How AI is disrupting the Middle East job market

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In an article on How AI is disrupting the Middle East job market, ZAWYA gives a clear snapshot of the prevailing atmosphere of human resources treatment before employment.

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From ChatGPT to career matching: How AI is disrupting the Middle East job market

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From ChatGPT to career matching: How AI is disrupting the Middle East job market

 

The adoption of Artificial Intelligence (AI) in recruitment has witnessed a meteoric rise globally, with a new LinkedIn report stating that job postings referencing AI skills have experienced an uptick in recent months.

Findings of the Future of Work report have revealed that English-language job postings mentioning GPT or ChatGPT have increased by 21 times on the careers platform since November 2022. The report further states that skills required for various jobs across industries have changed by 25% since 2015, with that number expected to reach at least 65% by 2030 due to the rapid development of new technologies like AI.

The Middle East job market is no exception with industry experts stating that there has been a recent ‘surge in demand for skills related to AI and data analysis’ by recruiters in the region.

Changing job description

A recent research paper by global management consulting firm Bain & Company revealed that demand for top tech talent has more than doubled between 2015 and 2019. The nature of the job has also evolved with 40% of the most in-demand jobs today not even existing in 2015.

PwC’s Middle East Workforce Hopes and Fears survey 2023, released in June, also found 52% of the individuals surveyed in the region believing their jobs will change significantly in the next five years, requiring them to acquire new skills and capabilities to boost AI literacy.

“The rise of AI has brought about significant changes in the job market, particularly for employees. Technology is automating routine and repetitive tasks across many industries, potentially leading to the displacement of jobs,” said Kamal Raggad, Chief Executive Officer and Co-founder of RemotePass, a global onboarding and payroll platform for remote teams.

Raggad said: “Simultaneously, there’s a surge demand for skills related to AI and data analysis. Individuals with expertise in machine learning, data science, and AI have become highly sought after. Moreover, many businesses are deploying AI tools to bolster productivity and decision-making, which augments the capabilities of employees in their daily tasks.”

According to Raggad, the landscape is also evolving rapidly for hiring managers, with the emergence of AI paving the way for the creation of novel job roles tailored to harnessing its capabilities. “In the realm of recruitment, AI tools are revolutionising processes by automating tasks like candidate screening, skills assessment, and matching the right candidates to the appropriate roles. Furthermore, to bridge the emerging skill gaps, there’s an increasing emphasis on investment in AI-focused training and upskilling programmes,” he added.

AI-driven platforms

According to a recent study by McKinsey, the MENA region is predicted to witness a significant workforce expansion of 127 million in the next decade, primarily driven by a burgeoning youth population.

As Gen Z enters the workforce, this has further led to an uptick in AI-driven resume building and job search platforms, with companies such as Bayt and GulfTalent using smart features to transform the way candidates and recruiters find, screen and shortlist opportunities.

Last month, Qureos, a UAE-based startup that specialises in personalised career matching across the MENA region, announced the launch of Iris, a recruitment platform that employs advanced AI and machine learning algorithms to aid hiring managers in candidate sourcing and evaluation.

According to the company, Iris can present an average of 47 relevant candidates per search in 26 seconds, ultimately reducing time-to-hire and slashing recruitment costs by up to 43%.

“Recognising that 30% of Middle East respondents, as per a PwC survey, are seeking new career opportunities, Iris serves as a critical catalyst for career advancement in the region,” said Alexander Epure, CEO & Co-founder of Qureos in a statement.

Industries embracing change

According to LinkedIn, industries that are seeing a shift towards AI-skilled members include Technology, Information, and Media, with the US also seeing significant movement in Education (1.2%), Professional Services (0.9%), Financial Services (0.9%), and Manufacturing (0.8%).

When looking at the speed at which members are adding AI skills to their profiles, the report states professionals in Financial Services (30x), Retail (29x), and Wholesale (24x) are pivoting toward AI faster than in Technology, Information, and Media (11x).

“The adoption of AI promises to bring profound changes to the job market. Industries built on repetitive tasks, such as manufacturing, data entry, and customer service, are more susceptible to AI-driven displacement. By contrast, fields that lean heavily on human creativity and interpersonal skills, like healthcare and the arts, might instead see evolving roles,” said Raggad.

