert "value" to mean "money". Prior to a few decades ago, nearly every job had value. Unemployment may be similar, but most of the "jobs" are just busy work. Assuming this is true, we may already be affected by automation.
I would argue if they aren't competent, they can't do the job.
Ideally, yes. The problem is they seemingly can do their job. Most people's competence are gauged by how quickly they can make a symptom go away, not how correctly they fix the root problem. Like a hospital that ranks doctors by how quickly they get through patients, and a doctor just hands out pain killers like candy. All they did is externalize the cost.
I do a lot of work with 3rd-parties and SSL. One of the issues that happens time and again is when I ask for the public key to install, they send me the private+public pair unencrypted via email and now I have their wild-star EV private cert that expires in 2 years. Just because someone can do the job doesn't mean they're competent.
There's a lot of diploma mills mass printing CS degrees and the general populace is grouping in decent schools with the trash. Even within good Uni/Schools, there are a lot of people getting degrees that shouldn't. There's a group of Ivy league CS professors that have been working with psychologist for over 20 years trying to figure out why so many people are so bad at programming in general, not just CS.
What they're currently seeing is 80% of student who apply fail in the first two semesters, 20% drop/fail for various reasons after the first two semesters, of the remaining 16%, 50% graduate only because of perseverance, not ability, and of the remaining 8%, they're on a power curve where 80% are below average. When taken as a whole, ~98% are below average. Does not seem to be a bell-curve at all.
They have done all kinds of experiments, sourcing ideas from all over the world from many CS or psychology professions, but nothing has worked. They can't seem to make it any easier. So far they have only found one predictor that seems highly correlated are predicting if the student will graduate and be good. Logical consistency. They have some tests that are very hypothetical and require using abstract reasoning to solve for a fictional problem. Think of an abstract reasoning test with pseudo-code instead of visual patterns. They look for two things in these tests, logical dissonance and repeat-ability of getting the same answer some many months later. Even if the reasoning is wrong, as long as it's consistent and does not contradict itself, they have a very high chance of being good at CS+programming.
The tests are "decent" at predicting if a student will probably be decent, but nearly perfect for predicting if they'll be a failure. Always easier to be the critic.
In "programming" few masters are experts and few experts are masters. In psychology, advanced knowledge and advanced reasoning are inversely related. You either know a lot and understand little or know little and understand a lot.
People with the strongest abstract reasoning skills have learned how to quickly forget. Turns out that the act of learning requires a lot of working memory. The more you know, the more clogged your working memory becomes because everything you see triggers a memory that keeps your working memory saturated. The less you remember, the faster you learn and the more complex ideas you can learn. Spatial memory uses a complete different part of your memory. You can remember a lot of abstract concepts without negatively affecting your working memory. If you focus on learning abstract concepts and not facts, you will learn faster.
Most people peak in abstract reasoning in their late teens and plummet in their 30s. This seems to be caused from lots of experience that causes the person to learn more. As the person learns more, their abstract reasoning gets used less and less while they continue to grow their knowledge and use their memory. At some point their abstract reasoning hits an inflection point veering down. People who do no focus on knowledge, but instead focus on understanding do not have this issue because they don't gain as much knowledge. They instead increase their abstract reasoning, which allows them to quickly learn new things and just as quickly forget them.
This is why experience is such a worthless metric in a problem domain that requires much abstract reasoning.
An expert is great for "solving" (remembering solutions) old problems, a master is great as solving new problems. Depending on what problems you have, choose wisely. Then you have the whole issue that in tech, specific knowledge has a half-life of 3-5 years. Worthless by the time you become an expert in it, unless you have a niche position for some legacy system.
People can be meta-conscious, but are not always. It's a skill not always exercised. Meta-cognition and abstract reasoning are highly correlated. The Dunning–Kruger effect is currently thought to be caused by a lack of abstract reasoning because one of the abilities of abstract reasoning is to know when you don't know something, which is also considered a highly meta-cognitive skill. Yet most people are highly affected by the Dunning–Kruger effect.
