Thoughts on Education and the Computer Age - Shift Happens
Thoughts on Education and the Computer Age – Shift Happens
In response to 'shift happens' you tube video: Part 1 – The Problem
March 1st, 2008
A friend sent me two YouTubes to watch, both part of ‘Shift Happens.’ They are interesting and thought provoking and, in conclusion, encourage a dialogue on the future of education. The following is presented as a partial response to that query for dialogue.1
In the two short videos that I saw, much is made about three key points:
1) Growth in the amount of data
2) Increase in computational power
3) New fields of study
Let's look at each
1) The growth in the amount of data.
The commentary on rise in the generation of data (exabytes worth of data every month or week or day) and the throughput rates of a trillion bps are all fascinating. But what does that really mean? First, there has to be recognition that much of what is generated, MOST of what is generated, is either strict entertainment (the vast bulk of YouTube videos, for example) or are a regurgitation of already existent data. The fact that the average 21 year old will generate 250,000 e-mails or IM by the time of his 21 birthday, means (assuming they start e-mailing or IMing at age 3) that they send 38 e-mails or IMs every day of their life. The vast bulk of that data is of no significance to the world beyond his or her group of friends.
Similarly, it is posited that the average human in the 1800s would be exposed to as much information in a lifetime as is found in eight New York Times. You can now encounter that much information in a few hours on the internet. While I’m not sure of the first half of this equation (how much information you would be exposed to in 1800), exposing someone to information isn’t really the issue, the issue is how much is processed?
The answer to that question is found in the nature of knowledge itself. Whenever 'facts' (I am assuming they are all true) like this are presented, there is an inference that with the growth of data will somehow come 'Wisdom.' That ignores the very nature of wisdom.
Who would want mold in a laboratory and why are all these cantaloupes sitting in the sun?
Wisdom is not a simple accumulation of mountains of data. Rather, wisdom is the final stage in a long and difficult process of synthesis of cognitive material over time. It begins with simple data. Data are sifted, much is discarded through the Socratic dialectic, and eventually some are synthesized into information. Information is then sifted, and more data is added, through more rigorous effort, and synthesis eventually leads to knowledge. Think of the journey from high school student to pre-med student to medical student to intern and resident and finally a practicing physician. By the time the MD is entering private practice he or she has built a 'knowledge base' on medicine. Over the course of a number of years that knowledge base, synthesized with other knowledge bases - chemistry perhaps, behavioral psychology, physics, etc. - (plus additional information and data, carefully selected) will allow the development of understanding. Even later, additional fields of knowledge and even understanding may be synthesized and we begin to see the development of wisdom.
What happens if we continually add more data? Do we create more wisdom?
Assume that you, as an individual, can sift through 10,000 datum per day, identify 250 key datum, and synthesize those into 50 units of information - every day. (Disregard the numbers, this is illustrative only). If I give you 100,000 pieces datum, what will you be able to do? Well, the answer is that you will be lucky to produce 10 units of information per day. You may in fact increase your speed of sifting data, perhaps identifying 500 or even 1000 key datum daily. But you will have run out of time to synthesize them. And tomorrow you will have 100,000 more data. And so, as we increase the speed of data generation and data transmission, we increase the amount of chaff you need to sift through to find the ‘kernels,’ reducing the amount of time available for synthesis - higher order mental activity.
The immediate response from many will be: "But, this is the value of computers - the ability to winnow out the kernels from the chaff." Well, yes and no. It is also the danger.
The key to developing higher order cognitive material is the synthesis of apparently unrelated items into a new synthesis. But that is exactly the material a computer would - logically - weed out. Computers will do as they are programmed, ‘sifting’ based on established relationships. And, we are told, at ever increasing speeds. Creating information from data or knowledge from information is the synthesis of apparently disparate items. Until someone ‘sees’ the new relationship, putting the two together ‘makes no sense.’
And so, penicillin, cheaply produced using cantaloupes, saved the lives of thousands and thousands of Allied soldiers during the last year of World War II.
2) The increase in computational power
There has been a point made that within 30 or 40 years a single $1,000 lap-top will have more computational power than every human alive.
Frankly, I’m surprised it will take that long. (I’m also not sure how you measure the computational capacity of one human, never mind billions, but I’m not sure it matters.) When I joined the Navy in the late 1970s the F-14A was the crème de la crème of tactical aviation and its AWG-9 radar and its ‘massive processor’ was the apex of tactical airborne weapon systems. The AWG-9 had, if I remember correctly, an Intel 8080 8bit processor, which gave it the capability to run something like 500,000 operations per second. As was pointed out at the time, this was more computational power than was available to NASA when they planned the first moon shot in the mid-1960s.
By the time I was working on my masters, six years later, I had a desk-top computer that was nearly two orders of magnitude more capable than the AWG-9. The fact is, that is what computers are good for: crunching numbers.
