artificial intelligence – Page 2 – The NEN

Workers say no to increased surveillance since COVID-19

New TUC polling reveals majority of workers say they have experienced surveillance in the past year

Overwhelming support for stronger regulation to protect workers from punitive use of AI and surveillance tech
Post Office scandal must be a turning point on uncritical use of worker monitoring tech, says TUC

Intrusive worker surveillance tech and AI risks “spiralling out of control” without stronger regulation to protect workers, the TUC has warned. Left unchecked, the union body says that these technologies could lead to widespread discrimination, work intensification and unfair treatment.

The warning comes as the TUC publishes new polling, conducted by Britain Thinks, which reveals an overwhelming majority of workers (60 per cent) believe they have been subject to some form of surveillance and monitoring at their current or most recent job.

The TUC says workplace surveillance tech took off during the pandemic as employers transferred to more remote forms of work.

Surveillance can include monitoring of emails and files, webcams on work computers, tracking of when and how much a worker is typing, calls made and movements made by the worker (using CCTV and trackable devices).

Three in 10 (28 per cent) agree monitoring and surveillance at work has increased since Covid – and young workers are particularly likely to agree (36 per cent of 18-34 year olds).

There has been a notable increase in workers reporting surveillance and monitoring in the past year alone (60 per cent in 2021 compared to 53 per cent 2020).

In particular, more workers are reporting monitoring of staff devices (24 per cent to 20 per cent) and monitoring of phone calls (14 per cent to 11 per cent) compared to 2020.

In calling for stronger regulation, the TUC highlights the recent Post Office scandal which saw hundreds wrongly prosecuted for theft and false accounting after a software error – and says it must be a turning point on uncritical use of worker monitoring tech and AI.

Creeping role of surveillance

The creeping role of AI and tech-driven workplace surveillance is now spreading far beyond the gig economy into the rest of the labour market, according to the TUC.

The following sectors have the greatest proportion of workers reporting surveillance:

financial services (74 per cent)
wholesale and retail (73 per cent)
utilities (73 per cent)

The union body warns of a huge lack of transparency over the use of AI at work, with many staff left in the dark over how surveillance tech is being used to make decisions that directly affect them.

The use of automated decision making via AI includes selecting candidates for interview, day-to-day line management, performance ratings, shift allocation and deciding who is disciplined or made redundant.

The TUC adds that AI-powered technologies are currently being used to analyse facial expressions, tone of voice and accents to assess candidates’ suitability for roles.

To combat the rise of workplace surveillance tech and “management by algorithm”, the TUC is calling for:

A statutory duty to consult trade unions before an employer introduces the use of artificial intelligence and automated decision-making systems.
An employment bill which includes the right to disconnect, alongside digital rights to improve transparency around use of surveillance tech
A universal right to human review of high-risk decisions made by technology

The TUC points out that the government recently consulted on diluting General Data Protection Regulation (GDPR) as part of its post-Brexit divergence agenda, despite it providing some key protections for workers against surveillance tech.

The EU is currently putting in place laws dealing specifically with the use of AI, whereas the UK does not have anything like this. The TUC says this is yet another example of the UK falling behind its EU counterparts on workers’ rights.

There is significant and growing support among workers for stronger regulation of AI and tech-driven workplace surveillance:

Eight in ten (82 per cent) now support a legal requirement to consult before introducing monitoring (compared to 75 per cent in 2020)
Eight in 10 (77 per cent) support no monitoring outside working hours, suggesting strong support for a right to disconnect (compared to 72 per cent in 2020)
Seven in 10 (72 per cent) say that without careful regulation, using technology to make decisions about workers could increase unfair treatment (compared to 61 per cent 2020).

Last year the TUC launched its manifesto, Dignity at work and the AI revolution, for the fair and transparent use of AI at work.

TUC General Secretary Frances O’Grady said: “Worker surveillance tech has taken off during this pandemic – and now risks spiralling out of control.

“Employers are delegating serious decisions to algorithms – such as recruitment, promotions and sometimes even sackings.

“The Post Office scandal must be a turning point. Nobody should have their livelihood taken away by technology.

“Workers and unions must be properly consulted on the use of AI, and be protected from its punitive ways of working.

“And it’s time for ministers to bring forward the long-awaited employment bill to give workers a right to disconnect and properly switch off outside of working hours.”

INEOS FPS At Grangemouth rolls out AI to reduce emissions

INEOS FPS has committed to reduce emissions from its operations to Net Zero by 2045
INEOS has already made progress, with emissions reductions of 37% since it acquired the site in 2005
The deployment of innovative Artificial Intelligence (AI) technology will further reduce emissions from its operations, demonstrating the company’s commitment to meeting UK/ Scottish Government targets

INEOS FPS has announced plans to deploy innovative Artificial Intelligence (AI)-driven optimisation technology at its Kinneil Terminal in Grangemouth that will deliver further carbon emissions reductions from its operations.

The decision follows the announcement of INEOS’ commitment to reduce greenhouse gas emissions from its operations in Grangemouth by more than 60% by 2030 as it targets Net Zero by 2045.

As part of its road map, the business is already making significant investments in emissions reduction projects at Grangemouth and deploying AI technology at Kinneil is another tool that will enable it to achieve the next phase of the transition to Net Zero.

Working with data analytics experts, OPEX Group, INEOS FPS will deploy the firm’s emissions.AI software, which optimises complex industrial facilities to deliver lower carbon emissions.

A real benefit emissions.AI will bring to INEOS’ systems is the way the tool calculates lowest achievable emissions; learning from the information received from hundreds of data points across our processes and always looking for what can be done better.