Most of the skills and abilities described by meta-cognition are extremely weak in most people. While they can have meta-cognition, they're not very good at it. On the other hand, people who claim to have lucid dreams are highly correlated with strong meta-cognitive abilities and abstract reasoning. There seems to be a positive linear correlation with lucid dreaming and frontal grey matter density in the part of the brain responsible for abstract reasoning. They three seem to go hand-in-hand with little deviation, but not causation as far as they can tell.
Changing the definition of conscious to mean what meta-consciousness means would make most people not very conscious, by deffinition.
psychologists have a decent understanding of what babies can and cannot understand
This does not include outliers. My abstract reasoning at the age of 6 was beyond what most adult programmers will ever peak at, yet "abstract reasoning does not start to develop until about age 11". Whatever. In my case, I was born with learning disability that forces me to use Abstract reasoning for nearly everything. The other parts of my brain don't work correctly. I actually have an inverse issues that I don't learn well from concrete examples, but I learn very well from abstract examples. This is the opposite of young children and it's always been this way for me.
My brother taught himself Algebra at the age of 9, and he didn't even have any Algebra books. He just got bored with Arithmetic and created a system of number manipulation to keep himself preoccupied. By the time he was a freshman, he was breezing through AP Calc and actually helping to teach the class. He completed the entire year of work in a few days while in class.
Excluding outliers is very common in research.
My mom was a middle child in a large family and had a lot of experience with young children, along with being the neighborhood baby sitter. She said that I almost never cried, even when only a few weeks old. Even after birth I was noticeably quieter. The doctor took note and thought I may have had some disability, but my mom noticed I like to make noises and shortly realized I made different noises for different wants. A simple example is when I wanted to feed, I would periodically make a sucking noise. If nothing happened in a short while , I would make a short whine+grunt to get attention, then make the sucking noise again. It wouldn't be until some fairly longer time later that I would actually start to cry like a normal child if I didn't get fed.
She always got asked about how she kept me so quiet. I also had a great propensity to keep myself preoccupied, rarely ever wanting attention or interaction from others.
My first sibling has a very strong personality the moment he was born. When the doctor/nurse, can't remember was handing them to my mother, the doctor did something and my brother let out a grunt that sounded like he was pissed off. It startled the person. My sibling was very impatient from those early moments. Made grunting sounds that quickly graduated into whining then crying. Made it very clear what they wanted the situation fixed. The crying shutoff like a light once they realized they were about to get what they wanted.
I know I experience suffering from pain, but I cannot show that other people experience suffering, only that they react. I assume that harming others would cause them to suffer and is therefore unethical without warrant. But that's the crux of this whole problem. How do we know if a computer is suffering? We can know it reacts, but cannot know if it's perceiving.
If my cat hears the key-chain jingle of the laser pointer, he'll come running from where ever he was hiding, look at my hand and figure out where it's pointing, then look in that direction for the dot. He knows my hand is the cause, but he doesn't care.
Your sarcasm fails and you failed to understand the logical implied nuances that made jimbolauski's post irreverent. Once you understand what he actually said and not take it at face value, then you'll understand my reply. Hint "You only feel 'fun' because your brain says something is fun. Nothing is really fun." Who the f*ck cares if it's all fake, I still experience it. In other words "I think, therefore I am"
The article talks about someone who could technically see, just not very well and was legally blind. I was talking about someone who had near zero optical neural stimulation.
We're nothing more than information in the space-time fabric that follows well defined algorithms either discretely or statistically. The entire Universe is just one massive computer and we just occupy a subset of space-time. You may want to learn about the abstractness of how our perception works. What you see as the color "red" is not a color but a concept that is not blue or green.
Red is defined as "not blue or green"
Green is defined as "not red of blue"
Blue is defined as "not red or green"
Welcome to how the brain works. Even concrete concepts are abstract at their core.
I should expand on what "familiar" means for pattern recognition. It's the pattern that I can most easily reason about. I visualize patterns. Think of it like an N dimensional "shape" of the sort. The more defined the shape is with the least about of mental effort, the more "familiar" it seems to me. I say this because the less effort I put into reasoning about something while coming to a "clear image", the more times I *must* have encountered the pattern. I assume reinforced neural path ways or something.
When I encounter a pattern that I am less familiar with, my thoughts branch all over the place. The more branching that occurs, the less reinforced the idea is. The more I encounter an idea, the more it gets reinforced into the way I naturally think.
