Forget all that stuff about £700million and 1,300 new Probation Officers - the answer as we now know is AI and Justice Transcribe is boosting productivity amazingly!
Justice Transcribe has saved an estimated 266,667 working hours across more than 1.6 million probation meetings since its rollout, according to the National Audit Office. The Ministry of Justice projects the tool will save around 450,000 hours annually for frontline officers.
Ok, there are one or two problems:-
i.e. shitloads of extra work as highlighted by the NAO report: "the pilot... recommended regular quality assurance audits and training on how to undertake a meaningful human review. Training and guidance materials emphasise the importance of reviewing the AI notes and the app included reminders for staff to do this at the point of use. For individual meetings, probation officers are expected to review the outputs from the tool before they add them to the national case management system."
There'll now be new well-paid managerial-level posts created for the chosen chumocrats who will deliver JT training & guidance for the frontline monkeys... and, of course, send a shitload of new emails reminding those monkeys to "review the outputs from the tool before they add them to the national case management system."
It aint gonna end well...
*****
Justice transcribe still requires you to review and edit what it has recorded…. That still takes time…. which it often records names / places wrong. It also doesn’t capture body language or HOW things are said/ the tone. That can be so revealing.
“no intervention completed due to crisis management and stabilisation”… you could play AI buzzword/ buzz phrase bingo!!!
Ok, lets play AI buzzword/ buzz phrase bingo!!!
Over to you.....Anon 08:08 - I’ll have ‘meaningful engagement’, ‘explored protective factors’, ‘emotional regulation’, ‘strengths-based approach’, ‘identified areas for further exploration’ and, of course, ‘crisis management and stabilisation’ for a full house, please!
https://www.theguardian.com/commentisfree/2026/oct/20/ai-supposed-to-save-time-opposite-government-uk?CMP=Share_AndroidApp_Ot
ReplyDeleteDon’t be fooled. The AI that was supposed to save us time is doing just the opposite
DeleteThe government says it can transform the state with AI, but it is no match for the resulting stream of machine-generated slop. And we all pay the cost
Another morning, another avalanche of emails. Even after a guilty cull, my inbox is sitting at well over 7,000, but lately I’ve started subscribing to the Quentin Crisp theory of housework: why bother, when after four years or so you stop noticing the accumulating dust? Empty inboxes just fill up again anyway.
In theory, email was supposed to save hours of meetings, phone calls and standing over photocopiers. Instead, we just spend hours deleting stuff people wouldn’t have bothered telling us if it had meant picking up the phone, but which they can now spam to their entire database at the click of a button. The glorious ease and convenience of being able to reach the world in seconds came, we now know, with the inconvenience of them being able to reach you right back.
And therein lies the challenge to the government’s hopes of AI helping to transform the machinery of the state on the cheap, saving not only time but billions of pounds in public money. It’s early days, but AI seems not so much to be streamlining public service delivery as gumming it up – partly because, as was once the case with email, the public is using it right back at them.
In a Substack post last week, the former civil servant Sam Freedman noted that governments around the world seem to be experiencing unusual surges in complaints, requests and responses to regulatory and official bodies since the adoption of ChatGPT. It’s the same story in the courts, with employment tribunal cases in England, Scotland and Wales reportedly rising by 39% in a year thanks in part to claimants using AI to draft claims, while magistrates and judges face a wave of people who can’t afford lawyers using ChatGPT to build cases that often don’t make sense. And all of this needs patient disentangling by a human, on the grounds that just because a defendant is citing precedents that don’t exist, it doesn’t mean there isn’t a genuine grievance buried in there somewhere.
Whitehall special advisers complain of departments drowning in AI-generated freedom of information requests, an abuse of a system originally intended to empower individuals. MPs’ offices are similarly swamped by AI-generated letters, all of which need to be read by humans for fear of missing something important from a constituent.
