Blog · Research · 18 September 2026 · 13 min read

Pew's Table Calls 46% a 37-Country Median. USA Today Calls It the Global Average.

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On Thursday 17 September 2026, Pew Research Center published a 37-country survey of what people expect artificial intelligence to do to jobs where they live. USA Today covered it the same morning. Every country percentage in that coverage checks out against Pew's own table, to the point.

The number that will outlive the coverage is the cross-country one: 46%. Pew's table calls it a 37-country median. USA Today calls it the global average. Those are two different instructions to a calculator, and only one of them was carried out.

This is not a correction. USA Today names Pew, links the study, quotes the country figures accurately and describes the question correctly. It is a vocabulary piece. A reader who repeats "the global average was 46%" is repeating something nobody computed, and the gap between those two words is wider than it looks.

What Pew published, and when

The report is "Globally, More People Expect AI to Cause Job Loss Than Growth", by Laura Silver, Richard Wike, Moira Fagan and Jordan Lippert, dated 17 September 2026. It covers 37 middle- and high-income countries. Pew's own one-sentence summary of the headline result is a count of countries, not a percentage of people:

"In 34 of 37 countries Pew Research Center surveyed earlier this year, people tend to believe AI will lead to fewer jobs rather than more jobs."

The release is more than one page. Beside the report sit a dedicated methodology sub-page, an appendix of detailed tables, a full Report PDF and a Topline PDF. A companion short-read, "Democrats are now more worried than Republicans about AI and its impact on jobs", went out the day before, on 16 September.

Four of those are named here and used for nothing. No figure in this post comes from the short-read or its chart page, from the Topline PDF, whose per-country tables did not survive conversion to text with their columns aligned, or from the appendix page, whose tables are published as images rather than as text. Everything below comes from the report page, the methodology sub-page and the formatted tables inside the Report PDF.

The number that travels: 46%

Pew's table for this question gives four shares for every country: fewer jobs, not much difference, more jobs, not sure. Its final row is the cross-country one, printed as "37-country median | 46 | 13 | 9 | 25". Laid out:

The question behind the first column is what AI will do to jobs in the respondent's own country over the next 20 years. USA Today's rendering of the same table:

"In the U.S., 71% of respondents predicted that AI will lead to fewer jobs, an increase of 7% over the past two years. The global average sharing this belief was 46%, with only Australia and South Korea beating the United States, at 76% each."

Three figures in that sentence were checked against Pew's table for this post: 71, 76 and 76. All three match exactly. The seven-point change over the past two years was not among the figures checked, and nothing here should be read as confirming or disputing it.

Pew's own word, three times in one document

The "median" label is not a one-off that a subeditor could reasonably flatten. It is the house term for cross-country aggregates, and it appears throughout the same release.

The row itself carries it: "37-country median". The report writes the same way about a different question, on how people feel about AI in general, reporting that "a 37% median are more concerned than excited, while a 41% median are equally concerned and excited". And it prints a second row with the identical label, "37-country median", for a separate question about AI and economic inequality. Pew's own summary sentence, quoted above, avoids a cross-country percentage altogether and counts countries instead: 34 of 37.

There is nothing wrong with the convention. A median across countries is the standard, defensible choice for cross-national comparison, precisely because it stops the two or three largest countries in a sample from deciding the global figure on their own. Pew states the convention on the face of the table. Nothing was hidden.

Worth noting too that this is one outlet's word, not a press-wide habit. ThePrint's writeup, published the same day, never states the aggregate number at all.

What a median across countries is, and what it is not

A median of 37 numbers is the middle one when they are lined up in order: the 19th of 37, with eighteen values on either side. That is arithmetic, not a claim about anybody's release.

The 37 numbers here are country percentages, and each country contributes exactly one. The Philippines, lowest in the table at 26%, contributes one. The United States at 71% contributes one. Australia and South Korea at 76% each contribute one. Population does not enter the calculation, and neither does sample size. A country of ten million and a country of a hundred million count the same.

