Amazon Is Shutting Down Mechanical Turk After 21 Years

Jeff Bezos called it artificial artificial intelligence: humans quietly doing the work software could not yet do. Twenty-one years later, the software caught up, and Amazon is closing Mechanical Turk on 30 September.

AWS stopped accepting new registrations on 30 July. SageMaker Ground Truth and Amazon Augmented AI close on the same date, which means Amazon is not trimming a product line, it is leaving human data collection altogether.

What happens to work already in the system

The wind-down has a schedule. Requesters get the standard 30 day HIT approval window on anything completed before the shutdown, so approvals or rejections run until 30 October. Anything untouched after that auto-approves. Transaction history stays accessible until 28 January 2027.

If you have jobs running, that is the calendar to work backwards from.

Why Amazon Mechanical Turk is shutting down

MTurk launched in 2005 and labelled an enormous share of the data that trained the models everyone now uses. The premise cracked when those models got good enough to do the tasks themselves. A 2023 study by researchers in Switzerland found that up to 46% of Mechanical Turk workers were already using AI models to complete their assignments, which is the whole story in one statistic: the platform was paying humans to do work that humans were quietly outsourcing back to machines.

The market moved too. Scale AI, Mercor and Prolific took the annotation business by selling vetted, specialist labour rather than an open marketplace of anonymous microtasks. Frontier labs now want a radiologist or a lawyer marking up training data, not whoever claims the HIT first.

It is worth sitting with the shape of that. The people who trained the systems were replaced by the systems they trained, and the replacement was economic rather than dramatic: the work simply stopped being worth $0.02 a task to anybody.

What it signals about where the money goes

Data labelling has not disappeared, it has moved upmarket and got expensive. That fits the wider pattern of AI spend shifting from cheap volume to specialised capability, the same shift visible in OpenAI building its own inference silicon and in the kind of reasoning work behind OpenAI's Astra clearing unsolved maths problems. If you would rather keep your own data out of that pipeline entirely, our guide to running a local LLM on a Mac is the practical starting point.

MTurk gets 33 more days.