# data[].attributes.headline
Research title. The changing nature of work 

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Research title. The changing nature of work 

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Sub topic. Future skills needed for employees

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This article shows multiple future skills that are required for future employees by 2030 in their careers.

This article shows some of the required future skills for future employees by 2030 similar to article one with some differences identifying cognitive flexibility and emotional intelligence.

The author of the article Stephanie lukins has multiple past experiences and is currently a research fellow at Harvard university. as the article was updated in July 2023 it has up to date material. The author has created multiple articles on a variety of issues in the filed of economics business and employment. the purpose of the article is to inform students and others of the required skills needed for employment by 2030 and has identified the need for advanced cognitive skills also found in article one suggesting multiple authors have identified this skill as being required for future employees. The author has served in multiple institutions and at all of these has been over six months. the most recent being Harvard university from July 2022 to July 2023 which was then this article was published suggesting the author has vast experience in the filed of research much improving the credibility of the article as to is published by an experienced researcher. The article is of relevance to the research aim as it identifies multiple future skills needed by employees by 2030.

Author Stephanie Lukins

Date published July 2019

Date updated 01/06/23

URL https://www.topuniversities.com/student-info/careers-advice/future-skills-youll-need-your-career-2030

date accessed 21/09/23

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Sponsored by the University of the Witwatersrand
In 11 years' time, the year 2030, it's highly likely you'll be working in a job that doesn't even exist yet - and no, we're not talking about building flying cars or developing the world's first time machine. The world of work is evolving quickly, which means you have to figure out how to prepare for a future job role that's impossible to predict.

Of course, there isn't a crystal ball that can tell us exactly what skills will be needed and what won't be needed. However, with the help of the University of the Witwatersrand, we've come up with five skills we believe you'll need to succeed in your future career, whatever it ends up being.

Cognitive flexibility

The rise of digital technologies means you're going to need to be able to handle the plethora of opportunities and challenges that come with it.

Do you have the ability to adapt to change and conceptualize complex multiple ideas all at once? If so, you're showing qualities that reside in advanced multi-taskers and which are highly valued by employers and recruiters.

Digital literacy and computational thinking

As the world continues to rely on highly technical and continuously evolving technologies, the need for those with the digital skills to match also increases.

You've most definitely heard of STEM, but have you heard of SMAC (social, mobile, analytics and cloud)? Although it may seem like we're being bombarded with digital buzzwords, being digitally literate offers capabilities beyond what was once thought possible when it comes to emerging technologies, such as artificial intelligence (AI), machine learning, Internet of Things (IoT), and data science.

"We need to train scholars to deal with the challenges of the 21st century, some which we may not yet have encountered," says Professor Adam Habib, Vice-Chancellor and Principal of the University of the Witwatersrand.

"We need to work across sectors to develop the technology required for us to leapfrog across eons of poverty, unemployment and inequality, and in so doing to create a new world order that prioritizes humanity before profits and power."

A master's degree in artificial intelligence or e-Science can help advance your digital skillset and accelerate your technical acumen in these emerging fields, from learning about data visualization and exploration, to computational intelligence, and natural language technology.

Judgement and decision-making

Although robots and automation technology may be better than humans in other ways such as calculations and diagnostic solving, it's still going to be humans that deal with the subjective side of data analytics.

Considering we're on the cusp of the fourth industrial revolution, we're still going to need to have somebody who is able to show the world what numbers mean and their significance.

Emotional and social intelligence

For everything that can be replaced by digital technologies and artificial intelligence, emotional and social intelligence remain uniquely human capabilities.

In some sectors, these qualities are absolutely crucial. The demand for jobs in healthcare, for example, are on the increase - demonstrating how some roles will always require a human element. Your future job is more than likely going to include working closely with others, so having empathy, the ability to collaborate, as well as excellent communication skills is something you're most definitely going to need.

Creative and innovative mindset

Despite a report by the World Economic Forum in 2018 suggesting robot automation will create more jobs than they displace, you'll still do well to keep on top of your creativity skills and maintain an innovative mindset.

Much like having an excellent sense of social intelligence, natural creativity is something which can't be easily replicated by the latest digital technologies. As long as you can think outside the box, you'll be just fine.

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Future skills you'll need in your career by 2030

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Discover the five skills employers will be looking for in the future and how you can get them.

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In this chapter, the analysis of technology and society continues, with a focus on (1) changing forms of work, including occupations and contingent jobs; (2) dynamism and flexibility in the workforce; (3) demographics and job satisfaction; (4) the organizations and other institutions in which we work; (5) changes in the role of work in people’s lives; and (6) education and job training.
National Academies of Sciences, Engineering, and Medicine. 2017. Information Technology and the U.S. Workforce: Where Are We and Where Do We Go from Here?. Washington, DC: The National Academies Press. https://doi.org/10.17226/24649.

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The future of employment: How susceptible are jobs to computerisation?

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Frey, C.B. and Osborne, M.A. (2013). The Future of employment: How Susceptible Are Jobs to computerisation? Technological Forecasting and Social Change, [online] 114(1), pp.254–280. Available at: https://www.sciencedirect.com/science/article/abs/pii/S0040162516302244.