"Average" is a different instruction. Say "the global average" and most readers hear something computed over people: count everyone who said fewer jobs, divide by everyone asked. That figure would weight each country by how many people live there, or by how many were interviewed. It is a perfectly coherent number to want. It is not the number in the table.

This post is not going to tell you which one would be bigger. Pew publishes no respondent-weighted or population-weighted global figure for this question in this release, and we have not computed one. We do not know whether such a number would land above 46, below it, or on it, and neither does anybody else quoting the figure.

There is a tell sitting in the printed row, and it takes ten seconds to check. Add the four medians: 46 plus 13 plus 9 plus 25 is 93 (our sum). Seven short of a hundred. A set of shares averaged across the same respondents has to describe one distribution and add up to the whole. A set of medians taken column by column does not, because a different country can sit in the middle of each column. This post cannot apportion that seven-point shortfall between that effect, ordinary rounding, and any response category the printed row does not show, and it does not need to. The point is narrower: the row holds four separate middles, not one distribution, and it does not behave like an average because it is not one.

The second number: 50,758 in Pew's count, 50,838 in the story

Pew states its sample in one sentence, and the scan behind this post found that sentence restated identically five times across two pages, the report page and the methodology sub-page:

"We surveyed 42,151 people across 36 countries from Feb. 8 to May 13, 2026 ... We surveyed 5,119 U.S. adults from Feb. 17 to Feb. 23, 2026 and 3,488 U.S. adults from June 22 to June 28, 2026."

The methodology sub-page goes one level further and gives the response rates behind the two US waves: "For W187, a total of 5,119 panelists responded out of 5,854 who were sampled, for a survey-level response rate of 87%. For W195, a total of 3,488 panelists responded out of 4,069 who were sampled, for a survey-level response rate of 86%." Those are the same two numbers again, from a different direction.

Beside that, USA Today's description of the same sample:

"The study looked at opinions on AI from 50,838 people – 8,687 from the U.S. – in 37 middle- and high-income countries between February and June."

That is 80 more people than Pew counts, in both figures. The non-US component is not in that sentence, but it is in ThePrint's, and it matches Pew exactly: "a Pew Research Center survey of 42,151 adults across 36 countries, conducted in the first half of this year. Adding the US makes that number 37." So the whole of the gap sits in the US figure, 8,687 against 8,607, and carries straight into the total, 50,838 against 50,758.

Why the gap exists, this post does not know, and it is not going to guess. Eighty respondents in fifty thousand will not move a headline percentage, and nothing here argues that any figure in the story is unreliable because of it. It is in this post for three reasons: it is exactly checkable by anybody with the report page open, it appears twice in one short article, and the Pew number it disagrees with is restated five times across two pages without varying by a single digit.

"Between February and June" is true, and it is uneven

The fieldwork window in the coverage is correct as an outer bound. Pew's own dates make it lopsided.

The 36-country international survey, which is effectively the entire non-US sample at 42,151 respondents, ran once, from 8 February to 13 May 2026. The United States is the only country with a second, later wave, 22 to 28 June 2026, and Pew's table footnote sources the US figure to it: "Spring 2026 Global Attitudes Survey; survey of U.S. adults conducted June 22-28, 2026."

So "February to June" describes one of the 37 countries in full and the other 36 not at all. At the 17 September publication date, the last day of international fieldwork was 127 days behind and its first day 221 days behind, while the US June wave closed 81 days behind (our arithmetic from Pew's stated dates).

This is a fact about timing, not a complaint about data quality. Pew prints its own fieldwork dates on the table, on the report page and on a dedicated methodology page, and repeats them until there is no way to miss them. The point is that "between February and June", read at speed, implies a more evenly recent sample than the one that exists. ThePrint handles the same asymmetry more carefully, describing the international survey as "conducted in the first half of this year" and keeping that separate from the US figure.

