Art will regin when he reach 100% efficiencies in all the sciences

[Elite Engineer]

I think we're half way to reaching this inflection point. The time when we have 100% energy efficiency, 100% of diseases cured, 100% automation, 100% food production, 100% technical transparency, 100% repair..there will be no jobs for scientists, doctors, cooks, mechanics, specialists, designers, engineers, secretaries, developers, financial planners.

 

Artists, actors, musicians, the whole lot will become the doctor and lawyer of yesterday. Science will become a thing of the past, an archaic method that has no purposeful application, barely enough for "education". I feel like we're beginning to feel the early stages of this, with smart phones, and other technologies and their connection with Twitter, Netflix, etc. I suppose it's akin to 1984, but just bare with me.

 

Your thoughts?

 

~EE

Edited December 23, 2016 by Elite Engineer

[DrKrettin]

Can you explain what on Earth the thread title means?

[swansont]

100% energy efficiency is impossible, as any engineer should know.

 

The rest are also basically impossible. Science becoming a thing of the past is not something to worry about.

[Country Boy]

I suspect "regin" was supposed to be "reign".

 

An "Elite Engineer" certainly should know, as swansont said, that "100% efficiency" is impossible.

 

(Does "swans on tea" refer to swans drinking tea, swans smoking "tea", or swans swimming in tea?)

Edited December 23, 2016 by Country Boy

[Delta1212]

What does "halfway" mean in this context? Half implies a midpoint between start and finish. You've sooner of defined a fininish line but where are we starting to count from?

 

Half the time it will take to reach that point? From when? The beginning of human history? That's quite a while. From the beginning of industrialization? The written word? The invention of the computer?

 

Or are we halfway in terms of the knowledge we need and the accelerated accumulation of knowledge means we're actually quite close? But then how are you measuring our current degree of knowledge and how are you extrapolating that to how much we need? Are we halfway on a linear scale? A log scale?

 

And, frankly, I'm not even entirely sure what you're getting at or how Twitter signals the end of science unless you're talking about the sociological phenomenon whereby the proliferation of social media as a primary information distribution outlet has result in a fracturing of the definition of our shared reality and an accelerated politicization of the essence of truth such that such that all scientific knowledge is up for debate on the basis of personal opinion rather than evidence.

[Elite Engineer]

Ok, so I see in some parts, my statement is lacking and confusing. I was trying to make a shorthand post, rather than a TL;DR post. Guess, we're going the long route then.

 

So, it's generally regarded that finding a well paying, steady job as an actor, artist, musician etc is fairly difficult, hence the "starving artist". All other regular 9-5 jobs, such as accountants, engineers, lawyers, doctors, etc, are well paying, steady jobs. However, when we reach an age of major scientific advancement in fields of engineering, medicine, computers...alot of these jobs will go away because there will be no use for them. If you think about it, alot of jobs in society are there because of scientific advancements one way or another. We mechanics because en engineer built a car, we have computer scientists, and IT jobs because computer scientists built computers. Doctors, nurses, specialists, etc exist because scientists made advancements in medicine. Also, other non-science related jobs are made because of these advancements. Customer service rep's are needed in IT companies, secretaries are needed by doctors, cashiers are needed in mechanic shops, quality control specialists are needed in Pharma companies. Salesmen are needed to sell drugs and cars. Manufacturing tech's are needed in engineering companies..etc. More or less, alot of trickle down jobs are made because of scientific advancements. Most of these jobs are consistent, decent paying jobs. In contrast, an artist doesn't always have a consistent paycheck or customer to support them.

 

The irony that I see in this is, if/when we reach a time when EVERYTHING is automated and made perfectly efficient, that there is no need for janitors, salesmen, accountants, IT customer service, QC specialists, nurses, doctors, engineers. The jobs that will have the same prestige and demand that an engineer or doctor accrue will be artists. Automation can't replace actors, comedians, writers, or musicians. Sure, you can make electronic music, and use CGI for movies, but the few "people" that have these jobs would dominate the job market.

 

btw, im not an engineer. My name is from the video game, Dead Space 2

[Strange]

Automation can't replace actors, comedians, writers, or musicians.

 

 

How do you know that?

[Delta1212]

Have you seen Rogue One yet? That makes a pretty compelling case for a future in which actors are no longer necessary, at least for film.