What is not answered is: what are they crunching? Where is all that data coming from and of what value is it? What is clear is that the computer does not know how to assign real value, only humans can do that.
As the economist Leo Cherne once said, “The computer is incredibly fast, accurate and stupid. Man is unbelievably slow, inaccurate and brilliant.”
3) New Fields of Study
The original discussion is intended to ask the question as to how educational systems were preparing students for the world of tomorrow. This point is stressed by discussing how few fields found in colleges today existed just ten or twenty years ago and that the rate of change is so high that within a few years fields of study will rise and fall, and new ones will be created so fast, that students will enter college to study fields that will be irrelevant by the time they graduate and new fields, one that they didn’t even know existed when they entered school will now be key fields of study.
And, by some date in the near term the world will be generating data at such a rate that the amount of data will be doubling every 3 or 4 days.
This would, in fact, suggest to me that we would all become dumber.
Here’s why. If education requires educators, teachers, mentors to lead the student through the tangle in front of him or her, and we arrive at a point in time where new data and new fields are growing so fast that we can’t even train people before the field disappears and is replaced with another, then we can never develop expertise in that field. We are thus confronted with a breaking point, a knuckle in the curve, if you will, after which the amount of data has become so overwhelming that there are no more teachers of these advanced fields, only new explorers, isolated from each other by canyon walls of data and the isolation of field unique languages. Individuals will know more and more about increasingly narrow fields of regard, and less and less about the rest of the world. They will become isolated by the sheer mass of data they are confronted with every day, networking around the world with the few other folks who understand them (because they now can) and finding themselves increasingly unable to communicate with those who are not in their field.
We have already seen this begin, with many people increasingly hesitant to engage in critical analysis of anything if it might cause them to question any so called expert. Instead, more experts are called in and the argument disappears into a tangle of jargon.
So, how do we fix it?
The point of these videos was to begin a discussion on where to take education. That is a noble endeavor and I will offer some thoughts on that subject tomorrow.
_______________________________________________________________
1 Some thoughts on numbers presented in the video. China’s numbers are presented in a somewhat ominous manner. But there is more to those numbers than what was presented. The fact that there are more unemployed in China then there are employed in the US translates into more than 150 million unemployed Chinese. The fact is that the vast bulk of China’s population lives in an area the same size as the US east of the Mississippi River. Putting 150 million unemployed into that size of an area is a problem that verges on crisis for China.
In response to 'shift happens' you tube video: Part 1 – The Problem
March 1st, 2008
A friend sent me two YouTubes to watch, both part of ‘Shift Happens.’ They are interesting and thought provoking and, in conclusion, encourage a dialogue on the future of education. The following is presented as a partial response to that query for dialogue.1
In the two short videos that I saw, much is made about three key points:
1) Growth in the amount of data
2) Increase in computational power
3) New fields of study
Let's look at each
1) The growth in the amount of data.
The commentary on rise in the generation of data (exabytes worth of data every month or week or day) and the throughput rates of a trillion bps are all fascinating. But what does that really mean? First, there has to be recognition that much of what is generated, MOST of what is generated, is either strict entertainment (the vast bulk of YouTube videos, for example) or are a regurgitation of already existent data. The fact that the average 21 year old will generate 250,000 e-mails or IM by the time of his 21 birthday, means (assuming they start e-mailing or IMing at age 3) that they send 38 e-mails or IMs every day of their life. The vast bulk of that data is of no significance to the world beyond his or her group of friends.
Similarly, it is posited that the average human in the 1800s would be exposed to as much information in a lifetime as is found in eight New York Times. You can now encounter that much information in a few hours on the internet. While I’m not sure of the first half of this equation (how much information you would be exposed to in 1800), exposing someone to information isn’t really the issue, the issue is how much is processed?
The answer to that question is found in the nature of knowledge itself. Whenever 'facts' (I am assuming they are all true) like this are presented, there is an inference that with the growth of data will somehow come 'Wisdom.' That ignores the very nature of wisdom.
Who would want mold in a laboratory and why are all these cantaloupes sitting in the sun?
Wisdom is not a simple accumulation of mountains of data. Rather, wisdom is the final stage in a long and difficult process of synthesis of cognitive material over time. It begins with simple data. Data are sifted, much is discarded through the Socratic dialectic, and eventually some are synthesized into information. Information is then sifted, and more data is added, through more rigorous effort, and synthesis eventually leads to knowledge. Think of the journey from high school student to pre-med student to medical student to intern and resident and finally a practicing physician. By the time the MD is entering private practice he or she has built a 'knowledge base' on medicine. Over the course of a number of years that knowledge base, synthesized with other knowledge bases - chemistry perhaps, behavioral psychology, physics, etc. - (plus additional information and data, carefully selected) will allow the development of understanding. Even later, additional fields of knowledge and even understanding may be synthesized and we begin to see the development of wisdom.