How long before public consultations on changing the law become so spammed by slop that they are in essence useless as a measure of what the country actually thinks? There’s a fine line between the noble aim of making it easier for individuals to interact with an otherwise remote state, and making it so easy that the result is an uncontrollable firehose of meaningless machine-generated guff.
The obvious answer to this kind of AI flooding is getting AI tools to detect or sift it, but that doesn’t always work when dealing with potentially vulnerable human beings. Constituents who use AI to express themselves in more fancy-sounding language when writing to their MP, for example, still have the right to expect a personal response from a human being.
Employers who thought they were being smart by getting AI to sift job applications, meanwhile, are reaping what they sowed, as resentful applicants automate their end of things too and spray-gun applications across the board, rather than concentrating on the jobs they really want. Now neither side can separate the wheat from an avalanche of chaff.
The risk of paralysis is likely only to increase if the public starts adopting agentic AI in the kind of numbers big tech fondly imagines. Early adopters might well find agents save them time and hassle. But shortcuts stop being shortcuts once everyone else is using them too, and risk turning into bottlenecks instead. Think of cars, which have vastly shortened journey times compared with travelling by horseback, except in cities at rush hour when too many other people are also trying to shorten theirs. By 2018, central London daytime traffic was moving on average at just over 7mph – about the same speed as a trotting pony.
DeleteHistorically, humans have always learned to develop ways around problems of our own making. We have spam filters for email, congestion charges to keep cars out of cities, and in the long term we could well figure out what kind of frictions we need to put back in the system to make it possible to live with the impact of AI.
I’ll have ‘meaningful engagement’, ‘explored protective factors’, ‘emotional regulation’, ‘strengths-based approach’, ‘identified areas for further exploration’ and, of course, ‘crisis management and stabilisation’ for a full house, please!
ReplyDeleteMaybe the biggest buzz phrase of all is ‘efficiency savings’.
The Guardian article raises a rather uncomfortable question about AI. Just because something can be produced more quickly doesn’t necessarily mean it creates less work. Sometimes it simply redistributes that work, often to the very people who are already struggling with excessive demands. And that brings us neatly to Justice Transcribe.
We’re presented with huge figures about hours saved, but what's exactly being measured? Does that include the time spent reviewing lengthy narratives, correcting inaccuracies and removing generic language? Or are we simply assuming that meaningful human review takes place because the process says it should?
My concern is that the polished, professional sounding language can create a false sense of confidence in what’s been recorded. When every interaction reads like a carefully structured therapeutic intervention, how critically are we actually examining whether it reflects what happened?
There’s a considerable difference between reviewing a record for accuracy and being impressed by how well it reads.
Because a PP cannot simply assume that a beautifully constructed account is an accurate one. We remain professionally accountable for what goes onto the case record and what others may subsequently rely upon.
There is also something rather troubling about the apparent need to turn every conversation into an elaborate account of meaningful intervention.
Sometimes supervision involves difficult conversations, frustration, uncertainty or very little apparent progress. Sometimes it involves listening, observing and recognising something that isn’t captured by the words spoken. Professional judgement includes knowing the significance of those things without dressing them up in therapeutic terminology.
An impressive narrative isn’t necessarily evidence of impressive practice.
But here’s the bigger question. If Justice Transcribe really does save hundreds of thousands of hours, what happens to those hours?
Do PPs actually regain time to build relationships, undertake meaningful supervision, develop professional judgement and respond to changing circumstances? Or do those theoretical savings simply become another justification for increasing workloads, reducing expectations of staffing capacity and demanding even more from an already overstretched workforce?
Given the current debate about probation being ‘not fit for purpose’, staffing shortages, pay and retention, I think that’s a rather important distinction.
Technology that genuinely gives PPs more time to do their jobs should be welcomed. Technology that merely enables the organisation to claim greater productivity while leaving the underlying pressures untouched is something else entirely.
Perhaps the real bingo winner isn’t ‘crisis management and stabilisation’ after all.
It’s ‘efficiency realised, capacity released, benefits delivered’.
But delivered to who?
House!