 

And it's fairly likely that we're coming up to a point where AI will be able to replace a lot of service sector jobs. That would have been pure fantasy a few years, but the advances that have been made in artificial neural networks in that time has pretty well convinced me that there is no job in pretty much any field that you can guarantee is impossible to automate any longer.

 

Any job a human can do, computer can do, or will be able to eventually. The question is how soon that happens and how economical it will be to have a machine do it vs an actual person.

[CharonY]

The assertion is quite different from OP. Yes menial jobs and some knowledge based jobs may be replaced. Though it is strange to assert a direct connection with sciences. Moreover, it seems that the basic premise is that creative jobs are safe from automation (somewhat). Science is clearly one of them.

[Delta1212]

The assertion is quite different from OP. Yes menial jobs and some knowledge based jobs may be replaced. Though it is strange to assert a direct connection with sciences. Moreover, it seems that the basic premise is that creative jobs are safe from automation (somewhat). Science is clearly one of them.

My point is that, long term, I don't think that's necessarily true. We crossed the point four years ago where neural networks were capable of finding meaningful patterns in large data sets without being told ahead of time what patterns they were looking for or what each individual element of data even represented.

 

Building robust facial recognition software by showing the neural network a large number of images with faces and without faces, but without having to tell it, with each input, which images contained faces and which didn't.

 

Or, same project but more amusingly and therefore getting more play in the press at the time, just showing it tons of hours of YouTube videos and it learning to recognize cats without having been promoted to do so.

 

Source for both: https://static.googleusercontent.com/media/research.google.com/en//archive/unsupervised_icml2012.pdf

 

And in the time since then, AI has been moving further and further into areas that are considered more "art" than science (a category which, somewhat ironically, in this discussion includes science, itself). Those areas of human rights endeavor that are acknowledged to be at least somewhat rules based on a superficial level but that contain such a level of complexity that it takes a degree of creativity to succeed at them, rather than rote rule-following.

 

AlphaGo was well covered in the press and I believe there was a discussion on this site about it at the time? And, of course, the next challenge it is tackling will be StarCraft, which may not have quite the same cultural cachet, but certainly ups the "muddle" factor as far as optimal moves go, and does maintain a population of very high level players to measure ability against.

 

What I haven't seen quite as widely reported on, and which frankly I find even more compelling in terms of "computers doing jobs that require both knowledge and also creative input in order to be successful" is the recent update to Google translate.

 

Languages are a hobby of mine, and I'm very familiar with Google translate and its limitations. I used it quite frequently as a tool, and using it properly as a tool required knowing exactly what its limits were, where it would break and what kinds of things it had problems handling, so that ai could rework the sentences I need translated to avoid things I knew would break it.

 

I should say I was very familiar with Google translate, because they just switched over from the previous, phrase-based algorithm to a neural network they built for the purpose earlier this year.

 

The improvement in the translations is remarkable. It used to give fairly broken translations for any sentences more complex than very short simple phrases. They were very helpful for figuring out the meaning of long articles in languages you don't speak, but no one ever would have mistaken them for human translations or looked to them for any kind of nuance about a general overview of whatever was being talked about.

 

I just went to the homepage of Spiegel Online and ripped the first paragraph I saw off the site and dropped it in Googke translate.

 

Here is the German:

Der Anschlag von Berlin wirft viele Fragen auf. In der Politik wird über schärfere Sicherheitsmaßnahmen diskutiert: Diese Vorschläge stehen zur Debatte - von Fußfesseln über "spezielle Erstaufnahmeeinrichtungen" bis Videoüberwachung.

 

Here is what Google came up with:

The Berlin attack raises many questions. Politicians are discussing more stringent security measures: These proposals are being debated - from ankle cuffs to "special first-time devices" to video surveillance.

 

Under the old system, that would have been a jumbled mess. And while the new system is not completely flawless, the translations mostly read as something an actual human would have written, rather than something you would get by trying to look up each word in a sentence in a dictionary, and there is a level of abstraction to the translation that is remarkable. A more literal translation of that second sentence would be "In politics, more stringent security measures are being discussed." It means the same thing, essentially, as "Politicians are discussing more stringent security measures" but it changes the subject and switches from passive to active voice, resulting in a slightly more natural-sounding English sentence than the direct translation. Achieving that while maintaining the semantic equivalence of the sentences is seriously impressive.