It also has a small consequence for the ranking everyone quoted. When the coverage lines up Australia at 76%, South Korea at 76% and the United States at 71%, the American number is the freshest point in the comparison: it comes from a wave that closed on 28 June, while the other two come from the window that closed on 13 May, at least 46 days earlier (our arithmetic). This post did not check per-country fieldwork dates inside that window, so the real gap for any one country could be wider than 46 days.

What checks out exactly

The specific country figures are not the story here, because they are right. Australia 76%, South Korea 76%, United States 71%, all verbatim against Pew's table. Greece 68%, Canada 61%, the United Kingdom 61%, France 60%, the Philippines lowest of the 37 at 26%, the same. Both press pieces carry the 76, 76, 71 triplet and both have it correct. ThePrint's version: "At 76 per cent each, Australia and South Korea record the highest share expecting job losses, followed by the United States at 71 per cent."

USA Today's article, by Greta Reich, published at 10:00 a.m. ET on 17 September 2026, also attributes the survey to Pew by name, gets the question right, and reports the finding in the direction the report reports it. Nobody invented a number. That is worth saying plainly, because the thing this post is actually about is harder to spot than an invented number and travels further for exactly that reason.

What the survey measures, which is expectation

One more thing about the 46%, and it is the one most likely to get lost when the figure is recycled six months from now.

Every percentage in this release counts opinions. The question asks what people think AI will do to jobs in their own country over the next 20 years. It is not a model output, not a forecast from an economist, and not a measurement of employment. It records what people expect. Nothing in the release establishes what AI has done or will do to jobs in Australia, South Korea, the United States, the Philippines or anywhere else.

So the sentence "46% of the world expects AI to cut jobs" is two steps away from the data before anyone argues about it. It is a median of country percentages rather than a share of the world's people, and it is an expectation rather than an outcome. Both steps happen silently, in ordinary English, without anyone quoting a wrong digit.

How to read the next global survey headline

Four checks, each of which takes under a minute on the primary source, and none of which needs any statistics beyond addition.

First, find the aggregate's own label in the primary document. Median, average, and "in 34 of 37 countries" are three different statements about the same underlying data, and only one of them is usually in the headline. Second, check whether the primary publishes a weighted figure at all. If it does not, then nobody has one, including the outlet that used the word average. Third, add the sample components up yourself; a total that does not reconcile is a signal about how the number was handled, even when it changes nothing. Fourth, read the fieldwork dates per component instead of as a range, because a range is the outer envelope of possibly very different windows.

None of those four catches a fabricated number. They catch a number that is correct and described as something else, which is the version that survives contact with fact-checking and ends up in someone's slide deck two years later.

What this post does not claim

It does not claim that 46% is wrong, inflated or deflated. The figure is printed in Pew's own table and this post reproduces it as printed. It does not claim that a respondent-weighted or population-weighted global figure would be different from 46, in either direction or by any amount, because no such figure has been published for this question in this release and this post has not computed one.

It does not claim USA Today misreported the survey. The country figures match, the attribution is there, and the question is described correctly. It does not know why USA Today's sample figures sit 80 above Pew's, only that they do, in both figures, consistently. It did not check the seven-point change over two years that the same sentence reports for the United States, and says nothing about whether that figure holds.

It does not say anything about what AI will actually do to employment in any of the 37 countries. This is a survey of expectations, and the limits of its evidence are the ones Pew states: 37 countries, medians rather than weighted averages for every cross-country figure, and fieldwork that closed on 13 May everywhere except the United States. And it uses nothing from the Topline PDF, the appendix-of-detailed-tables page, or the 16 September short-read, all three of which are named above and none of which supplied a number here.

The Pew report page, its methodology sub-page, the Report PDF, the USA Today article and ThePrint's writeup were fetched and read during this run on 18 September 2026, and every figure and quotation above was checked against the document it came from.