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SURELY no self-respecting hack would argue that a moment of insight or analytical expertise that lies at the heart of solid journalism can be reduced to a series of simple, easily reproduced tasks? There is, after all, no way that the spark of inspiration ignited by the nuanced and intangible intercourse of analysis and synthesis can be clasped, not to mention crammed into the rigid corset of algorithmic rules. Or can it? Jim Giles, a writer who has contributed to this newspaper, fellow journalist MacGregor Campbell and a team of researchers led by Niki Kittur, from Carnegie-Mellon University in America, decided to check.

Under the rubric "My Boss Is a Robot" they are testing whether it is possible to draw on the sort of distributed creativity that the internet has made possible—and faddish—to perform the equivalent of journalistic piecework. To start with, the group has chosen to bash out the kind of article with which Babbage is all too familiar: a write-up of a newly released scientific research paper. Rather than assign the task as a whole to a single person, their system will try to tease apart and outsource different elements of analysis and production.

The effort will not embrace a wiki-like approach, in which drafts are successively (and sometimes simultaneously) revised by unrelated parties who may or may not bring particular expertise to the table, and who can all see the current state of work. Instead, the group will atomise the process of writing an article into multiple steps which can be accomplished in isolation. (Part of the project is to see how reproducible—or not—such tasks really are.) Tasks might include writing a headline, summarising a chart, or providing a conclusion for a subsection of text. Each component will be assigned to multiple people without allowing them to see what the others have come up with. The collected products will then be sent out again for examination by another batch of eyes, again unable to compare notes. "You need redundancy for quality," explains Mr Giles. This competitive culling process is designed to judge which contributors excel, as well as reduce the need for editorial oversight by crowdsourcing part of that function.

The team finds participants in its experiment via Mechanical Turk, an automated task-jobbing service built by Amazon.com, an online retailer, as part of its cloud and computation division. Amazon uses it for some of its data gathering and processing. Mechanical Turk allows anyone to post tightly defined jobs, dubbed Human Intelligence Tasks (HITs). Those assigning HITs can set tests that prospective workers must pass to qualify for the job, or limit employ to workers with a good track record rated by previous finished jobs for which the assigner agreed to pay. Each HIT has a price tag or range of fees attached, often exceedingly low by developed-world standards. One current HIT, for instance, consists in collecting museum and art gallery entrance fees, and pays $0.12 for each gathered item. A few firms, such as Clowdflower, offer a layer on top of Mechanical Turk to help companies indentify high-quality workers. (The service's name refers to the Turk, a chess-playing automaton built in the late 18th century later determined to be a fake.)

Mr Giles and his colleagues have already completed the first test, where they asked ten workers to write a lead sentence or two that would capture the most salient point in the abstract of this research paper. The offerings, the quality of which proved surprisingly high, were then pushed out to another twenty workers who voted on which was best. Two in particular were fingered as the most likely to induce readers to read on. The winning submission read, "Researchers have always wondered what made hit songs, books and movies, just that, hits. What they've found is that quality had only little to do with it."

This is, quite literally, only the beginning. Things are bound to get more complicated further down the column inches. It is straightforward to ask somebody to write, or assess, a fabulous intro to an article; much less so to commission them to write just the second, or the 22nd, line—especially if the writer is oblivious to what came before. Stitching together the separately outsourced chunks may prove more intractable still.

Mr Giles reckons that dealing with these problems will require continuous refinement of the various HITs' instructions to make them unambiguous enough to ensure that the resulting bits can be sewn together relatively seamlessly—and automatically. In effect, this differs precious little from a schematic computer program, with people playing the role of software modules that, given a particular input, create a usable output for the next module to churn.

The planned test of the system also carries a whiff of basic computer science: the classic thought experiment devised by Alan Turing, an artificial-intelligence pioneer. In the "Turing test", a computer is deemed intelligent when a human judge cannot reliably tell which of his two unseen interlocutors is a computer and which is another human being. Mr Giles's trial will involve taking a fresh research paper on the basis of which Mr Giles or Mr Campbell would bash out a piece fit for publication, and feeding the same paper to their human processing modules. The results will then be published side by side on the project website without bylines to see whether readers can tell the difference between the amateur crowd's collective wordsmithery and that of a trained reporter.

In one way, the comparison with artificial intelligence is rather comforting, at least to journalists. Very clever people have been trying to get machines to master natural language, to little practical effect. IBM's Watson computer may have made mincemeat of his human competitors on "Jeopardy!", a trivia quizshow requiring both vast knowledge and linguistic competence. But it will be a while yet before Watson-like contraptions can undercut an eloquent specimen of Homo sapiens.

However, when discussion of Mr Giles's human modules turned to money anxiety set in. The experiment to produce the first line of text required spending a dollar on labour (though that clearly did not include whatever the two journalists and the team of researchers earned for their efforts). Mr Giles cannot yet put a price on a full article, but expects it to be a fraction of what freelancers, not to mention staff writers, demand for what would—were the system to function smoothly—be the same work. True, Mr Giles admits that the most likely outcome is that the process still requires expertise to punch up and add depth to the automated draft. But that is typically the job of editors, not lowly journalists tasked with filing raw copy. Perhaps Babbage ought to brush up his editing skills. Just in case.