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(Created page with "Matt Bradley made an interesting point about the gallop towards AI: we should be careful of anthropomorphizing robots. What they do is a bad proxy or derivative of human intelligence. It is not the same, and we should not let habits of language conflate the two Ther’s another way of looking at it, too: we should not see what humans do as a proxy for how robots behave, either. Not only should be be mindful of lazy computer metaphors for human behaviour, but we should b...")
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Matt Bradley made an interesting point about the gallop towards AI: we should be careful of anthropomorphizing robots. What they do is a bad proxy or derivative of human intelligence. It is not the same, and we should not let habits of language conflate the two
Recently, Matt Bradley made an interesting point<ref>[https://www.linkedin.com/pulse/why-humanise-machines-matthew-bradley-adgce ''Why Humanise The Machines?'']</ref> about our gallop towards [[AI]]: whatever we do, we should be careful of anthropomorphising when we talk about robots. Machines don’t think, and they don’t “''hallucinate''”. Hallucinating is actually a pretty special, [[I am a Strange Loop|strangely-loopy]] phenomenon. No-one has yet come up with a compelling account of how any kind of human consciousness works — cue tedious discussions about [[Cartesian theatre|Cartesian theatres]] — but we do know this is categorically not what machines do. We should not let habits of language conflate the two. Down that road lies a false sense of security.
 
But the converse is just as important: we should not describe what humans do in terms meant for machines — we shouldn’t ''robomorphise'', or evaluate human performance in terms suited to machine behaviour. This is to make a grievous category error.
 
This does not just invite [[technological redundancy]] — which, in its place, is no bad thing — we do not lament the demise of proofreaders over delta-view — mechanisation promises  to clear away the [[tedium]] and bureaucratic sludge in well-understood, low-risk, standard processes — but that seems not to be the aspiration of the thought leaders.


Ther’s another way of looking at it, too: we should not see what humans do as a proxy for how robots behave, either. Not only should be be mindful of lazy computer metaphors for human behaviour, but we should be wary of evaluating humans by reference to machine qualities, much less optimising our criteria for human contributions for numerical processing. For if there is a sure way to technological redundancy, that is surely it.
(Technological redundancy, in its place, is no bad thing — we should not lament the demise of manual comparison over deltaview, any more than we should lament the demise of hand weavers over the Jacquard loom).
But technological redundancy has its place — clearing out the tedium and bureaucratic sludge in well-understood, low-risk, standard processes — but that seems not to be the aspiration of the thought leaders.
“Any sufficiently advanced technology is indistinguishable from magic” says Arthur C. Clarke — the jury is out whether AI is different, but it is not unreasonable to proceed on the assumption it is not, and foolish to do otherwise.
“Any sufficiently advanced technology is indistinguishable from magic” says Arthur C. Clarke — the jury is out whether AI is different, but it is not unreasonable to proceed on the assumption it is not, and foolish to do otherwise.
The main use cases for machines in any industry from the beginning of civilisation are these: power, speed, accuracy, efficiency, economy.
 
Machines do things easier and cheaper and quicker than humans.
The main use cases for machines in any industry from the beginning of civilisation are these: ''power'', ''speed'', ''accuracy'', ''efficiency'', ''economy''. Machines do things easier and cheaper and quicker than humans. They always have done. Per George Gilder:
They therefore work best in constrained, predictable environments that have, as far as possible, been preconfigured to eliminate unknowns and minimise waste. The factory production line is the paradigm example. Human intervention is minimised and, where possible, eliminated.
{{quote|“The claim of superhuman performance seems rather overwrought to me. Outperforming unaided human beings is what machines are supposed to do. That’s why we build them.”<ref> ''Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy'' (2018)</ref>}}
Humans have been largely absent from production industries — this has been a great driver of the colossal pivot to the service industry. It isn’t that we don’t make things any more: we just don’t need humans to do it. We have optimised and configured the production industry so it can work by itself.
 
The service industry is going through a similar process. Where it can it will eliminate expensive, manual processes that can be done automatically.  
They therefore work best in constrained, predictable environments that have, as far as possible, been preconfigured to eliminate unknowns and minimise waste, such as a factory production line. Human intervention is minimised and, where possible, eliminated.
Where this can be done easily, it has been: deltaview. Email obviates the fax room.  
 
But matters requiring human interaction have been harder to fully automate. The typical reactions have been to triage — delay the intervention of a human as long as possible — or to “self serve” — a rather cheeky means of getting the consumer to do part of the work, or absorb its expense — for you. Ryanair are masters of this — they even charge customers for getting their booking wrong!l (penalising humans for their own human frailty is the ultimate in chutzpah) but it happens within and without organisations.  
=== Why humans don’t work in manufacturing any more ===
Internet enabled outsorurcing service to the customer or consumer. Typing pool!
Therefore humans have been largely absent from production industries — this has been a great driver of the colossal pivot to the service industry. It isn’t that we ''don’t'' make things any more: it‘s just that most of the time we don’t need ''humans'' to do it. We have optimised and configured the production industry so it can work by itself.
 
The service industry has undergone a similar process over the last forty years, expecially as it ballooned with refugees from manufacturing. Where it can, it will eliminate expensive, manual processes that can be done automatically.  
 
Where this can be done easily, it has been: deltaview, for example. Law firms used hire teams of “document examiners”. Likewise email obviated the fax room and, largely the mail room.  
 
But matters requiring human interaction have been harder to fully automate. The typical reactions have been to [[triage]] — delay the intervention of a human as long as possible — or to “self-serve” — a rather cheeky means of getting the consumer to do part of the work, or absorb its expense — for you.  
 
Ryanair is the master of this — it even charges customers for getting their booking wrong!  
(penalising humans for their own human frailty is the ultimate in chutzpah) but it happens within and without organisations.  
 
Internet enabled outsourcing service to the customer or consumer. Typing pool!
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