What happens if we continually add more data? Do we create more wisdom?
Assume that you, as an individual, can sift through 10,000 datum per day, identify 250 key datum, and synthesize those into 50 units of information - every day. (Disregard the numbers, this is illustrative only). If I give you 100,000 pieces datum, what will you be able to do? Well, the answer is that you will be lucky to produce 10 units of information per day. You may in fact increase your speed of sifting data, perhaps identifying 500 or even 1000 key datum daily. But you will have run out of time to synthesize them. And tomorrow you will have 100,000 more data. And so, as we increase the speed of data generation and data transmission, we increase the amount of chaff you need to sift through to find the ‘kernels,’ reducing the amount of time available for synthesis - higher order mental activity.
The immediate response from many will be: "But, this is the value of computers - the ability to winnow out the kernels from the chaff." Well, yes and no. It is also the danger.
The key to developing higher order cognitive material is the synthesis of apparently unrelated items into a new synthesis. But that is exactly the material a computer would - logically - weed out. Computers will do as they are programmed, ‘sifting’ based on established relationships. And, we are told, at ever increasing speeds. Creating information from data or knowledge from information is the synthesis of apparently disparate items. Until someone ‘sees’ the new relationship, putting the two together ‘makes no sense.’
And so, penicillin, cheaply produced using cantaloupes, saved the lives of thousands and thousands of Allied soldiers during the last year of World War II.
2) The increase in computational power
There has been a point made that within 30 or 40 years a single $1,000 lap-top will have more computational power than every human alive.
Frankly, I’m surprised it will take that long. (I’m also not sure how you measure the computational capacity of one human, never mind billions, but I’m not sure it matters.) When I joined the Navy in the late 1970s the F-14A was the crème de la crème of tactical aviation and its AWG-9 radar and its ‘massive processor’ was the apex of tactical airborne weapon systems. The AWG-9 had, if I remember correctly, an Intel 8080 8bit processor, which gave it the capability to run something like 500,000 operations per second. As was pointed out at the time, this was more computational power than was available to NASA when they planned the first moon shot in the mid-1960s.
By the time I was working on my masters, six years later, I had a desk-top computer that was nearly two orders of magnitude more capable than the AWG-9. The fact is, that is what computers are good for: crunching numbers.
What is not answered is: what are they crunching? Where is all that data coming from and of what value is it? What is clear is that the computer does not know how to assign real value, only humans can do that.
As the economist Leo Cherne once said, “The computer is incredibly fast, accurate and stupid. Man is unbelievably slow, inaccurate and brilliant.”
3) New Fields of Study
The original discussion is intended to ask the question as to how educational systems were preparing students for the world of tomorrow. This point is stressed by discussing how few fields found in colleges today existed just ten or twenty years ago and that the rate of change is so high that within a few years fields of study will rise and fall, and new ones will be created so fast, that students will enter college to study fields that will be irrelevant by the time they graduate and new fields, one that they didn’t even know existed when they entered school will now be key fields of study.
And, by some date in the near term the world will be generating data at such a rate that the amount of data will be doubling every 3 or 4 days.
This would, in fact, suggest to me that we would all become dumber.
Here’s why. If education requires educators, teachers, mentors to lead the student through the tangle in front of him or her, and we arrive at a point in time where new data and new fields are growing so fast that we can’t even train people before the field disappears and is replaced with another, then we can never develop expertise in that field. We are thus confronted with a breaking point, a knuckle in the curve, if you will, after which the amount of data has become so overwhelming that there are no more teachers of these advanced fields, only new explorers, isolated from each other by canyon walls of data and the isolation of field unique languages. Individuals will know more and more about increasingly narrow fields of regard, and less and less about the rest of the world. They will become isolated by the sheer mass of data they are confronted with every day, networking around the world with the few other folks who understand them (because they now can) and finding themselves increasingly unable to communicate with those who are not in their field.
We have already seen this begin, with many people increasingly hesitant to engage in critical analysis of anything if it might cause them to question any so called expert. Instead, more experts are called in and the argument disappears into a tangle of jargon.
So, how do we fix it?
The point of these videos was to begin a discussion on where to take education. That is a noble endeavor and I will offer some thoughts on that subject tomorrow.
_______________________________________________________________
1 Some thoughts on numbers presented in the video. China’s numbers are presented in a somewhat ominous manner. But there is more to those numbers than what was presented. The fact that there are more unemployed in China then there are employed in the US translates into more than 150 million unemployed Chinese. The fact is that the vast bulk of China’s population lives in an area the same size as the US east of the Mississippi River. Putting 150 million unemployed into that size of an area is a problem that verges on crisis for China.
posted by Pete O'Brien @ 11:40 AM
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