 

Anyone would doesn't think this has major implications for the ability of networks to produce output that requires creative input doesn't really understand how translation works.

 

I'm not claiming that machines will eventually take every job that a human currently does. My contention is that there is no job currently done by humans that can definitively be labeled as safe from automation in the sense of a machine eventually being capable of performing at, near or above human-level at the task. This includes science, which at its core is the attempt to find high level patterns in mass amounts of raw data. This is exactly the kind of work that machines are already good at doing. And since scaling up of neural networks has, thus far, resulted not merely in gains of speed for processing time, but also in the degree of abstraction that the networks are able to handle in what they do.

 

I am again, though, speaking in principle. I don't think there is any job that a machine, simply scaling from what we have now, cannot do in principle, whether it will be economical to employ a machine capable of doing a given job instead of every human currently doing the job is another question entirely. For low level service jobs, it probably will be, and even for some jobs that require advanced education levels, especially, for instance, in the medical field where diagnostic AIs are already beginning to outpace human doctors in terms of accuracy in medical evaluations.

 

It may be that some tasks require a level of abstraction such that it simply isn't worth the money to run a neural net of the size required in order to properly do the job vs what it would cost to pay a human to do it.

 

But I'm not going to hazard a guess as to exactly what professions will actually wind up falling into that category.

[swansont]

I suspect "regin" was supposed to be "reign".

 

An "Elite Engineer" certainly should know, as swansont said, that "100% efficiency" is impossible.

 

(Does "swans on tea" refer to swans drinking tea, swans smoking "tea", or swans swimming in tea?)

Drinking, I suppose, but really it's just my user name, phonetically spelled.

[Delta1212]

Personally, I want to know the fates of swan sons a through s.

[CharonY]

The examples show how systems can do info synthesis, but I have not seen examples of generating new approaches, ideas or knowledge.

[Delta1212]

The examples show how systems can do info synthesis, but I have not seen examples of generating new approaches, ideas or knowledge.

You say that like there is a difference in kind rather than simply one of degree.

[StringJunky]

The examples show how systems can do info synthesis, but I have not seen examples of generating new approaches, ideas or knowledge.

I think Delta is right, in principle, because we acquire data and the so called imagination is where we permutate that data; we don't just pull ideas out of thin air... they are constructs derived from stored information. If an AI can model random permutations then test them from known formulas to see if they work they are doing the same as a human. The vast majority of people's ideas fail and so will the AI but they'll get through them alot faster.

Edited December 25, 2016 by StringJunky

[CharonY]

Maybe. It requires the presence of some pattern, which I can see in dome areas (music composition for example, even story telling). But I do not quite see it in the area of scientific discovery quite yet.

[StringJunky]

Maybe. It requires the presence of some pattern, which I can see in dome areas (music composition for example, even story telling). But I do not quite see it in the area of scientific discovery quite yet.

Yes, it's a fair way off but I don't think it's fanciful. At that point though AI may be pretty autonomous if it can do that. The Three Laws may be around then.

[Delta1212]

Maybe. It requires the presence of some pattern, which I can see in dome areas (music composition for example, even story telling). But I do not quite see it in the area of scientific discovery quite yet.

Oh yes, as StringJunky says, I'm not claiming this is a place we're at now nor that we're going to reach it tomorrow. It's just that it seems like it's more of a matter of scaling and refinement of techniques to get from where we are now to that point, rather than such an AI requiring the development of some heretofore completely unknown technology. To give an analogy, if such an AI is our moonshot, then we're currently in the early days of Werner Von Braun rather than being at the Wright Brothers stage.

[Ophiolite]

I don't think there is any job that a machine, simply scaling from what we have now, cannot do in principle,

 

While AIs will be capable of arguing the case for Young Earth Creationism, I don't think any of them will be willing to take the job.

[Sriman Dutta]

We are already living in a Machine Era. The time when humans marry robots is not too far away I think.

[DrKrettin]

We are already living in a Machine Era. The time when humans marry robots is not too far away I think.

 

Wow - a wife with an "OFF" button. Dream on.

[Sriman Dutta]

 

Wow - a wife with an "OFF" button. Dream on.

LOL