ABU DHABI, April 9, 2023 (WAM) — The rapid adoption and daily use of artificial intelligence (AI) applications is disrupting multiple economic sectors, manufacturing industries and business practices, according to new research by TRENDS Research and Advisory. efficiency may be improved. .
“Increasing computational power and the growth of machine learning have also emerged as major factors underpinning the growth of AI. AI’s use of machine learning enables it to train algorithms to perform predictive tasks using historical data as input. This enables relatively accurate prediction of outcomes without the need for human programming intervention,” said research assistant Nouf Yaqoob Al-Saadi, author of the study.
The rise of big data is another factor underpinning the rapid adoption of AI and machine learning in everyday life. Worldwide, he has over 4.95 billion Internet users, and his ever-expanding data sets enable the development of more accurate algorithms and applications.
Examples of AI in everyday life include smart assistants (Apple’s Siri and Amazon’s Alexa), chatbots, predictive mapping apps, personalized e-shopping, AI-driven employment, algorithmic management of taxi services, facial recognition software, automated Includes driving car, data-driven threat protection. security, and many other applications.
However, the rate of development of AI and machine learning highlights several potential policy issues, such as worker migration and labor market disruptions. AI-powered systems can perform tasks previously performed by humans, potentially displacing certain jobs. Given their role as workers, labor market disruptions and worker migration can have far-reaching effects on employment levels, wages, and overall labor market opportunities.
An early analysis of the AI phenomenon found that technology will replace 400 million jobs, using a 2017 high-profile management consulting study that estimated that AI and automation could effectively replace 400 million to 800 million jobs by 2030. The focus was on the potential to replace most jobs globally. Stanford University also notes that by its very nature, AI “performs tasks involving pattern detection, judgment, and optimization. Includes operator.
Most recently, the OECD concluded that the ‘direct displacement’ effect of AI exposure on workers was not statistically significant, but workers with highly developed digital skills were ‘effectively using AI’. and likely find it easier to move to something more valuable that is not automated.” – Added tasks within their profession. Conversely, the prospects for workers with low-level digital skills are hampered by their inability to interact effectively with technology and take advantage of its potential benefits.
This perspective argues that artificial intelligence and machine learning will not replace workers in the traditional sense. Rather, the effect of technology is to coordinate the entire labor market system. For example, “digital computers” have changed the nature of work in nearly every sector of the economy over the last few decades, but the end result is not to replace workers outright, but to increase productivity. and accelerated complementary innovation.
Focusing on the industries most likely to be impacted by AI and machine learning, the marketing industry case study provides an example of complementary innovation. Large-scale marketing campaigns, traditionally essential to reaching target audiences and potential consumers, are complemented by the ability of machine learning to access and learn from data that can accurately predict consumer interest. I’m here. In this way, machine learning allows you to more precisely tailor your ads to reach the maximum number of potential consumers.
Healthcare is another industry currently being impacted by machine learning. An article published by the World Economic Forum in 2020 stated that by 2030, AI will be able to access multiple data sources to uncover disease patterns and the technology will be able to predict an individual’s risk of developing certain diseases. At the same time, they conclude that they will be able to suggest preventive measures.
Beyond medical diagnosis, AI is also expected to contribute to the efficiency of healthcare system management by reducing patient wait times. With essential procedures such as electronic medical records (EMR), healthcare systems are already using big data tools for next-generation data analytics. Machine learning tools are poised to add even more value to this process.
When we talk about education, we think about schools, institutions/universities, education, access to knowledge. Over the years, computers have been widely used for various educational processes. However, the advent of machine learning is fundamentally changing the methodology of teaching, learning and research.
For example, through adaptive learning, this innovation can assess student performance in real-time, alter teaching strategies according to findings, and deliver individually customized content based on student needs. This is especially useful for detecting students with specific learning disabilities and improving their performance and retention in class. Another positive result of machine learning is increased efficiency in managing schedules and classroom content. This frees teachers up significantly from administrative tasks, allowing them to spend more time focusing on tasks that require human interaction and a creative approach.
Similarly, customer service representatives who use AI to automate routine customer interactions can free up time to focus on more complex customer issues. By automating repetitive tasks, employees can devote their energy and attention to more complex and fulfilling tasks.
The examples above show how AI can be used to create new opportunities for employees to learn new skills and land higher value jobs. In addition, AI and machine learning are creating new trends in “desired” skills globally, reinforcing skills typically required for work. For example, a recent study by the World Economic Forum predicts that AI will automate 75 million jobs and create 133 million new jobs worldwide by 2025.
While it is true that certain roles can become redundant, current trends across these industries suggest a shift in focus to upskilling and reskilling workers to adapt to new roles. doing. For these reasons, the main impact of AI on the global job market is likely to be the creation of massive demand for reskilling and upskilling.
Underpinning this growth trend are AI researchers, AI data analysts, machine learning engineers, deep learning engineers, AI content editors, AI chatbot strategists, AI product content specialists, and AI prompts. A surge in job titles. manager etc. The economic growth potential of AI is substantial, and his PWC, a management consulting firm, said AI, robotics, and smart automation could add his $15 trillion to global GDP by 2030. I’m assuming.
This range of expected changes in the global job market poses challenges and opportunities for both employees and employers. In fact, there is a growing demand for workers with AI-related skills and experience, so it will be necessary to upskill and reskill workers to meet the new demand of integrating existing jobs with AI. It is important to invest heavily in training programs for For such training programs to be effective, continuous research and research is essential to keep up with changing labor market conditions.
In conclusion, machine learning is transforming the labor market and will continue to do so as it is becoming an established factor for accelerating automation and improving work efficiency. However, the impact of AI on the labor market will depend on the extent and pace of its adoption and integration into the workplace, and must be judged on a global scale.
However, this stage requires observation. Dedicate ample amounts of public funding, given that the profit motives of private companies may direct investment in AI toward the pursuit of task automation (rather than upskilling existing workers) Due consideration must be given to Towards AI research that favors AI as a complement to workers rather than outright replacing them.
It is important to approach the integration of AI with the current labor market with an open mind, embracing the possibilities AI offers, but being mindful of its limitations and implications for the workforce.