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Agentic AI to make data uplink the next mobile bottleneck | Computer Weekly

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Agentic AI to make data uplink the next mobile bottleneck | Computer Weekly


One of the consequences of artificial intelligence (AI) systems becoming capable of reasoning, planning and executing tasks autonomously is that mobile traffic patterns are changing noticeably, with uplink being of growing importance.

A study from InterDigital has shown how the emergence of agentic AI will redefine the demands placed on devices, networks and cloud infrastructure. Among the findings of the The distributed network shift enabling AI on device report, conducted by ABI Research for the InterDigital, was that the rapid adoption of agentic systems – which is expected to increase across enterprise and consumer markets over the next three years – was increasing uplink traffic from AI devices, changing the way modern networks operate. The result will be a reimagining of network design.

The study noted that modern mobile networks have historically been optimised for downlink throughput and video delivery. However, unlike traditional mobile applications that primarily consume data via downlink, agentic AI systems continuously generate and exchange contextual information to enable real-time reasoning and decision-making. Therefore, as AI devices generate increasing volumes of upstream data, networks risk becoming overloaded, leading to higher latency and costs.

The study found four main devices driving uplink traffic: smart glasses, wearables, smartphones, IoT sensors and devices. Smart glasses continuously capture video, images and environmental context, sending data upstream for real-time AI inference and assistance. ABI Research predicts 70 million smart glasses shipments by 2030, with cellular-enabled devices representing more than 12% of shipments.

By contrast, wearables – including next-generation tech that collects voice, biometric and contextual signals – support persistent agentic AI interactions. Smartphones increasingly transmit multimodal inputs such as voice, photos, video and sensor data to cloud and edge AI systems. In their operation, IoT sensors and devices continuously stream operational or environmental data to AI models for analysis, automation and decision-making.

The study also found uplink pressures are already visible in video-heavy applications such as livestreaming and real-time video collaboration, where many users uploading simultaneously can create localised mobile cell congestion. It added that unlike these temporary spikes, agentic AI systems will generate continuous upstream data exchanges from connected devices, potentially creating sustained pressure on uplink capacity.

The report suggested that to meet AI demands of modern devices, the industry must transition toward distributed intelligence architectures, where AI workloads are orchestrated across on-device processors, and cloud platforms based on their complexity. It said that embedding intelligence deeper into network infrastructure will ensure AI-enabled applications can operate efficiently without compromising on performance.

The study observed that as the entire mobile ecosystem continues to innovate and integrate the latest AI technology at pace, ensuring a coherent and complementary direction of travel is essential to enabling future AI applications and their associated experiences.

This is particularly seen as the case for 6G networks, which will be designed to make smartphones better at Mobile Broadband (MBB) access by improving network speeds, reducing latency and refining the battery life of devices.

However, InterDigital cautioned this is just the foundation on which additional services will be built. Integrating AI in the network will allow smartphones to offload demanding applications to the edge of the network – as well as into centralised locations – to ensure optimal resource utilisation, enabling a distributed intelligence fabric.

“Agentic AI introduces a new set of requirements for both networks and devices,” said Larbi Belkhit, and Paul Schell, senior analysts at ABI Research and co-authors of the report. “Supporting autonomous AI systems will demand far more distributed computing architectures and significantly more intelligent networks. Operators will need to manage increasingly symmetrical traffic patterns while enabling real-time AI workloads across device, edge and cloud.”

“Agentic AI marks the next phase in the evolution of intelligent connectivity,” said InterDigital chief technology officer Rajesh Pankaj. “Intelligence must be distributed across devices, networks and the cloud, and delivering these AI-enhanced services efficiently will require a new computing architecture that balances performance, latency and energy efficiency.”



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Essex Police halts live facial recognition over bias and accuracy risks | Computer Weekly

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March 20, 2026

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Essex Police halts live facial recognition over bias and accuracy risks | Computer Weekly


Essex Police has paused its use of live facial recognition (LFR) technology after identifying potential accuracy and bias risks.

The force’s suspension of its LFR system – provided by Israeli biometrics firm Corsight – was revealed in an audit document published by the Information Commissioner’s Office (ICO), which said Essex Police must work to “reduce the risks” identified before continuing with future deployments.

A list of LFR deployments from Essex Police shows the last time the force used the technology was on 26 August 2025, meaning its deployments had already been paused by the time the ICO carried out its audit that November.

While it is currently unclear what specifically prompted the force to suspend its LFR use, Computer Weekly exclusively reported in May 2025 that Essex Police had failed to properly consider its potentially discriminatory impacts, after a “clearly inadequate” equality impact assessment (EIA) was obtained via Freedom of Information rules by privacy campaign group Big Brother Watch.