He continued: “AI’s swift ascent in the technological world has dual implications. On one hand, there’s a palpable concern over job reductions, especially in sectors like retail and finance, where AI tools like chatbots and algorithmic trading are being swiftly adopted. On the flip side, sectors rooted in creativity, complex problem-solving, and those reliant on a human touch are likely to be more resilient. Moreover, AI’s rise is birthing entirely new sectors in cybersecurity and AI research, signalling a promising horizon for novel avenues of employment.”

(Reporting by Bindu Rai, editing by Brinda Darasha)

(bindu.rai@lseg.com)

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Saudi Arabia is now harnessing AI to combat desertification

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Saudi Arabia is now harnessing AI to combat desertification

The above-featured image is for illustration and is credit to BNN.

 

As desertification poses a significant challenge in the country due to its arid climate and climate change effects, AI-driven analysis of satellite imagery and data will pinpoint areas most susceptible to desertification. Remote sensing technologies will monitor vegetation, rainfall, and plant health changes over time.

First Published Aug 21, 2023 in ASIANET

The Saudi Ministry of Environment has initiated a program that utilizes artificial intelligence (AI) to combat desertification. This collaboration involving the ministry, the National Center for Vegetation Development and Combating Desertification, and the King Abdullah University of Science and Technology intends to assess vegetative cover within Saudi Arabia.

The program aligns with afforestation projects and the “Green Saudi” initiative. As desertification poses a significant challenge in the country due to its arid climate and climate change effects, AI-driven analysis of satellite imagery and data will pinpoint areas most susceptible to desertification.

 

Remote sensing technologies will monitor vegetation, rainfall, and plant health changes over time.

 

Strategies to counter desertification, including tree and shrub planting, water management enhancements, and sustainable agriculture promotion, will be developed.

This AI-powered program represents a crucial step towards Saudi Arabia’s desertification mitigation and sustainability goals. By utilizing advanced technologies, the nation aims to safeguard its natural resources and construct a more sustainable future.

Saudi Arabia is concurrently executing various initiatives against desertification, such as the ambitious “Green Saudi” project, focused on planting 10 billion trees nationwide, and the “National Center for Vegetation Development and Combating Desertification,” dedicated to cultivating drought-resistant plants and refining water management techniques.


A total of 77 initiatives are in motion under the Saudi Green Initiative (SGI) to attain three pivotal targets and effect positive, enduring change. This comprehensive approach encompasses afforestation, biodiversity preservation, emissions reduction, and establishment of new protected areas.

As part of the SGI, Saudi Arabia is translating its vision of a greener future into action, investing in sustainable development.

The forthcoming SGI Forum, scheduled for October 23-24 in Riyadh, represents a landmark event in Saudi Arabia’s endeavour to transition from an oil-based economy to a cleaner, more sustainable one.

The SGI aims to plant 10 billion trees, encompassing 30% of the total land area, create expansive protected zones, conserve coastal marine life, and encourage alternative agriculture. Technology will play a pivotal role in facilitating Saudi Arabia’s transformation into a greener nation.

With its diverse landscapes encompassing forests, pastures, coastlines, and islands across around 2 million square kilometres, Saudi Arabia is harnessing AI and remote sensing to streamline the study and monitoring of its environment.

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Technology is Breaking New Ground in the Construction Industry

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How Technology is Breaking New Ground in the Construction Industry

MELBOURNE, VICTORIA, AUSTRALIA, August 4, 2023/EINPresswire.com/ — The construction industry is undergoing a significant revolution, driven by groundbreaking technological advancements. As professionals in engineering and construction embrace digital transformation, the concept of ‘Construtech’ is reshaping traditional construction techniques and changing the way the industry thinks about its data.

Technological Trends Driving the Future of Construction:

The construction industry is witnessing a rapid shift towards technological innovations that are transforming how projects are planned, designed, and executed. Some of the key technological trends driving the future of construction include:

Construction Management Software:

Construction management software is at the forefront of technological innovations in the construction industry. This advanced software suite streamlines project management processes, allowing construction teams to collaborate seamlessly, manage resources effectively, and monitor project progress in real-time. With features like document management, task tracking, and cost control, construction management software enhances efficiency and productivity throughout the project lifecycle.

