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So I think programming will eventually become a tool used by everyone rather than something for only for programmers and other tech-savvy individuals. It'll be

So I think programming will eventually become a tool used by everyone rather than something for only for programmers and other tech-savvy individuals. It'll be something that everyone uses the same way basic arithmetic is a tool that everyone uses these days. These days programming is reserved for the few because in order to program you have to learn a language with very specific grammar and the level of abstraction is still quite low. The underlying operations being expressed by current languages are not themselves intuitively hard to understand but the average person is prevented from doing so because of the language barrier. The level of abstraction that the average programmer is working with is moving continuously higher. In the past there was a time when the average programmer was working at the level of assembly language but today the average programmer is working at much higher levels of abstraction. There are obvious disadvantages to current visual programming systems as you've described but it may be the case that we just haven't developed the right abstractions and interfaces that work best for visual programming.

kpil 10y ago
I doubt that will happen. There is a distinction between incidental complexity - complex tools and languages - and inherent complexity - the problem itself, it's domain and the emergent properties of it all combined with a Turing complete machine. You can't really do much to reduce the inherent complexity, and even professional programmers are struggling with the inherent complexity in all but the smallest problems. Some programmers are even struggling more than others which suggests to me that programmers need to be a bit above average IQ to be efficient, and it might even be a lower limit were nothing useful happens at all. What could potentially happen is that we could invent AI agents that could help us tackle some of the inherent complexities, and maybe non professionals could string together intents that will be interpreted by AI, but that won't happen soon. Edit: The insights about incidental and inherent complexity is not mine. They were popularised in the great book The Mythical Man-Month by Fred Brook that have many insights that are applicable to software development in general apart from those insights that are applicable to writing large operative systems. As the book is 40+ years old and the follow-up essay "There is no silver bullet" - that expand on the complexity topic - is 30 years old, there is little reason that we are still trying to invent the silver bullet. I guess it could even be described as a failure of the educational systems, because I'm sure there is a lot research in information theory that have been done or at least should have been done, that touches these topics.
- sjayasinghe 10y ago
  In many cases what differentiates a programmer who is better at dealing with inherent complexity than another has a lot to do with the ability to apply the right patterns, tools, or strategies under the right circumstances. This ability is largely influenced by having been exposed to similar problems in the past and having applied various strategies to solve those problems. One reason why a lot of programmers struggle is because our current educational systems do not expose students to computational thinking at an early age. They've simply not have had enough exposure to that kind of thinking. Even though computational thinking draws on computer science as a formal discipline the insights are applicable to various other domains and virtually everyone will benefit if they're able to apply the same kind of thinking to other problems in their personal and professional lives. Without having to solve any problems specific to computer science people can still acquire the ability to effectively apply computational thinking by solving other problems in their lives because the inherent complexities of those other problems are going to have some similarities to the inherent complexities in designing software systems. Now some people may already have highly developed computational thinking abilities without ever having touched a computer because intuitively they've understood how to solve analogous problems in a different domain. Such people may be far better at dealing with inherent complexity than some or most professional programmers but they could never apply those abilities in this domain due to the barrier to entry posed by the incidental complexity associated with the tools and languages. A friend of mine, a physicist, is an example of the above. Her approach to dealing with complex problems is already far better than many developers I know, but she wouldn't be a good programmer simply because she doesn't understand the tools. However, if she were to invest significant time to understand the tools then she'd be a better developer than most. Not only that, if she had familiarity with the tools then her already developed computational thinking skills would mature much further. If she were to have access to tools that allowed her to apply her ability to deal with complexity without getting in her way then that would be the ideal outcome. What I'm trying to say is that we are a very long way away from minimizing the incidental complexities introduced by our tools and languages. EDIT: Sal Khan gave a relevant Ted talk on the limitations of our educational systems: https://www.youtube.com/watch?v=-MTRxRO5SRA https://www.youtube.com/watch?v=-MTRxRO5SRA He mentions that if you were to ask a literate individual in a past society with a 10 percent literacy rate what would be the maximum possible literacy rate they would've said something like 20 percent (80 percent of the population is incapable of overcoming the inherent complexity associated with gaining literacy). But our educational systems have progressed far enough to achieve a 99 percent literacy rate, which would've been impossible for someone in a society with 10 percent literacy to even consider as a possibility. Our estimates of where the boundary between incidental and inherent complexity lies is generally going to be strongly biased.