Experts criticised the document at the time for being “incoherent”, failing to look at the systemic equalities impacts of the technology, and relying exclusively on testing of entirely different software algorithms used by other police forces trained on different populations.

The force was also criticised for “parroting misleading claims” from the supplier about the LFR system’s lack of bias, with the National Institute of Standards and Technology – a body widely recognised as the gold standard for LFR testing, where all of the testing data is publicly shared – holding no information to support the accuracy figures cited by Corsight, or its claim to essentially have the least-biased algorithm available.

Big Brother Watch alleged at the time that these issues taken together meant the force had likely failed to fulfil its public sector equality duty to consider how its policies and practices could be discriminatory.

Independent testing

Responding to the criticisms, the force said at the time that it was continuing to carry out evaluations, noting that both the National Physical Laboratory (NPL) and Cambridge University had been commissioned to conduct further independent testing of its system.

According to the results of that Cambridge study – published on 12 March 2026 – the system was more likely to correctly identify men than women, and was “statistically significantly more likely to correctly identify black participants than participants from other ethnic groups”.

Matt Bland, a criminologist involved in the study, said: “If you’re an offender passing facial recognition cameras which are set up as they have been in Essex, the chances of being identified as being on a police watchlist are greater if you’re black. To me, that warrants further investigation.”

By contrast, the further NPL testing – also published in March 2026 – found black men were most likely to be correctly matched by the system and white men least likely, but noted that the disparity was not statistically significant.

Computer Weekly contacted the force to ask what specifically prompted the LFR suspension decision, including whether it was the study results or previous criticisms of the EIA.

“In line with our commitment to our Public Sector Equality Duty, Essex Police commissioned two independent studies which were completed by academia,” a spokesperson said. “The first of these indicated there was a potential bias in the positive identification rate, while the second suggested there was no statistical relevant bias in the results.

“Based on the fact there was potential bias, the force decided to pause deployments while we worked with the algorithm software provider to review the results and seek to update the software,” they added. “We then sought further academic assessment.

“As a result of this work, we have revised our policies and procedures and are now confident that we can start deploying this important technology as part of policing operations to trace and arrest wanted criminals. We will continue to monitor all results to ensure there is no risk of bias against any one section of the community.”

Responding to news of the suspension, Jake Hurfurt, the head of research and investigations at Big Brother Watch, said: “Police across the country must take note of this fiasco. AI [artificial intelligence] surveillance that is experimental, untested, inaccurate or potentially biased has no place on our streets.”

Ramping up deployments without debate

While the use of LFR by police – beginning with the Met’s deployment at Notting Hill Carnival in August 2016 – has already ramped up in recent years, there has so far been minimal public debate or consultation, with the Home Office claiming for years that there is already “comprehensive” legal framework in place.

However, in December 2025, the Home Office launched a 10-week consultation on the use of LFR by UK police, allowing interested parties and members of the public to share their views on how the controversial technology should be regulated.

The department has said that although a “patchwork” legal framework for police facial recognition exists (including for the increasing use of the retrospective and “operator-initiated” versions of the technology), it does not give police themselves the confidence to “use it at significantly greater scale … nor does it consistently give the public the confidence that it will be used responsibly”.

It added that the current rules governing police LFR use are “complicated and difficult to understand”, and that an ordinary member of the public would be required to read four pieces of legislation, police national guidance documents and a range of detailed legal or data protection documents from individual forces to fully understand the basis for LFR use on their high streets.

Before the consultation had even closed, however, the Home Office announced plans for the massive roll-out of AI and facial-recognition technologies as part of sweeping reforms to the UK’s “broken” policing system.

Under the proposals – announced in late January 2026, nearly three weeks before the consultation closed – the Home Office will increase the number of LFR vans available to police from 10 to 50; set up a new National Centre for AI in Policing – to be known as Police.AI – to build, test and assure AI models for policing contexts; and invest £115m over three years to help identify, test and scale new AI technologies in policing.

‘Panopticon’ vision

In a recent interview with former prime minister Tony Blair, UK home secretary Shabana Mahmood described her ambition to use technologies such as AI and LFR to achieve Jeremy Bentham’s vision of a “panopticon”, referring to his proposed prison design that would allow a single, unseen guard to silently observe every prisoner at once.

Typically used today as a metaphor for authoritarian control, the underpinning idea of the panopticon is that by instilling a perpetual sense of being watched among the inmates, they would behave as the authorities wanted.

“When I was in justice, my ultimate vision for that part of the criminal justice system was to achieve, by means of AI and technology, what Jeremy Bentham tried to do with his panopticon,” Mahmood told Blair. “That is that the eyes of the state can be on you at all times.”