Project Management Software for Construction:

Project management software tailored for the construction sector has become an essential tool for managing complex projects. From project planning to scheduling and budgeting, this software empowers construction professionals to optimise project timelines and resources efficiently. Real-time data and analytics enable proactive decision-making, ensuring projects are delivered on time and within budget.

Vendor Management Systems:

Efficient vendor management is crucial for construction companies, and technology is providing solutions to streamline the process. Vendor management systems offer tools to manage supplier information, track performance, and ensure compliance with industry regulations. Vendor management software simplifies the procurement process, ensuring a reliable supply chain for construction projects.

Accounts Payable Software:

Automating accounts payable processes has become a game-changer in the construction industry. Accounts payable software eliminates manual tasks, reduces processing time, and minimises the risk of errors. With streamlined invoice approvals and payment processing, construction companies can improve financial efficiency and cash flow management.

Call Forwarding Software:

Communication is the lifeline of any construction project, and call-forwarding software enhances connectivity and accessibility. This technology allows construction professionals oversight on critical pieces of communication that can otherwise go unchecked. Whether on-site or in the office, call-forwarding software keeps teams connected, promoting seamless communication and collaboration, and helps keeps budgets in check.

How Evolve Construction Management Software is Useful:

Among the pioneers of Construtech, the Evolve Construction Management Software Suite stands out as a game-changing solution for the construction industry in Australia. With a focus on efficiency, productivity, and seamless project management, Evolve Construction Management Software offers comprehensive features, including:

Project Planning and Scheduling: Effortlessly plan and schedule construction projects, allocate resources, and track progress in real-time.

Document Management: Centralise project documents, contracts, and permits for easy access and efficient collaboration.

Cost Control and Budgeting: Monitor project costs, manage budgets, and track expenses to ensure projects stay within financial constraints.

Task Management: Streamline tasks and assign responsibilities, keeping construction teams organised and on track.

Mobile Accessibility: Access project data and updates on the go with mobile compatibility, ensuring effective communication and decision-making even in the field.

“As technology continues to break new ground in the construction industry, we are proud to offer cutting-edge solutions like Evolve Construction Management Software to our clients,” says Bill Kennedy, CEO of Evolve Construction Management. “With the adoption of ‘Construtech’, we aim to empower construction professionals, enhance project efficiency, and drive success in the ever-evolving construction landscape.”

The rise of Construtech signifies an exciting era of innovation and transformation in the construction industry. As professionals embrace these technological trends, the future of construction promises to be more efficient, sustainable, and dynamic.

About Evolve Construction Management:

Evolve Construction Management is a leading construction solutions provider committed to leveraging technology for superior project management and construction excellence. With a focus on client satisfaction and innovation, Evolve Construction Management is at the forefront of driving the construction industry into the digital age.

Bill Kennedy
Evolve Construction Management email

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AI Edge Computing and its Impact on Urban Infrastructure

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The above featured-image is for illustration and is credit to aaeon
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Fagen Wasanni Technologies published this article on AI Edge Computing in urban development that’s worth reading.

Exploring the Future of Smart Cities: The Role and Impact of AI Edge Computing on Urban Infrastructure

As we stand on the precipice of a new era in urban development, the future of smart cities is being shaped by the rapid advancements in technology. One of the most transformative technologies is Artificial Intelligence (AI) Edge Computing, which is poised to have a profound impact on urban infrastructure.

AI Edge Computing is a paradigm that brings computation and data storage closer to the location where it’s needed, to improve response times and save bandwidth. This technology is a game-changer for smart cities, as it allows for real-time data processing, enabling cities to become more efficient, sustainable, and livable.

The integration of AI Edge Computing into urban infrastructure is already underway, with cities around the world beginning to harness its potential. For instance, in the realm of traffic management, AI Edge Computing can analyze data from traffic cameras in real-time to optimize traffic light sequences, reducing congestion and improving road safety. This technology can also predict traffic patterns, allowing city planners to make informed decisions about infrastructure development.