Carl Benedikt Frey and Michael A. Osborne's article "The Future of Employment: How Adaptable Are Jobs to Technology?" is an important and useful resource for a number of reasons. The study is creative and forward-thinking, adding to our knowledge of how computerization affects the labour market. The following main ideas illustrate why this article is a reliable source:

Creative Approach: To calculate the possibility of automation for a wide range of specific jobs, the authors use a unique procedure.  The technique, which is based on developments in mobile robotics (MR) and machine learning (ML), enables a thorough evaluation of how susceptible an occupation is to automation.

data-oriented Methods: The study uses data from the O*NET, a comprehensive resource that offers in-depth details on 903 different jobs. Taking a wide range of characteristics into consideration, the authors utilise this data to classify vocations according to their vulnerability to computerization.

Historical Context: The article starts out by outlining how technology advancement has affected employment historically. It gives background information on the historical relationship between technological breakthroughs and employment, as well as citing John Maynard Keynes's prediction of technological unemployment.

Looking ahead Analysis: The writers take into account technical developments that extend beyond the conventional framework of computerising repetitive operations. They evaluate the growing range of jobs that computers can now accomplish, and their study is prospective, taking into account the potential effects of future technological advancements on the labour market.

To sum up, this article's distinctive technique, data-driven approach, historical background, forward-looking analysis, relevance to ongoing discussions, and interdisciplinary character make it a valuable resource. For academics, decision-makers, and anybody else interested in the nature of labour in the age of automation and computerization, it adds to our understanding of the changing link between technology and employment.

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The changing nature of work and organizations: Implications for human resource management

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Spurk, D. and Straub, C., 2020. Flexible employment relationships and careers in times of the COVID-19 pandemic. Journal of Vocational Behavior, [online] 119, p.103435. Available at: <https://www.sciencedirect.com/science/article/pii/S0001879120300609>

The article above is very relevant and creditable for various reasons, it addresses the crisis that happed in 2020/2021 of COVID-19 and how it genuinely changed the working and employment system, And how it involved the future skills and the advanced technology.

Secondly, the article's comprehensive analysis emphasises its credibility.  It explores multiple aspects of work and employment, including working conditions and motivations as well as attitudes towards the workplace, professional advancement, and personal happiness.  The reader will have a thorough understanding of the pandemic's various impacts on several aspects of work thanks to this full approach.

Moreover, Technology adaptation: The essay describes how the COVID-19 epidemic caused a sudden change in working conditions, with many people switching to remote work from home offices. For a variety of workers, adjusting to new technologies and digital tools became important, emphasising the value of digital literacy and the usage of technology at work.

Further more, The article also provides particular scenarios and in-depth examples that support its points. For instance, the increasing need for food delivery services and Uber's response to the pandemic are both mentioned. Such specific examples support the credibility of the article by showing that it is firmly based on the real-world experiences and reactions of workers and businesses.

Lastly, the article wasn’t biased and it fully covered the full crisis step by step, and showing real-world examples that increased the source’s credibility.

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The current state of employment in Canada

Canada is currently enjoying a sustained period of economic growth and record low levels of unemployment. However, the Canadian labour market faces two main challenges in maintaining this momentum of economic growth. The two challenges, namely a shortage of skills and an aging workforce, are expected to impact employers in several ways. They include a lag in productivity levels, a rise in early withdrawal from the workforce, and a decrease in the levels of economic activity. The issue of skills

Demographic changes

One of the most powerful forces affecting work and organizations is changing worker demographics. The workforce of 2015 will be different than it is in 2005. Lower birth rates coupled with an aging workforce have resulted in a shrinking labour pool. The age distribution of the workforce will shift dramatically, while the characteristics, values, and expectations of new workforce entrants will be remarkably different than that of the past. On the demand side, the kinds of workers who are

Technology

The second factor which drives where we work, and how we organize and manage work is technology (Wallace, 2004). As new technologies are invented, the way we do things changes, and those changes in turn affect us personally and directly, such as where we live and work. The important thing about technology is that it continues to get better, cheaper, and faster. As a result, we can process enormous quantities of information, share and access data easily, and communicate globally. Suffice to say,

Globalization

As we have indicated earlier, technology has increasingly linked local markets, cut the cost of moving information, and broken down all kinds of political and cultural barriers. The growth of transportation (e.g., airlines and shipping companies) has enabled us to experience the global marketplace for products and services. While new markets are being discovered, new competitors also emerged. Besides the obvious threat of outsourcing of jobs, globalization has also brought us global labour

Implications

Several factors have come together over the past decade to impact the role, relevance and practice of human resource management in organizations. These factors operate at many different levels and raise important issues and challenges for the management of organizations.

The past decade has also seen dramatic increases in our understanding of the relationship of HRM practices and firm performance. As a consequence, HRM is now seen as a major competitive advantage that cannot be copied readily by

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The changing nature of work and organizations: Implications for human resource management

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This manuscript considers how changes in the external environment of organizations have altered the world of work. While global trends are identified,...

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This article shows the increasing use of advance technologies and the need for advanced cognitive skills for future and current employees in the world of work.

This article was authored by two people one was Simon Djankov of the London school of economics he was the former deputy prime and minister of economics in Bulgaria 2009-2013.

Federica Saliola is the other author and is the Manager of the Jobs Group in the Social Protection and Jobs Global Practice at the World Bank.

The article shows the demand for future skills and is clearly relevant as it discusses the skills needed by future employees in the workplace.

This article talks about future skills for employees particularly technological skills so is relevant to the sub question being researched.

While the article is 5 years old it has accurately predicted the need for developed and applicable technological skills and advanced cognitive skills needed in todays workplace in which has only continued in most jobs as the amount of technology in jobs has only increased since 2018 particularly since covid 19 and people being forced to work from home in most jobs due to the pandemic.

The centre of economic policy research (CEPR) is Europes leading network of economic policy researchers.