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The Corsair 4000D RS PC Case Keeps Your System Cool

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March 20, 2026

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The original Corsair 4000D was my favorite computer case ever. It boasted excellent cooling, a simple but refined look, and an appealing price. For just an extra $20, the new Frame 4000D RS promises several major upgrades to both usability and flexibility, but we all know how sequels sometimes turn out.

Having built up a new test system inside, I can tell you that the case is technically just as good, particularly in the hands of any experienced builder. The cooling and component support is second to none, and some of the usability features are so novel I can’t believe other case makers haven’t thought of them before.

That said, I don’t feel like the Frame version of this case has the elegant simplicity that I found so delightful in the old 4000D. It’s now made to please the high-end computing nerd, with wider component support, better cooling, and a refreshed new look with fancier machining. The upside is clear: folks get improved component support, more build options, and the same suave style. The tradeoff is a slightly noisier case with a few usability complications.

Regardless of minor complaints, the new Frame 4000D RS is still one of the best cases you can build in, and I’ll happily recommend it going forward, even if I wish it were an addition to Corsair’s cases, rather than a replacement.

The Space Between

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Photograph: Brad Bourque

The biggest compliment I can give the Frame 4000D RS is, with a few exceptions, I never had to cram my hands into any weird spaces or bend cables into weird angles to make them fit. The major contributing factor to that is a variety of movable plates in places that didn’t used to move on the old case, or most cases, for that matter. It’s an area where Corsair cases have always excelled, but some thoughtful additions here make it truer than ever.



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Everywoman announces 2026 Women in Technology Awards winners | Computer Weekly

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March 20, 2026

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Everywoman announces 2026 Women in Technology Awards winners | Computer Weekly


Everywoman has announced the winners of its 2026 Everywoman in Technology Awards, sponsored by Salesforce.

For the past 16 years, professional network Everywoman has been showcasing talented women in the technology sector for their ongoing work, both to shine a light on the amazing women already in the industry and to encourage others to seek technology roles.

The number of women in the UK’s technology sector, though slowly increasing, is still below 25%, and with rapidly growing technologies such as artificial intelligence (AI), it’s becoming increasingly important to ensure the makeup of those working in technology matches its varied user base.

Increasing the number of visible and accessible role models of all types has been cited as being one of the ways to encourage women into the tech and digital space, with experts stating that young people are more likely to consider these careers for themselves when they can see others like them across the technology sector.

Nicole Goodwin and Sophie Catto, joint managing directors of AllBright Everywoman, said: “Remarkable women across the technology sector are developing innovations that have the power to transform how we live and work, while building systems that generate significant value for the UK economy. Many of this year’s finalists are also leading inspiring initiatives that equip girls with the skills and confidence to use technology as a pathway out of poverty. 

“By bringing this powerful community of tech leaders and visionaries together through the Salesforce everywoman in Technology Awards, we celebrate their achievements and amplify their stories, creating visible role models who can inspire the next generation to pursue careers in STEM.” 

Everywoman intentionally chooses winners not just from leadership or C-suite roles, but also students, entrepreneurs and innovators, increasing the visibility of role models to help young women or those outside of the sector see themselves represented, making them more likely to consider a tech career for themselves.

The winners of this year’s Salesforce Everywoman in Technology Awards are as follows:

AI Champion 

  • Nausheen Basha, research associate, Imperial College London

Apprentice Award

  • Kelly Howes, junior software engineer apprentice, Compare The Market

Cyber Security Award

  • Rebecca Phelps, senior cyber lead, BAE Systems

CTO/CIO of the Year Award

  • Nicola Emsley, CIO – mortgages, savings and insurance (BUK), Barclays

Digital Star Award

  • Louise Edwards, vehicle specialist, 165 Regiment RLC

Digital Transformation Leader Award

  • Kerry Casey-Foulkes, director of transformation enablement, Virgin Media O2

Software Engineer Award

  • Chiamaka Okenwa, software engineer, Monzo

Entrepreneur Award

  • Fiona Roach Canning, co-founder and CEO, Pollinate

Innovator Award

  • Ganna Pogrebna, professor, David Trimble chair and executive director, AI and Cyber Futures Institute, Queens University Belfast

Leader Award

  • Lara Beers, vice-president global sales, Kraken

Male Agent of Change Award

  • Tim Ibell, dean of the Faculty of Engineering & Design, University of Bath

One to Watch Award

Rising Star Award

  • Danita Samuel Prakash, IT deskside engineer, HCL Tech

Tech For Good Award 

  • Yasmin Mohamud, mentor, KastanTech AI

Team Leader Award

  • Kripa Balachandran, head of product, Mission Zero Technologies

The Woman of the Year Award was given to Aji Bawo, head of commercial product at Tesco, who has not only used technology as a tool to push for innovation in the retail space, but also to give girls in underdeveloped countries access to education.



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