In the context of public safety, AI Edge Computing can be used to enhance surveillance systems. By processing data on the edge, these systems can identify potential threats or criminal activity in real-time, enabling quicker response times from law enforcement agencies. Moreover, AI algorithms can learn and adapt over time, improving their accuracy and effectiveness.

The impact of AI Edge Computing extends to environmental sustainability as well. Smart sensors placed throughout a city can monitor air quality, noise levels, and waste management in real-time. This data can then be processed on the edge, providing city officials with actionable insights to address environmental issues promptly and efficiently.

Furthermore, AI Edge Computing can revolutionize the way cities manage their energy consumption. Smart grids powered by this technology can monitor and analyze energy usage in real-time, optimizing the distribution of energy and reducing waste. This not only leads to significant cost savings but also contributes to a city’s sustainability goals.

However, the implementation of AI Edge Computing in urban infrastructure is not without its challenges. Data privacy and security are major concerns, as the technology involves the collection and processing of vast amounts of data. Cities must ensure robust data protection measures are in place to safeguard citizens’ privacy. Additionally, the deployment of AI Edge Computing requires substantial investment in infrastructure and skills training, which may be a hurdle for cities with limited resources.

Despite these challenges, the potential benefits of AI Edge Computing for smart cities are immense. As cities continue to grow and evolve, this technology will play a pivotal role in shaping urban infrastructure, making cities smarter, safer, and more sustainable.

In conclusion, the future of smart cities is intrinsically linked with the advancement of AI Edge Computing. This technology is set to redefine urban infrastructure, transforming the way cities function and improving the quality of life for their residents. As we move forward into this exciting new era of urban development, the possibilities for what our cities could become are truly limitless.

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Read the Fagen Wasanni Technologies

Compression and complexity: Making sense of Artificial Intelligence

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Compression and complexity: Making sense of Artificial Intelligence

30 June 2023

Sergio Scandizzo

 

 

 

Sergio Scandizzo is Head of Internal Modelling at the European Investment Bank.
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Artificial Intelligence (AI) is expected to have a major impact on Europe in the coming decades. Sergio Scandizzo explains how the concepts of compression, complexity and depth can help us understand the potential implications of AI for our daily lives.

ChatGPT and other instances of ‘generative AI’ have recently taken the internet by storm and, in parallel, generated a mountain of critical comments ranging from the awed and terrified to the unimpressed and disparaging. On one side is the traditional concern that AI can help people cheat, replace human judgement in key decisions for our lives and ultimately damage livelihoods by raising unemployment.

On the other, somehow illogically, although perhaps as an understandable reaction to those fears, critics have tried to find fault with AI’s performance: it cannot solve certain mathematical puzzles (nor can the majority of humans); it writes essays that are predictable and solely based on searching the available literature (as most essays written by humans sadly are); on occasion, it can produce absurd results and reach biased and discriminatory conclusions (otherwise said, it looks as human as it gets).

So, while we tremble at the thought of a dystopic future of technological unemployment, AI-controlled governments, and stultified students, at the same time, we berate current AI applications for not yet being that kind of God-like, infallible intelligence capable of solving any possible problem without fail. The reality is that most ‘failures’ of AI – not being original, basing decisions on existing information, numbly following rules or simply failing several times at complex tasks – are typical human features.

Some critics note that ChatGPT uses the most cited texts, assuming that those are the most scientifically reliable, to come up with answers. True, but what do most people do when they write an essay? First, they read the most cited texts. Similarly, others devise tricky mathematical questions to make the programme produce wrong answers (which are the kind of answers most humans would give). I wonder, therefore, about how many university essays, honestly written by mediocre students in the future, will look like they were written by ChatGPT or some other AI engine and attract unfair accusations of plagiarism.

The objective of Deep Blue or AlphaGO is not to be intelligent, but to play Chess or Go like an intelligent being (us). That they clearly can do so is disquieting perhaps because it suggests that it doesn’t necessarily take human intelligence to play these games, even at the highest level.

The same holds true for so-called creative tasks. If a machine can write a perfectly acceptable, even if not especially original, essay, it gives us pause for thought primarily because it forces us to rethink both the value of certain products of our intelligence and the meaning we attach to them. This is presumably what makes some commentators desperate to find fault in AI’s performance, as if they were keen to reassert the primacy of human intelligence against an existential threat.

