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How Does Technology Affect Employment

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I spent some time over the weekend (I know, I probably need some other hobbies), and reviewed a new report from the Brookings Institute titled ‘Automation and Artificial Intelligence: How Machines Affect People and Places’. In the report, Brookings tried to investigate (like many other organizations in recent years), what potential effect advanced technology, automation and AI will have on the labor market. In particular, what types of jobs and in what areas are more or less likely to be affected, changed and potentially replaced as technology continues to improve and develop.

How Does Technology Affect Employment

There is a lot of interesting information in the 100+ page report, and for those of you who are interested in this, I will block some time to go through it all, but for those who want something shorter, TL; DR version, here are the three most interesting findings / conclusions / takeaways from the report.

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1. Contrary to the hype and hysteria surrounding automation and AI, most jobs are not particularly susceptible to automation. Take a look at the key findings from Brookings in the chart below:

Although almost no single occupation will be unaffected by the introduction of new technology, the impact on employment will vary in intensity and be significant for only 25% of occupations. Another 52 million or more jobs, about 36% of the workforce will see some or moderate impact from the new technology. And a further 39% of jobs will only see a low impact from the new technology. The impact of diversity in the workplace reminds me of the old saying, ‘The future has come, it has not been distributed evenly’.

2. Low-wage jobs, on average, are more exposed to potential automation. In the variation stated in the first chart, Brookings attempted to break down what types of jobs, at what types of wages, and in which geographic areas are most likely to be affected by technology. Here’s a look at the data on pay levels and the potential impact of automation:

The main driver behind low-wage jobs being more vulnerable to automation is the tendency for jobs that are largely made up of routine, physical and cognitive tasks that can be predicted to be the most vulnerable to automation in the short and medium term. Consider jobs such as office administration, simple production and cooking. So according to Brookings, the roles that currently pay the lowest salaries are at the greatest risk. The danger of this, of course, is that the people who hold these jobs are also the least prepared to change jobs to roles that are more complex, higher up the pay scale and are less likely to be influenced by technology.

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3. In addition to wide variety across the types of jobs and wage levels, automation jobs can also vary widely from location to location. A greater relative impact will be felt, according to Brookings, in smaller and more rural areas. See the data below:

There’s a lot of detailed data to analyze there, but the bottom line is that workers in smaller, more rural communities are about 10 percentage points more likely to have their jobs affected by technology than workers in urban areas. This may be a by-product of ongoing challenges faced by smaller communities to prevent skilled and young workers from leaving to seek better opportunities in larger cities.

Since this is a long post, I’ll cover what the folks at Brookings suggest localities, businesses, education, and people can do to better prepare for the wave of automation. Suffice it to say that understanding the problem and the challenge is an important first step to solving it.

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References allow you to track the source of this article, as well as articles written in response to this article. Disruptive innovation is becoming a real part of the manufacturing industry. In fact, the rate of adoption of advanced technology suggests that most American factory floors are already in a cycle of disruption. As costs fall and capabilities increase, artificial intelligence (AI) and other automation technologies are now set to re-engineer the manufacturing industry.

In the latest McKinsey Global Institute report, Jobs lost, jobs gained: Labor transition in the age of automation, they found that by 2030, as many as 375 million workers-or about 14 percent of the global workforce-may have to change job categories. because digitization, automation and advances in artificial intelligence are disrupting the world of work.

According to a recent survey of 1,600 global companies, 71 percent of industry leaders expect widespread use of AI and robotics in the future.

As the nature of work changes, organizations must create new strategies to improve human intelligence to remain competitive.

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Today’s computerized systems operate faster and more reliably than their human counterparts, performing tasks beyond human capabilities. AI-powered technologies such as virtual assistants, self-checkout systems, driverless cars and fraud detection technologies are already commonplace. At the same time, AI and other disruptive technologies are still constrained by significant limitations, and this has important implications for how we think about education and the future of the skilled workforce.

As Rana Foroohar of the Financial Times noted, “The way for companies and governments to turn potential job disasters into opportunities is by using this disruption to train a 21st century workforce and build the public infrastructure to support it.”

Despite the fact that advanced AI and machine learning may begin to replace much of the global workforce over the next two decades, there are still significant opportunities to further develop worker skills. As a recent report from the McKinsey Global Institute shows, the most difficult activities to automate are those that involve complex skills in decision-making, planning, human interaction, imagination and creative work. Simply put, while machine learning has been particularly effective in making predictions, it has been much less successful in dealing with challenges related to judgment, decision making, and interpretation.

With digital transformation underway, companies are focusing on redesigning the organization itself. As networks and ecosystems replace organizational hierarchies, organizational learning becomes a platform for developing and maturing emerging organizations.

The Impact Of Technology On The Economy

To become a high-performing organization and realize the importance of talent mobility, companies must make strategic investments in their learning ecosystems, determine where the largest skills gaps exist and what resources are available to fill those gaps. Unfortunately, in companies where the HR department is solely responsible for employee development, the gap between strategy and execution becomes apparent.

Today’s companies must continuously integrate new skills into their feedback loop, to better align the HR strategy with the entire organization’s capacity for organizational learning.

As the manufacturing industry begins to shift to smart design and smart factories, manufacturers and designers must incorporate learning effects into their business planning.

The learning effect occurs when learned skills are applied in the workplace, subsequently improving performance and driving business goals. The knowledge value chain is a series of intellectual tasks where employee knowledge builds an employer’s unique competitive advantage. Although learning is consumed individually, its value comes when it is retained. It adds value when individuals remember what they have learned and apply it at the right time in the right context at work.

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Now imagine if 10,000 workers make even the most subtle improvements in performance. 10,000 improvements accumulate and are equal to progress in achieving business results. Embrace the fantasy economy

Although a new wave of automation technology is replacing various jobs, it remains a complementary technology for many types of creative work. In fact, this technology trend is giving rise to what many leaders refer to as the “imagination economy”. That is, an economy where intuitive and creative thinking creates economic value, even as logical and rational thinking is increasingly automated.

Although the manufacturing sector is experiencing a technological renaissance, leaders must focus on developing closer links between research and development (R&D), data analytics and product design. But they should also consider significant improvements in the system to promote human capital. Education and training must now be in line with continuous improvement in the production process. Learning and doing become more interactive. This means:

Globally, production continues to increase. Currently, it accounts for 16 percent of global GDP and 14 percent of employment. As manufacturers adopt new technologies to increase productivity and reduce costs, AI and 3D printing make it easier for manufacturers to experiment with new product designs and create complex composite parts. All this means that learning and doing are far more integrated than before.

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The need to improve learning throughout the manufacturing sector today has made organizational learning essential to drive growth. When companies invest in scalable HR reporting and workforce analytics solutions, they can get started, too

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