It is an independent organisation so has no governmental bias improving their credibility. As the CEPR is funded diversely it will not rely on a single source of funding so is less susceptible to pressure to change its findings by their funders.

Harvard referencing

Authors Federica Saliola and Simon Djankov

date published 23 November 2018 URLhttps://cepr.org/voxeu/columns/changing-nature-work

Date accessed 22/10/23

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Over the last century, machines have replaced workers in many tasks. On balance, however, technology has created more jobs than it has displaced (Frey and Rahbari 2016). Technological progress has transformed living standards. Life expectancy has gone up; basic health care and education are widespread, andmost people have seen their incomes rise. And yet, fears of robot-induced unemployment often dominate discussions over the future of work.

The World Bank's recently launched World Development Report for 2019 on The Changing Nature of Work (World Bank 2019) addresses these issues, analysing what exactly is changing and what needs to be done. The report argues that, on balance, concerns about robot-induced unemployment appear to be unfounded. Instead, the future of work is driven by the competing forces of automation and innovation, the other 'AI' (Figure 1).

Figure 1 In the future, the forces of automation and innovation will shape employment

Note: The ordering of the sectors in the figure should be understood as running from the most automatable to the least automatable, or from the low-skill and middle-skill jobs to high-skill jobs where there is a decline in the relative demand for some less educated workers.

Technological progress enables firms to automate, replacing labour with machines in production, and to innovate, expanding the number of sectors, tasks, and products. The pace of innovation will determine whether new jobs or tasks emerge to counterbalance the decline of old, routine-based jobs.

For example, recent evidence for Europe suggests that while technology replaces some workers, it also raises labour demand. Overall, technology that replaces routine work is estimated to have created more than 23 million jobs across Europe from 1999 to 2016 (Gregory et al. 2016).

The report casts its net wider than an attempt to predict the number of jobs that technology may create or destroy, focusing instead on the changing nature of the firm, its impact on skills and the terms on which people work, and how government policy should be reoriented in response.

The digital economy has expanded firm boundaries and driven a fundamental shift in the nature of firms. Physical presence is no longer a prerequisite to doing business: companies provide online services from abroad or profit from intangible assets such as software and intellectual property; digital platforms generate income from the capital of others. Firms in the digital economy can evolve much faster from local start-ups to global behemoths, often with few employees or tangible assets (Figure 2).

Figure 2 Recent technological advances accelerate the growth of firms

Source: WDR 2019 team, based on Walmart annual reports; Statista.com; IKEA.com; NetEase.com

For governments, identifying where value is created in the digital economy-and capturing some of those corporate gains-is not always straightforward, particularly when it comes to user data. Under these circumstances, it has become easier for companies to locate assets (and subsequently profits) in countries with preferential corporate tax frameworks. Digital markets also provide new risks in the competition context.

The changing nature of firms coincides with a shift in the demand for skills among workers. The demand for less-advanced skills that can be replaced by technology is declining. At the same time, the demand for advanced cognitive skills (Krueger and Kumar 2004), socio-behavioural skills (Cunningham and Villaseñor 2016), and skill combinations associated with greater adaptability arerising (Hanushek et al. 2017).

The rise of platform marketplaces is also changing the way people work and the terms on which they work, through the so-called 'gig economy'. Individuals and firms need only a broadband connection to trade goods and services on online platforms. This 'scale without mass' brings economic opportunity to millions of people who do not live in industrialised countries or even industrial areas (Brynjolfsson et al. 2008).

That said, the number of gig economy workers remains small as a proportion of the overall workforce. Data is scarce but, where it does exist, the numbers are still low. Data from Germany and the Netherlands indicate that only 0.4% of the labour force in these countries is active in the gig economy. The report estimates that, worldwide, the total freelancer population is around 84 million, or less than 3% of the global labour force of 3.5 billion. A person counted as a freelancer may also have a regular salaried job. In the US, for example, more than two-thirds of its 57.3 million freelancers also hold a traditional job, turning to freelance work to supplement their income (Upwork 2017). The best estimate is that, globally, less than 0.5% of the active labour force participates in the gig economy.

These changes in the nature of work have been more pronounced in advanced economies, particularly Europe and North America where the uptake and penetration of technology aregreater and labour markets are more developed. Correspondingly, the growth of the gig economy has raised alarm bells in those parts of the world because it blurs the divide between formal and informal work: in both cases, workers are typically in low-productivity employment, with most labour laws unclear on the roles and responsibilities of the employer versus the employee. This group of workers often lacks access to benefits. There are no pensions, no health or unemployment insurance schemes, and none of the protections provided to workers in long-term, contract-based employment.

Governments have to invest more and better in lifelong learning if workers are to stand a chance of adjusting to future labour markets-from early childhood development programmes and formal schooling, through to higher education and adult learning programmes. But rethinking social protection systems is just as important.

A formal wage employment contract is still the most common basis for the protections afforded by social insurance programmes and by regulations which, for instance, set a minimum wage or severance pay. The German chancellor Otto von Bismarck is acknowledged as the founder of social insurance-providing benefits for workers in the formal sector financed by dedicated taxes on wages. The system relies upon steady wage employment, clear definitions of the employer and employee relationship, and a fixed retirement date. But this contributory approach is beginning to look outdated as the changing nature of work disrupts these traditional norms. Technology shifts the demand for workers' benefits from employers towards directly demanding welfare benefits from the state.