Compression as intelligence

Let us try to look at the problem from another perspective. A ‘lossy’ compression algorithm is an algorithm that saves memory space by identifying statistical regularities across a set of data and storing a single copy of patterns that recur multiple times, without being exactly the same. The results of such technique are worse than what you get using a ‘lossless’ compression algorithm, where the original information can be completely reconstructed, but good enough for several practical applications.

It works especially well with images and music, much less well, unsurprisingly, with text and numbers. For example, if a lossy algorithm will store just one copy for several similar-looking areas of a picture, the reconstructed image may become slightly blurred but would still be recognisable overall. On the other hand, if the algorithm stores only the average of several similar numbers in a spreadsheet, the results will likely be useless.

Last February, science fiction author Ted Chiang wrote a very thoughtful piece in which he argued that ChatGPT works very much like a lossy algorithm applied to the internet, whereby it samples a large amount of information and repackages it in the form of text that is not exactly the same as any of the texts available online, but close enough to look both correct and original.

Aside from the fact that he may have stumbled across a definition applicable to a lot of what passes for creativity these days, what is especially intriguing is the use of compression as a metaphor for intelligence and specifically, his observation that the best way to devise a way to efficiently compress a set of data is to understand them.

Indeed, if we need to compress, for instance, the Fibonacci sequence, which is an infinite series in which each number is the sum of the previous two, we would do well by storing only three equations – F0 = 0 (applies only to the first integer), F1 = 1 (applies only to the second integer), and Fn = Fn-1 + Fn-2 (applies to all other integers) – rather than a very long sequence of integers hoping that the next user will guess the rule.

Complexity and depth

In a different context, Nobel laureate Giorgio Parisi argues that the problem of finding the simplest description of a complicated set of data corresponds to finding the scientific laws of the world and is “often taken as a sign of intelligence”. To clarify this idea, Parisi draws on the concept of the algorithmic complexity of a string of symbols.

The latter is defined as the length of the shortest computer programme producing that string as an output. In the Fibonacci sequence example, such a programme will incorporate, in the simplest possible fashion, the three equations above, thereby obtaining a very short description of an (infinite) sequence. On the other hand, if we examine the string “Dkd78wrteilrkvj0-a984ne;tgsro9r2]3”., nm od490jwmeljm io;v9sdo0e,.scvj0povm]]-” the shortest programme most likely will have to look like:

Print (once):

‘Dkd78wrteilrkvj0-a984ne;tgsro9r2]3”., nm od490jwmeljm io;v9sdo0e,.scvj0povm]]-‘

This is longer than the string to be printed. Equally important, however, is the concept of the logical depth of an algorithm, which is the actual amount of CPU time needed to execute it. In the Fibonacci case, while the algorithm is short, the actual amount of CPU required to execute it is potentially infinite as the sequence goes on forever. In the random string above, the algorithm is indeed not very efficient with respect to the length of the string, but its execution is very quick.

We say therefore that the former algorithm has low complexity and high logical depth, while the latter exhibits the opposite features. A good scientific theory has low complexity (it gives the simplest explanation of data) but potentially high logical depth (it explains a lot and may require a very long time to compute all its implications).

As an example, E=mc2 has very low complexity, but an enormous level of logical depth as it implies a very profound and far-reaching set of results. It follows, alas, that in many practical cases we settle for more approximated theories with higher complexity and lower logical depth either because of efficiency (approximated theory may be good enough for certain tasks) or because we simply cannot afford the CPU time required (Parisi gives the example of when we meet a lion on our path and we must make a decision in real time or else become its dinner).

This trade-off between complexity and depth is fundamental in understanding how intelligence, human or otherwise, works, yet most discussions of AI seem to ignore it. ChatGpt may well be, as Chiang says, an imperfectly compressed version of the available data, but so is most of our learning. Intelligence, amongst other things, is the ability to perform those somewhat imperfect compressions that balance cognitive objectives with our natural constraints.


NB: This article gives the views of the author, not the position of EUROPP – European Politics and Policy, the London School of Economics or the European Investment Bank. Featured image credit: Emiliano Vittoriosi on Unsplash


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