We believe that once the new software is fully integrated there is the potential to identify up to a 10% reduction in existing emissions – with further opportunities thereafter.

Opex Group’s emissions.AI software is leading edge technology. It will continuously monitor energy use across the Kinneil Terminal to pinpoint opportunities to minimise fuel and power consumption and further optimise plant operations. As well as having access to real time emissions data in greater detail the software will allow INEOS FPS’ operational teams to know when and where to optimise processes and plant for lower emissions.

Andrew Gardner, Chief Executive at INEOS FPS commented; “The installation of the emissions.AI software takes energy management to a new level, that will lead to significant CO₂ savings.

“We are committed to delivering our roadmap to net zero and see technology as a key enabler to achieving our decarbonisation goals. Across our organisation we are embedding a culture of carbon awareness, including as part of daily operations. AI will assist our teams in unlocking immediate operational emissions savings by making emissions data instantly available to them.”

Chris Ayres, Chief Customer Officer at OPEX said: “We are delighted to support INEOS in their drive to reduce carbon emissions. Turning existing operational data into actionable emissions intelligence will give INEOS FPS’ teams access to the information they need to drive faster and better informed operational decisions, and get after day-to-day emissions savings opportunities.

“Data holds the key to empowering operations teams to contribute to decarbonisation targets. To gain a much deeper understanding of the emissions profile of their assets and identify the actions they can take to make a difference, today.”

Data science scholarships on offer to bright minds in Scotland

EXPLORE Data Science Academy (EDSA) is investing up to £250,000 in the strongest and highest achieving graduates in Scotland by offering as many as 40 free scholarships for its six- month online data science courses.

Applications are open now until the 6th June 2021.

EDSA is inviting top graduates that have excelled in their studies and consistently performed well academically to apply and expand their knowledge in Data Science. The EDSA has trained over 1000 young data scientists in South Africa since 2017 and has a graduate employment rate of over 90% at above average starting salaries.

Its courses were recently recognised by Amazon Web Services (AWS), which has partnered with EDSA to offer data science learning to young Africans.

“We believe that our data science course formula, which includes self-study, team challenges, real world problem solving, and world class facilitators, can produce similar results in the UK,” said Shaun Dippnall, CEO of EDSA.

“The higher education system is not producing a sufficient number of work-ready graduates. Our courses are designed to ensure that our students, once graduated, have both the technical and practical skills needed in the workplace,” Dippnall adds.

On completion, the EDSA will assist graduates to find employment through its network.

Skills shortages

A recent survey found that 73% of UK firms believe they lack the talent to complete AI and data science initiatives. EXPLORE Data Science Academy is bridging that gap by offering a suite of comprehensive online courses including Data Science, Data Engineering, Data Analytics, and Business Intelligence, that deliver specialist training in a real-world environment.

Dippnall believes this is an ideal opportunity for highly talented Britons to top up their skills and embark on an exciting career in one of the most sought-after careers at no cost.

“As data becomes the currency of modern business, the race to become data-driven has seen organisations investing heavily in core analytics skills, but lack of support, funding and time available for upskilling are cited as current challenges within the UK data science community,” Dippnall says.

Real world problem solving

EDSA’s courses are practical and deal with real-world problems in business. “The innovative design of our learning platforms and the passion of our scientist facilitators equip EXPLORE students to do great things. Facilitators are experienced in tackling real-world problems and skilfully mentor learners throughout the programme,” he adds.

While the EXPLORE Data Science Academy is new to the UK, its consultancy division EXPLORE AI has been delivering artificial intelligence solutions for Britain’s largest water utility supplier, Thames Water, as part of a project to monitor the supply and demand on its network. There are more than 70 data scientists from EXPLORE AI working for Thames Water, many of which graduated from EDSA.

“The Thames Water success story validates EDSA’s decision to expand out of the South African context and take its place on the world stage. We are excited about our entry into the UK market and I encourage exceptional graduates to apply. This could well be the gateway for 40 such candidates to embark on a thrilling and rewarding career – at no cost. What have you got to lose?” concludes Dippnall.

Data Science Course details

Learners will gain an overview of Data Science and Machine Learning – the skills required to be a data scientist. In the Fundamentals phase they learn how to clean, analyse and visualise data as well as how to effectively communicate the findings. During Machine Learning, students solve real-world problems by building regression, classification and unsupervised learning algorithms in Python. This involves data exploration insight building, improving and communicating models from a raw and unstructured dataset.

Topics Covered:

Data Science Fundamentals

SQL – Create and query a SQL database to extract valuable information
Python Programming – Create Python functions to process and analyse datasets
Visualisation – Building dynamic and interactive dashboards using Power BI

Machine Learning

Regression – Learn about linear regression, variable selection, feature engineering, regularisation, decision trees, parametric methods, ensemble methods and bootstrapping. Build regression models and test the results of forecasts.
Classification – Learn about logistic regression, natural language processing, decision trees, support vectors, neural networks, ensemble methods and hyperparameter tuning. Build and optimise classification models to improve the accuracy of predictions.
Unsupervised Learning – Learn to apply unsupervised techniques, clustering, dimensionality reduction and recommendation systems to gather insight and derive patterns from unstructured data

Have what it takes to be a data scientist?

To apply for a free slot in this world class data science course, applicants must go to https://explore-datascience.net/ and undertake an aptitude test to qualify for selection.

The scholarship application window is open now until and the 6^th June.

See https://www.youtube.com/watch?v=tCkwnPur7jA for more information about EDSA’s courses.