Direct social assistance programmes also need to be revised to ensure that they guard against growing labour market risks. The evidence is irrefutable that cash transfers make positive contributions to the health and education of current and future generations of people. They reduce stress and depression, increase mental bandwidth, and foster more involved parenting. All of these undoubtedly make for happier, more productive households. But there is generally low uptake of social assistance. In the EU, only about 60% of social benefits are claimed (Eurofound 2015). This is due to a lack of information about such benefits, the stigma attached to them, and the bureaucratic hurdles required to be overcome in order to receive them.

'Universal basic income' is the fashionable solution, but in truth, the world knows very little about how it would work in practice. Studies suggest the fiscal implications would be significant. The cost of a universal basic income for adults set at the average poverty gap level ranges from 9.6% of GDP in low-income countries to 3.5% of GDP in upper-middle-income countries (Figure 3). A simulation for four European countries shows that a universal basic income would cost (if set at a level equal to existing cash transfer programmes) 13.8% of GDP in Finland, 10.1% in France, 8.9% in the UK, and 3.3% in Italy (Browne and Immervoll 2017). In each case, it was not always possible to offset the cost of the universal basic income simply by abolishing existing allowances. Other initiatives would have to be cut or taxes raised to provide the necessary cash.

Figure 3 The cost of a universal basic income climbs as the income level of countries decreases

Sources: WDR 2019 team, based on World Bank's World Development Indicators (database) and PovcalNet and United Nations' World Population Prospects.

References

Browne, J, and H Immervoll (2017), "Mechanics of replacing benefit systems with a basic income: Comparative results from a microsimulation approach", Journal of Economic Inequality 15(4): 325-44.

Brynjolfsson, E, A McAfee, M Sorell and F Zhu (2008), "Scale without mass: Business process replication and industry dynamics", Harvard Business School Technology and Operations Management Unit Research Paper 07-016, Cambridge, MA.

Cunningham, W, and P Villaseñor (2016), "Employer voices, employer demands, and implications for public skills development policy connecting the laborand education sectors", World Bank Research Observer 31(1): 102-34.

Eurofound (European Foundation for the Improvement of Living and Working Conditions) (2015), Access to social benefits: Reducing non-take-up, Publications Office of the European Union, Luxembourg.

Frey, C B and E Rahbari (2016), " Technology at work: How the digital revolution is reshaping the global workforce ", VoxEU.org, 25 March.

Gregory, T, A Salomons and U Zierahn (2016), "Racing with or against the machine? Evidence from Europe", ZEW Discussion Paper 16-053, Center for European Economic Research (ZEW), Mannheim, Germany.

Hanushek, EA, G Schwerdt, S Wiederhold and L Woessmann (2017), "Coping with change: International differences in the returns to skills", Economics Letters 153(April): 15-19.

Krueger, D, and KB Kumar (2004), "Skill-specific rather than general education: A reason for US-Europe growth differences?" Journal of Economic Growth 9(2): 167-207.

Upwork (2017), Freelancing in America 2017 (database), Mountain View, CA.

World Bank (2019), World Development Report 2019: The Changing Nature of Work. Washington, DC: World Bank.

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Over the last century, technology has created more jobs than it has displaced. This column presents an overview of ways in which technology and innovation are changing the nature of work, leading to demand for advanced cognitive skills and greater adaptability among workers.

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The article has identified multiple skills that employees will need in the future of employment mainly being an ability to use the technology available and some soft communication skills.

The article is of relevance to the research aim as it discusses the future skills required for employees. As the article was published in May 2022 the information presented in up to date and relevant as it shows the impacts of Covid which forced employees to work digitally and identifies the need for advanced technological skills for future employees. The three authors of the article have worked in two universities each Caitlin Ferreira at Luleå University of Technology, Luleå, Sweden and Red & Yellow Creative School of Business, Cape Town, South Africa.

Jeandri Robertson, at Luleå University of Technology, Luleå, Swede nand University of Cape Town, Cape Town, South Africa.

Leyland Pitt at Beedie School of Business, Simon Fraser University, Vancouver, Canada and Hanken School of Economics, Helsinki, Finland. As all three of the authors have worked in universities they have more credibility as their research has to be conducted to the universities standard and is checked before being published. The article is relevant useful and up to date all improving the credibility of the research within the article that is being presented which is why it is being used.

Harvard reference

Authors Caitlin Ferreira, Jeandri Robertson, Leyland Pitt

Date published 06/05/22

URL https://onlinelibrary.wiley.com/doi/full/10.1002/tie.22276

Date accessed 31/10/23

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Automation and New Tasks: How Technology Displaces and Reinstates Labor

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Rana Adil khan (1) 30111638 Automation and new tasks: How Technology displaces and reinstates labor 

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Rana Adil khan (1) 30111638 Automation and new tasks: How Technology displaces and reinstates labor 

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Topic: The changing nature of work and employment
Subtopic Future Skills needed for employment
Name Rana Adil khan
Student ID 30111638
This topic show the complex  relationship between automation and labor demand presented by Acemoglu Daron and pascual Restrepo in 2019. The core of this framework revolves around the allocation of tasks within production processes, shedding light on the impact of technological change on the employment landscape.
Automation, as a key agent of change, is catalyzing a significant shift in work dynamics. It facilitates the replacement of tasks previously performed by human labor, always tilting the balance in favor of capital. The result is a significant reduction in the share of labor in the value-added chain, which may lead to reduced labor demand despite increased productivity. However, this framework provides a balanced perspective by integrating the concept of reintegration through the creation of new tasks. These tasks, which are often more beneficial to human work, balance out the harmful effects of automation-induced commuting. The creation of these new tasks contributes positively to the content of production tasks, promoting employment and thus increasing both job density and job demand.
Empirical analysis based on analysis of industry-level data presents a clear picture overall trends. This reflects in particular slower employment growth due to  growing displacement effects, which are particularly pronounced in the manufacturing sector. Furthermore, the weaker rebound effect and slower rate of productivity growth compared to previous periods indicate the complexity of factors influencing labor demand in the era defined by the revolution. technology.
This framework provides a comprehensive perspective to understand the multifaceted impact of automation on labor demand. Its meaning resonates in both theoretical discourse and empirical analysis, providing valuable insights into the changing landscape of work in modern times.
Harvard reference
Acemoglu, D. and Restrepo, P. (2019). Automation and New Tasks: How Technology Displaces and Reinstates Labor. Journal of Economic Perspectives, 33(2), pp.3–30. doi:https://doi.org/10.1257/jep.33.2.3.

