Reports of our death are an exaggeration: Difference between revisions

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 {{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>{{br|Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy}} (2018)</ref>}}
 ===The [[division of labour]]===
-Machines can only operate in constrained environments. They make flawless decisions, as long as both question ''and'' answer are pre-configured. But take a machine out of its designed environment and it is useless: Good luck getting a [[Jacquard loom]] to plough a field.
+Nowadays, we need to distinguish between ''traditional'', obedient, rule-following tech, and ''randomly-make-it-up'' ''pattern matching'' tech — [[large language model]]s, which are unthinking, probabilistic, pattern matching machines. The latter are the novelty act of 2023, at the top of their hype cycle right now but, like [[Blockchain|blockchain]], will struggle to find an enduring use case.
-We [[sacks of meat]] are better at handling ambiguity, conflict and novel situations. We’re not perfect, but whatever the conundrum is we can at least produce an answer. We don't hang, or freeze waiting for a dialogue box to be clicked: even though syntax errors are par for the course: humans don’t (easily) crash. That’s the boon and the bane of the [[meatware]]: you can’t tell when one makes a syntax error.
+''Traditional'' machines can only operate in constrained environments. They make flawless decisions, as long as both question ''and'' answer are pre-configured. But take a machine out of its designed environment and it is useless: Good luck getting a [[Jacquard loom]] to plough a field.
-But put human and machine together and you have a powerful proposition: the machine handles the rule-following; the human figures out what to do when you run out of road. It’s a partnership. A division of resources. Technology is an extended phenotype. But this is nothing new: this is always how we’ve used technology: the human figures out which field to plough and when; the horse ploughs it.
+We [[sacks of meat]] are better at handling ambiguity, conflict and novel situations. We’re not perfect, but whatever the conundrum is we can at least produce an answer. The meatware doesn’t crash, or hang until dialogue boxes close. That’s the boon and the bane of the [[meatware]]: you ''can’t tell'' when there is a syntax error.
-Now technology has caused the odd short-term dislocation — the industrial revolution put a bunch of hand-weavers out of work — but the long-term prognosis has been benign: “labour-saving devices” have freed us to do things we previously had no time to do, or hadn’t realised you could do, before the technology came along. As technology has developed, so has the world’s population grown, while poverty and indolence have fallen. ''People have got busier''. Whatever technology is doing, with due regard to the risk of confusing [[correlation]] and [[causation]], it ''isn’t'' putting us out of work.
+But human and machine together make a powerful proposition. The machine follows the rules; the human figures out what to do when it runs out of rules, and writes new rules. This is nothing new: this is always how we’ve used technology: the human figures out which field to plough; the horse ploughs it.
+While it may have prompted the odd short-term dislocation — the industrial revolution put a bunch of basket-weavers out of work — but the long-term prognosis has been benign: “labour-saving devices” have freed us to do things we previously had no time to do, or hadn’t realised you could do, before the technology came along. As technology has developed, so has the world’s population grown, while poverty and indolence have fallen. ''People have got busier''. Whatever technology is doing, with due regard to the risk of confusing [[correlation]] and [[causation]], it ''isn’t'' putting us out of work.
 Technology opens up design-space. It expands the intellectual ecosystem, domesticating the ground we know, and opening up [[frontier]]s we don’t. [[Frontier]]s are places where we need smart people to figure out new tools and new ways of operating. Machines can’t do it.