There are man other aspects of meta-cognition that I need to use, but this is the most simplified explanation that captures the whole idea.
It gets really weird when I "remember" something that I never actually did. I've only been aware of this a few times, but one of them was when my reasoning changed for a certain problem domain and I started to "remember" a false implementation, but a better implementation. I only realized this after a few seconds of discussing with a co-worker. I noticed a lack of meta-memory about the thoughts and found it very strange. The ideas kept flowing as I normally create ideas in real-time, but I had nothing to associate with them. I realized I must have learned something new that changed the way I thought. Jumped into the code to actually look at what I did, and figured out what I learned that changed the way I thought. By remembering this small factoid of what changed the way I thought, I could consciously pretend to not be aware of that fact and re-create my prior logic again.
It takes great mental effort to ignore something that I should be aware of. Because I'm used to going with the flow of what's natural, I'm effectively creating cognitive dissonance and deviating from that flow. I eventually refactored the code with my new reasoning applied, not to make it "better" in any measurable way, but to make it easier for me to remember with my new way of thinking.
That's why you need to be meta-cognitive about your thoughts and memory. I actually have a learning disability that makes it extremely difficult to remember facts of any kind, but I can remember meta-facts just fine. Instead of remembering something directly, I remember by focusing on a fact while it's int my short-term memory and creating lots of meta-knowledge about the knowledge I want to remember. Then when it comes time to remember something, I use the meta-knowledge to reason about what the original knowledge was.
A simple example of this is when I was recently reading a book. I stopped on page 127. I have extreme difficulty remembering "127", but I can trivially remember "the first power of two greater than 100, less one". Or with names. I have difficulty remembering a new name, but once I've learned a name, instead of remembering someone's name, I remember that someone has the same name as someone I know. It took me a good part of a year to remember my wife's name, but now that I know her name, I can easily remember other people with the same name.
This scales really well for remembering complex system. I don't need to remember every little detail about a multi-million line of code project. First I focus on learning the problem the system is trying to solve. I do this by changing the way I think. I essentially replay the thoughts in my head until I come to the correct conclusion by default without remembering anything, because I have difficulty remembering. Now that I think a certain way, I just need to reason about the problem domain using that frame of mind. I can quickly think of the potential patterns I could use to solve the problem. The pattern that seems most familiar is probably the correct pattern. Mind you, I can't remember which pattern is correct, I only only gauge how familiar the pattern seems to me. Then I reason about how I would implement that pattern. Using reasoning, I will create a solution to the problem. If my reasoning is consistent, I will recreate the same result. I do this faster than most people can directly remember something. Since I don't actually remember the individual details, I can effectively "remember" absurdly large complex systems.
Essentially I use my abstract reasoning to identify patterns, then I use my meta-cognition to identify familiar patterns, then use my reasoning to implement those patterns. This is how I "remember" almost everything. I effectively do real-time generation via decades of honed abstract reasoning and meta-cognition. I like to think of it more like how Minecraft has infinitely large worlds vs manually painstakingly creating a map by hand. Instead of remembering every little detail about the world, I only need to remember the algorithm to generate the world, then remember the hopefully few parts that deviate from the algorithm.
Being that I naturally use my abstract reasoning for pretty much everything I do in daily living, I can many times solve new problems nearly as quickly as I can "remember" problems. I also need to be extremely consistent with my reasoning. Even slight changes to my reasoning can drastically affect what I "remember".
This begs the question. "What is 'remembering'?" Seeing that I don't actually remember almost anything, yet for all intents and purposes, I do.
By your definition, people don't make choices. Nothing really matters, might as well give up living.
I can make a Turing complete system with pulleys, ropes, and some sort of engine. If someone was to make software that could do what you said, then they could do it with the pulleys and engine. Would this system of ropes be considered conscious?
All of the brain structure to see exist by birth, yet they need to learn to see, and if a child does not learn to see by a certain age, they will never be able to perceive even if they regain their sight later in life. The existence of the structure does not mean it is functional.
Please define "feeling" pain. We're all just computers. I know that I can "feel pain", but how can I know another computer, say the brain of an ant, can feel pain and are not just reacting to damage? If you're not careful, then the character you play in the game "Doom" is "feeling pain" and you're torturing him.