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Abstract We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the allocation of tasks to capital and labor-the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added and may reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which labor has a comparative advantage. The introduction of new tasks changes the task content of production in favor of labor because of a reinstatement effect, and always raises the labor share and labor demand. We show how the role of changes in the task content of production-due to automation and new tasks-can be inferred from industry-level data. Our empirical decomposition suggests that the slower growth of employment over the last three decades is accounted for by an acceleration in the displacement effect, especially in manufacturing, a weaker reinstatement effect, and slower growth of productivity than in previous decades.

Citation
Acemoglu, Daron, and Pascual Restrepo. 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor." Journal of Economic Perspectives, DOI: 10.1257/jep.33.2.3

Additional Materials

JEL Classification

D24 Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

J23 Labor Demand

J24 Human Capital; Skills; Occupational Choice; Labor Productivity

J31 Wage Level and Structure; Wage Differentials

O33 Technological Change: Choices and Consequences; Diffusion Processes

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human capital; skills; occupational choice; labor productivity

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wage level and structure; wage differentials

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technological change: choices and consequences; diffusion processes

# data[].attributes.attachment_link.title
Automation and New Tasks: How Technology Displaces and Reinstates Labor

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Automation and New Tasks: How Technology Displaces and Reinstates Labor by Daron Acemoglu and Pascual Restrepo. Published in volume 33, issue 2, pages 3-30 of Journal of Economic Perspectives, Spring 2019, Abstract: We present a framework for understanding the effects of automation and other types o...

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This article has identified the need for technological skills due to the digitalisation of the workplace.

The article focusses on the need for technological skills for future employees due to the rise in technology to enterprises but also identifies the need for soft skills such as communication and cooperation.

The article is of relevance to the research aim of future skills needed for employees as it has identified the need for advanced technological skills this is consistent with the other three articles suggesting technological skills are needed for future work is agreed on by multiple authors. As the article was published in 2021 the information included is still up to date and relevant. The purpose of the article is to convey the needed skills to employees current and future in the industry. All of the three authors have worked at a university so the research they conduct needs to meet the university standards and is checked before being published improving the articles credibility.

A common idea among all sources that were used was the need for advanced technological skills this would suggest the idea that this skill is needed as reliable as multiple authors have included it in their respective articles soft skills was also repeatedly mentioned so that skill is also agreed upon by some of the authors of the sources as being required for future employees.

Harvard reference

Authors Sebastian Saniuk, Dagmar Caganova and Anna Saniuk

Date published 10/06/21

URL https://link.springer.com/article/10.1007/s11036-021-01788-4

Date accessed 31/10/23

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Knowledge and Skills of Industrial Employees and Managerial Staff for the Industry 4.0 Implementation - Mobile Networks and Applications

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The development of the Industry 4.0 concept offers completely new technologies’ enablers using high level of automation and digitalization. There is a huge challenge for enterprises not only due to the application of modern technologies (such as Internet of Things, Big Data Analytics, Cloud Computing, etc.) related to the creation of Cyber-Physical Systems but also for a human resources development. Scientists and practitioners pay a lot of attention to technological changes in enterprises, but relatively little research is conducted on the issue of human resources development. The problem becomes more interesting in light of the Industry 4.0 era which resulted in changes in the employment structure, requirements for future industrial employees and managerial staff and also to the approach to the education process. The changing demand for skills is a quite well-researched topic in economics and management, but the changing skill demand for the Industry 4.0 is just the newest case of a quite old debate. The case of Industry 4.0 seems to be a particular case for the general change in skill demand due to digitalization. The main aim of the paper is to indicate the key areas of required knowledge and skills of employees essential to implement the Industry 4.0 concept. They are identified on the basis of a critical literature analysis and the conducted survey of selected industrial enterprises. The results of this research are particularly important for adapting the employee training system and the education process for students.

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The Top 5 Skills You Need For The Future Of Work - Matei

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The Top 5 Skills You Need For The Future Of Work - Matei

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The article is pertinent to the abilities that employers will require to hire people in the future. It emphasises a number of crucial ideas that are consistent with the changing needs of the labour market and the influence of technology.

The article was written by a contributor of Forbes. Ashley Stahl is a career counsellor, author, and speaker well-known for her work assisting people in discovering and pursuing fulfilling career pathways. She graduated from Moore College of Art and Design in 2009 with a BFA in art history, and she is currently a graduate student at Tyler School of Art and Architecture studying art history and arts management.

The article is talking about 5 majour skills needed in the near future for both employees and employer.

Overall, the article is relevant nowadays as it is few month old. The article is reliable as most things discussed in there are starting happening since Covid 19.

