It’s hard to build a service powered by artificial intelligence. So hard, in fact, that some startups have worked out it’s cheaper and easier to get humans to behave like robots than it is to get machines to behave like humans.

“Using a human to do the job lets you skip over a load of technical and business development challenges. It doesn’t scale, obviously, but it allows you to build something and skip the hard part early on,” said Gregory Koberger, CEO of ReadMe, who says he has come across a lot of “pseudo-AIs”.

“It’s essentially prototyping the AI with human beings,” he said.

This practice was brought to the fore this week in a Wall Street Journal articlehighlighting the hundreds of third-party app developers that Google allows to access people’s inboxes.

In the case of the San Jose-based company Edison Software, artificial intelligence engineers went through the personal email messages of hundreds of users – with their identities redacted – to improve a “smart replies” feature. The company did not mention that humans would view users’ emails in its privacy policy.

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The third parties highlighted in the WSJ article are far from the first ones to do it. In 2008, Spinvox, a company that converted voicemails into text messages, was accused of using humans in overseas call centres rather than machines to do its work.

In 2016, Bloomberg highlighted the plight of the humans spending 12 hours a day pretending to be chatbots for calendar scheduling services such as X.ai and Clara. The job was so mind-numbing that human employees said they were looking forward to being replaced by bots.

In 2017, the business expense management app Expensify admitted that it had been using humans to transcribe at least some of the receipts it claimed to process using its “smartscan technology”. Scans of the receipts were being posted to Amazon’s Mechanical Turk crowdsourced labour tool, where low-paid workers were reading and transcribing them.

“I wonder if Expensify SmartScan users know MTurk workers enter their receipts,” said Rochelle LaPlante, a “Turker” and advocate for gig economy workers on Twitter. “I’m looking at someone’s Uber receipt with their full name, pick-up and drop-off addresses.”

Even Facebook, which has invested heavily in AI, relied on humans for its virtual assistant for Messenger, M.

In some cases, humans are used to train the AI system and improve its accuracy. A company called Scale offers a bank of human workers to provide training data for self-driving cars and other AI-powered systems. “Scalers” will, for example, look at camera or sensor feeds and label cars, pedestrians and cyclists in the frame. With enough of this human calibration, the AI will learn to recognise these objects itself.

In other cases, companies fake it until they make it, telling investors and users they have developed a scalable AI technology while secretly relying on human intelligence.

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