
Photo: XMO
Algorithms now make the decisions.
AI WORKPLACE MONITORING
AI-powered workplace surveillance systems are becoming increasingly common across corporate environments, reshaping how employers monitor productivity, manage performance, and make decisions about redundancies and disciplinary action.
Once limited to basic time-tracking software, these systems now use artificial intelligence to analyse vast amounts of digital behaviour data – including application usage, email and messaging patterns, web browsing activity, and device interaction.

The result is a detailed, continuous picture of how employees work throughout the day – particularly in remote and hybrid settings where physical oversight is limited.
Industry adoption has accelerated since the widespread shift to remote work during the ‘pandemic’, with employers turning to tools such as ActivTrak, Teramind, and Hubstaff.

These platforms typically install monitoring agents on company devices, allowing organisations to track active work time, software usage, or capture periodic recordings.
More recently, large enterprise software providers have integrated similar capabilities directly into workplace ecosystems.
Microsoft, for example, offers ‘productivity analytics tools’ within Microsoft 365 environments that aggregate collaboration data from email, chat, and meetings.

Meanwhile, HR platforms such as Workday are increasingly combining workforce analytics with performance management systems, enabling employers to correlate behavioural data with formal performance reviews and organisational planning.

This is known broadly as ‘Human Capital Management’ (HCM), with systems merging behavioural data with formal metrics to give employers unprecedented views of activity.

The use of artificial intelligence is central to this shift.
Rather than simply recording activity, modern systems attempt to interpret it.
AI models classify behaviour into categories such as “productive time”, “focus time”, or “idle time”, and compare individuals against team or organisational baselines.
Some systems generate ‘productivity scores’ or ‘risk indicators’ that highlight employees who deviate significantly from expected patterns.

This has led to growing interest among employers in using such data not only for productivity insights, but also for decision-making around staffing.
In some organisations, sustained low activity scores, reduced engagement, or changes in working patterns are being used as supporting evidence in performance improvement plans, disciplinary procedures, or redundancy assessments. In restructuring exercises, aggregated productivity metrics may be used to justify workforce reductions on efficiency grounds.

The trend has been particularly pronounced in sectors with large remote workforces, including technology, customer support, and professional services.
Just today, it was announced that Meta will be cutting 8,000 jobs as part of a major AI-focused restructure – with employees notified in the middle of the night.

U.S-based companies have announced nearly 50,000 job cuts already this year linked to AI, according to research from outplacement firm, Challenger, Gray & Christmas.
Analysts note that while surveillance technologies existed prior to 2020, their deployment has expanded significantly in both scale and sophistication over the past five years – driven by cost pressures, remote work normalisation, and advances in AI analytics.

This growth of workplace monitoring has raised significant concerns among employment lawyers, trade unions, and privacy advocates.
Critics argue that productivity metrics fail to capture the complexity of knowledge work, where time spent inactive may reflect thinking, planning, or offline collaboration.
There are also concerns that employees may feel pressured to prioritise visible “activity” over meaningful output.
Some organisations implement safeguards like anonymised reporting, aggregated team-level analytics, and restrictions on access to individual-level data.
Despite these safeguards, enforcement is largely reactive, and critics argue that the balance of power remains weighted towards employers, particularly where monitoring is tied directly to performance evaluation or job security.
As AI capabilities continue to evolve, it is expected that workplace surveillance tools will become more predictive – identifying not only what employees have done, but forecasting future performance risks or ‘retention likelihood’.
This raises further questions about fairness, transparency, and the extent to which algorithmic assessments should influence employment decisions.
If you ask me, I’d say AI should never be used in this way – but unfortunately, the spread has become more widespread than most people even realise.
The modern world is filled with systems of machines dictating entire lives by algorithms, and it doesn’t seem like anything is slowing down soon.
SURVEILLANCE AND SOCIAL CREDIT
Invasive surveillance mechanisms used to determine productivity and performance are becoming normalised everywhere, and the tools are improving with each passing year.
A recent examination by The New York Times found that 80% of the 10 largest private U.S. employers track the productivity metrics of individual workers.

Many companies that shifted to work-from-home models during the COVID-19 ‘crisis’ also quickly began using surveillance software to monitor employee activities.
It was not hard to predict that the same companies would continue these practices beyond the scope of restrictions, be it to ‘save on costs’ or as ‘flexibility options’ for employees.
Creating a New Slave Class: Workplaces in ‘Post-Lockdown’ Australia
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As a result, employees risk becoming collateral damage in the push to automate the enterprise, as companies try to impose technologies to keep tabs on employees.

Regulatory frameworks have struggled to keep pace with the technology.
Authorities have previously warned that outdated laws are allowing “unchecked and unchallenged” use of surveillance and automation technologies by employers.
NSW committee finds workplace surveillance outpacing laws
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As always, our laws just can’t keep up with emerging innovations.

It’s not just workplaces doing this, either. We have previously detailed how at least 24 universities in Australia and New Zealand have used some sort of ‘online proctoring tool’.
Online surveillance of university students grows
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Furthermore, over 4 million Australian school students were caught up in an international data mining scheme due to remote learning during lockdown periods.
Millions of Australian school students tracked during lockdown remote learning
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Training the next generation to be good little digital slaves.
ACLU senior policy analyst, Jay Stanley, recently warned of these “nightmarish” surveillance technologies, pointing to surveillance-heavy China as a worst-case scenario.
China is a place where “there is no space between what can be done, and what is done.”

He has a point. This entire push gives me ‘social credit system’ vibes – as human beings are ranked and judged accordingly based on their ‘productive’ and ‘good’ behaviours.
China’s ‘Social Credit System’ Will Soon Reach Australia
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AI advancements have only made the nightmare more efficient and all-seeing, which should be of concern for any Australian who cares about freedom and privacy.
There are still ways around it at present, including the rise of ‘mouse jigglers’ to keep recorded activity moving at all time – but these things won’t last very long in the face of AI.
Automatic ‘mouse jigglers’ help outsmart workplace surveillance
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Today, simple tracking tools that look for mouse movements and typing speeds are being replaced with advanced algorithms that track overall performance and work rate.
We are truly living in a world once only found in science fiction novels – and this isn’t even talking about how the robots themselves are replacing physical staffers too.
It is only a matter of time before your ‘work score’ will be available alongside your ‘credit score’, all linked together with internal and external Digital ID systems.
The once free and open digital realm has become a giant trap for the masses.

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How about monitoring Politicians and other Government employees? See how much time they are wasting.