Link: https://www.forbes.com/sites/ashleystahl/2023/05/11/the-top-5-skills-you-need-for-the-future-of-work/

Author: Ashley Stahl

Date published: 11/05/2023

Date accessed 03/11/2023

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The Top 5 Skills You Need For The Future Of Work

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Worried about AI taking over your career? Here are the top five human skills you can develop to secure your job.

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Automation, Computerization and Future Employment in Singapore on JSTOR

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Rana Adil khan (2) 30111638 Automation, Computerization and Future Employment in Singapore

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Rana Adil khan (2) 30111638 Automation, Computerization and Future Employment in Singapore

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This article examines the impact of automation and computerization on Singapore's future employment landscape.It explores the correlation between technology development,job transformation and the necessary skills for the workforce.It specifically exploresthe challenges and opportunities of automation and how they will affect Singapore's employment trends. The Singapore employment landscape is developing rapidly due to automation and computerization. This paper explores the impact of technological progress on the future prospects of the nation's workforce.It investigates the changes in employment patterns and skills that will be essential to the workforce.Automation and computerization are revolutionizing Singapore's industry.The integration of AI,robotics and digitaltechnology may reshape job roles,reduce dailytasksand create new opportunities. Sectors such as manufacturing,finance and logistics have undergone major transformations,emphasizing the importance of adaptable skills sets. As Singapore's employment market evolves, certain skills are becoming increasingly important.Adaptability,technical competence, problem-solvingand creativity are crucial for individuals to thrive in changing landscapes.Continuous learning and development of soft skills such as communication and critical thinking are crucial to future employment. Automation and computerization in Singaporemeana period of change in the employment landscape. While some jobs may be reduced,new opportunities will arise. To adapt to this change, you need to acquire and develop specific skills for future employment.
Harvard reference
Fuei, L.K. (2017). Automation, Computerization and Future Employment in Singapore. Southeast Asian Economies, 34(2), pp.388–399. doi:https://doi.org/10.1355/ae34-2h.

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Automation, Computerization and Future Employment in Singapore on JSTOR

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Lee King Fuei, Automation, Computerization and Future Employment in Singapore, Journal of Southeast Asian Economies, Vol. 34, No. 2 (August 2017), pp. 388-399

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You Need a Skills-Based Approach to Hiring and Developing Talent - Matei

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You Need a Skills-Based Approach to Hiring and Developing Talent - Matei

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The article mention the importance of focusing on skills when hiring new employees and it point that there is a need to shift towards a skills-based approach in the hiring process.

The article does not, however, include a comprehensive list of all the particular abilities required of prospective hires.

The article was written by Ryan Rolsansky who is an enterprenur and the CEO of LinkedIn. He studied 1 year at the University of California, then he dropped out in order to devote all of his time to starting a business with his two roommates.

The article talks about re- and upskilling has become increasingly important in the quickly evolving global economy of today. A thorough review of the recruiting and personnel development procedures is necessary to successfully navigate these changes.

The article says that over 140 million individuals are expected to lose their jobs due to the COVID-19 pandemic, and an additional 1.6 billion people face potential income loss. Regretfully, a large number of the lost employment might never come back.

Encourage managers to find out what areas of the business their employees are interested in as a practical solution for those organisations that might not be able to set up structured learning programmes.

Link: https://hbr.org/2021/06/you-need-a-skills-based-approach-to-hiring-and-developing-talent

Harvard Business Review

Author: Ryan Roslansky (CEO of LinkedIn)

Publish date: 08 June 2021

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With the global economy experiencing massive change, upskilling and reskilling have taken on a renewed sense of urgency. Success through these transitions requires major shifts in thinking about how hiring and employee development are done.

The economic toll of the Covid-19 pandemic is expected to leave more than 140 million people out of work and another 1.6 billion at risk of income loss. Unfortunately, many of the jobs lost simply won't return. At the same time, certain companies and industries like logistics and manufacturing can't hire fast enough. Shifting to a skills-focused approach is a viable solution to an evolving workforce dilemma.

Workers often don't realize that the skills they have for one job can be easily transferred to another - nor do employers. Take food servers who lost their jobs due to the pandemic. More than 70% of them have the skills needed to succeed in customer service, which is currently one of the most in-demand jobs on LinkedIn. Had servers and people hiring for customer service specialists known they already had many of the required skills, we may have seen a significant shift of out-of-work food servers into in-demand roles instead of seeing those positions go unfilled.

Evaluating employees and new hires based on their skill sets instead of their work history can help level the playing field - and help companies realize the talent they already have. It also makes talent pools more diverse and often makes hiring more effective.

This is the future of hiring and development. To get ahead of it, companies need to start weaving learning into their company cultures. Organizations slow on the uptake will be left behind and forced to deal with unsatisfied and unmotivated employees and significantly less innovation overall. At a time when talent is the number-one commodity in business, companies can't afford to remain stuck in old mindsets.

Here are three ways companies can upskill and reskill their existing workforce and take a skills-based approach to hiring new employees.

Support new career paths for your employees

Many large enterprises around the world have viewed the need to upskill their current talent as urgent for the last few years and have invested millions - and in some cases, billions - in "future proofing" their employees, arming them with the skills required to adapt to changing work. For example, JPMorgan Chase added $350 million to their $250 million plan to upskill their workforce. Amazon is investing more than $700 million to provide upskilling training to their employees. PwC is spending $3 billion to upskill all of its 275,000 employees over the next three to four years; the mantra of the program is "New World, New Skills." The pandemic accelerated this need for companies of all sizes, as many needed to retool their employees quickly to fulfill changed business priorities.