kpil 10y ago

I doubt that will happen. There is a distinction between incidental complexity - complex tools and languages - and inherent complexity - the problem itself, it's domain and the emergent properties of it all combined with a Turing complete machine. You can't really do much to reduce the inherent complexity, and even professional programmers are struggling with the inherent complexity in all but the smallest problems. Some programmers are even struggling more than others which suggests to me that programmers need to be a bit above average IQ to be efficient, and it might even be a lower limit were nothing useful happens at all. What could potentially happen is that we could invent AI agents that could help us tackle some of the inherent complexities, and maybe non professionals could string together intents that will be interpreted by AI, but that won't happen soon. Edit: The insights about incidental and inherent complexity is not mine. They were popularised in the great book The Mythical Man-Month by Fred Brook that have many insights that are applicable to software development in general apart from those insights that are applicable to writing large operative systems. As the book is 40+ years old and the follow-up essay "There is no silver bullet" - that expand on the complexity topic - is 30 years old, there is little reason that we are still trying to invent the silver bullet. I guess it could even be described as a failure of the educational systems, because I'm sure there is a lot research in information theory that have been done or at least should have been done, that touches these topics.

sjayasinghe 10y ago
In many cases what differentiates a programmer who is better at dealing with inherent complexity than another has a lot to do with the ability to apply the right patterns, tools, or strategies under the right circumstances. This ability is largely influenced by having been exposed to similar problems in the past and having applied various strategies to solve those problems. One reason why a lot of programmers struggle is because our current educational systems do not expose students to computational thinking at an early age. They've simply not have had enough exposure to that kind of thinking. Even though computational thinking draws on computer science as a formal discipline the insights are applicable to various other domains and virtually everyone will benefit if they're able to apply the same kind of thinking to other problems in their personal and professional lives. Without having to solve any problems specific to computer science people can still acquire the ability to effectively apply computational thinking by solving other problems in their lives because the inherent complexities of those other problems are going to have some similarities to the inherent complexities in designing software systems. Now some people may already have highly developed computational thinking abilities without ever having touched a computer because intuitively they've understood how to solve analogous problems in a different domain. Such people may be far better at dealing with inherent complexity than some or most professional programmers but they could never apply those abilities in this domain due to the barrier to entry posed by the incidental complexity associated with the tools and languages. A friend of mine, a physicist, is an example of the above. Her approach to dealing with complex problems is already far better than many developers I know, but she wouldn't be a good programmer simply because she doesn't understand the tools. However, if she were to invest significant time to understand the tools then she'd be a better developer than most. Not only that, if she had familiarity with the tools then her already developed computational thinking skills would mature much further. If she were to have access to tools that allowed her to apply her ability to deal with complexity without getting in her way then that would be the ideal outcome. What I'm trying to say is that we are a very long way away from minimizing the incidental complexities introduced by our tools and languages. EDIT: Sal Khan gave a relevant Ted talk on the limitations of our educational systems: https://www.youtube.com/watch?v=-MTRxRO5SRA https://www.youtube.com/watch?v=-MTRxRO5SRA He mentions that if you were to ask a literate individual in a past society with a 10 percent literacy rate what would be the maximum possible literacy rate they would've said something like 20 percent (80 percent of the population is incapable of overcoming the inherent complexity associated with gaining literacy). But our educational systems have progressed far enough to achieve a 99 percent literacy rate, which would've been impossible for someone in a society with 10 percent literacy to even consider as a possibility. Our estimates of where the boundary between incidental and inherent complexity lies is generally going to be strongly biased.