If your company is unable to support a structured learning program, encourage managers to find out what other areas of the company their employees are interested in learning about and help them participate in cross-functional meetings and projects. Allow them to spend 10% of their work time on that cross-functional work.

You shouldn't have to switch companies to get ahead - creating and supporting these learning programs not only shows your employees that you're invested in their future, but they also open different pathways for growth internally and can evolve into new career paths. In Northrop Grumman's Pathways program, for example, employees do three 12-month stints in different roles before choosing the path they'd ultimately like to follow.

Don't wait for the next crisis to begin the process of reskilling employees for critical roles. Employees who see good opportunities to learn and grow are 2.9 times more likely to be engaged. Creating internal programs that identify and address skill gaps not only helps prepare for future disruptions but also helps your strongest and most dedicated employees feel secure.

Give employees learning time and rewards

According to a June 2020 survey conducted by Glint, a human resources software company owned by LinkedIn, an overwhelming number of employees - 97% - want to expand or at least continue the amount of time they spend learning. What's more, opportunities to learn and grow have emerged as the strongest driver of work culture.

Executives and managers should make it clear that ongoing education is integral to personal career growth and can be done on company time. To help foster a learning culture, encourage employees to block out calendar time for learning each week or month - and do the same. If managers have dedicated learning time, employees will be more likely to follow suit.

It can be stressful to juggle learning with looming deadlines or client needs. Remind yourself and your team that the investment in learning will pay off for their careers and the organization, and give specific guidance in employee growth plans. For example, an employee can make it an end-of-quarter deliverable to spend four hours each month on learning courses, then discuss their learnings during their annual review.

Some businesses promote their learning programs with contests and incentives. Rewards, whether monetary or internal kudos, can boost employee participation considerably. Executive and manager participation is a must - it's crucial for us to lead by example. Even putting the most recent course you watched below your email signature signals to employees that it's a priority for you.

Shift to a skills-based approach when hiring

In the past year, LinkedIn has seen a 21% increase in job postings advertising skills and responsibilities instead of qualifications and requirements in the U.S., and the number of positions that don't require a degree increased by nearly 40% in 2020 compared to 2019.

Taken together, we can see companies are starting to be more intentional about hiring for a candidate's future potential, not their past history. But it'll be a long road. Our traditional recruiting processes still place an emphasis on certain types of education, experience, or personal referrals that can lead to a homogenous workforce.

Start by rethinking your job descriptions. Focus on the results you'd like to see, rather than the type of qualifications that you think could deliver them. Highlighting the desired skills - the candidate's ability to perform certain tasks - gets to the same results without creating an unnecessary barrier to entry, like a requirement for a four-year degree.

Of course, the job post is one of the earliest steps in your hiring process. Once you've removed unnecessary barriers to entry, you'll still need a skills-based way to assess candidates and find your finalists. If you're looking beyond education and experience, what should you evaluate?

Stay focused on skills - and the assessments that can measure them. From hard skill evaluations like coding tests, to innovative soft skill assessments, to " job auditions," there are plenty of ways to gauge a candidate's ability to perform without relying on their education or experience as proxies. Even asking unexpected interview questions can let you see how a candidate processes information and problem-solves in real time. It's also never too early to discuss learning commitments during interviews with candidates - it may even make you more attractive as an employer.

The payoff? A wider, more diverse talent pool and perhaps stronger retention: Employees without a traditional four-year degree stay at companies 34% longer than those with such a degree, according to LinkedIn data. While this could be a sign that it's more difficult for them to find their next job, it could also be a sign that they're simply more engaged and feel like the company is betting on their success. As LinkedIn's 2018 Workplace Learning Report showed, 94% of employees said they would stay at a company longer if it invested in their career.

By taking a skills-based approach to the hiring process, diplomas and titles can sit alongside assessments, certifications, endorsements, and other alternate methods for determining the capability and fit of a candidate. What's more, by focusing on skills, employers can increase the size of their talent pools, allowing them to pinpoint quality applicants for hard-to-fill roles. Once you've hired them, keep your employees engaged and your company ready to adapt to changing demands by creating a culture of learning. It's how we'll start hiring and developing talent for the future, not the past.

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You Need a Skills-Based Approach to Hiring and Developing Talent

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The economic toll of the Covid-19 pandemic is expected to leave more than 140 million people out of work and another 1.6 billion at risk of income loss. Unfortunately, many of the jobs lost simply won't return. At the same time, certain companies and industries like logistics and manufacturing can't hire fast enough.

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These are the top 10 job skills of tomorrow – and how long it takes to learn them - Matei

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These are the top 10 job skills of tomorrow – and how long it takes to learn them - Matei

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The artice talks about 10 job skills needed to work in any job in the next 3-4years.

The article is published by World Economic Forum and written by Kate Whiting. She's a 15 years of experience as a journalist and editor covering news and features for print and digital media. This means that her article can be trusted and reliable for now and near future. The article is 3 years old and still pretty accurate. It also highlights how technology has the ability to create new jobs in addition to changing existing ones.

Moreover it states that "by 2025 is 40%, and 50% of all employees will need reskilling". This proves that learing new skills is very important. The article aslso states that" Critical thinking and problem-solving top the list of skills that employers believe will grow in prominence in the next five years. These have been consistent since the first report in 2016". This also shows that since 2016 most information has been accurate regarding this topic.

Link: https://www.weforum.org/agenda/2020/10/top-10-work-skills-of-tomorrow-how-long-it-takes-to-learn-them/

Author: Kate Whiting

Date published: 21/10/2020

Date accessed 03/11/2023

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Education

Professor Klaus Schwab says technological innovation can be leveraged to unleash human potential. Image: REUTERS/Denis Balibouse

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Half of all employees will have to reskill in the next five years. Image: World Economic Forum

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These are the top 10 job skills of tomorrow - and how long it takes to learn them

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Critical thinking and problem-solving top the list of skills employers believe will grow in prominence in the next five years, according to the Future of Jobs report.

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6 of the most in-demand skills for the future of work - Matei

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6 of the most in-demand skills for the future of work - Matei

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The article talks about skills needed for future empoyment as in todays workplace the HR managers are most concerned about skill gaps of 75% of them say there is a shortage of applicants with the necessary skills. The article talks about what skills are required to know in order to have a job.

The article was published by Employment Hero platform which is one of the top cloud-based HR platforms in the UK that combines payroll, services, employee benefits, compliance, and HR software. The author is the team from Employment Hero and doesnt have a named person.

Overall the platform that publish is article is reliable and has 4.5 out of 5 stars based on 199 user reviews on Capterra.

Link: https://employmenthero.com/uk/blog/future-of-work-skills/

Author: The Team, Employment Hero

Publish date: Published 20 Dec 2021

Updated 22 Aug 2023

Date accessed: 03/11/2023

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According to a study by SHRM, HR Managers view skill gaps as the biggest concern when recruiting talent, with 75% of saying there is a skill shortage among applicants. With so many human resources trends taking off over the next decade, we're beginning to see a major shift in priorities.

While we've recently seen a heavy focus on upskilling technical skills such as computer programming and data science, the development of soft skills has taken a back seat.

According to Deloitte, two-thirds of jobs will be soft-skill intensive by 2030, confirming that the skill gap doesn't only exist within technical roles. Additionally, research from Deloitte revealed "the average worker is missing around 2 of the 18 critical skills that are advertised for a job".

If we compare this to 2010, where the average worker lacked 1.2 of the skills, we can see the skills gap is widening over time. As the leaders of tomorrow begin to enter the workforce, it's never been more important to be aware of the most in-demand skills for the future of work.

Read on as we share the skills you need to continually develop to future-proof yourself and your team.

1. Innovation and creativity

Technology is at the forefront of every industry, so it's crucial you remain creative and innovative. When we were younger, we got told that thinking outside of the box is a great skill to have, and this continues throughout your entire career.

When you have the ability to see projects in a new way, you'll be able to be creative.

According to LinkedIn, creativity is the most in-demand soft skill of the future. This is due to technology replacing many of the mundane, process-related work that doesn't require much thought or creativity to perform.
Me when I think of something creative.
However, according to Adobe, 78% of employees over the age of 25 wish they had greater creative ability and equally, 78% of hiring managers believe that creativity is critical to economic growth.

With many people putting themselves in the 'I'm not creative' basket, it's crucial to remember that being creative doesn't just apply to the arts, and thinking this way instantly creates a roadblock. Being creative can be as simple as thinking of challenging the status quo to try new things.

STEM fields can benefit from creative thinking just as much as the arts.

2. Problem-solving and critical thinking

According to the World Economic Forum, one in three jobs require complex problem-solving skills and the ability for employees to think critically. While specific professions like engineering and science require critical thinking in their day-to-day, they're not the only ones!

It's become apparent that roles outside these areas need to do the same to create a true competitive advantage.

Machine learning and artificial intelligence enable better access to data, so you have the ability to make strategic decisions. If you're scared of automation taking over your role, don't be! It's important to shift your view to see how it can actually improve your ability to make decisions and solve problems.

If you want to take a look at how automation is impacting the human resources industry, you can read our blog.

3. Growth mindset

Having a growth mindset follows from the two points above. In the constantly changing work environment, it's crucial that you're agile and able to pivot easily.

So, what exactly is a growth mindset? It's the ability to continually improve so you can be great at anything when you put your mind to it. Not only this, but having a growth mindset involves continually being on the lookout for the latest trends and innovations that can help you be better and perform better.

For example, if there are two employees and one displays a growth mindset, and the other does not, there will be an obvious conflict of opinions. We've put together two examples below, and we definitely know which employee we would want in our team!

Employee A: Constantly thinking of ways to innovate and strongly believes that challenges are simply opportunities to be better.

Employee B: Close-minded to change and prefers to kick it old school with manual processes.

4. Leadership

As Gen Z begins to enter the workforce, it's essential we prepare the leaders of tomorrow.

Teaching important skills can make all of the difference including:

Decision-making

Public speaking

Delegating

Communication

How to take ownership of the task at hand

According to Forbes, four out of ten leaders in the tech industry are failing. This is the most significant failure rate across all industries. Where is it going wrong, I hear you ask?

One reason is due to the tech industry putting very little resources into developing leaders. Another contributing factor is that technology is the fastest-growing industry. It's also been reported that only 32% of leaders in this industry meet with their teams to discuss performance, a vital component of employee engagement.

At Employment Hero, we pride ourselves on going against these trends. Every employee has weekly 1:1 meetings with their direct manager to discuss performance and any other concerns. It's a great way to discuss work in a relaxed environment.

If you want to join a fast-growing tech company, check out our open roles here.

5. Interpersonal skills

When the future of work is faced with so many changes on the technology and automation front, it's important to remember that having strong interpersonal skills is always in demand. The ability to communicate effectively is an important skill that can be the difference between a manager and a leader.

Whether it's communicating with co-workers to complete a project or working with clients, communication is a skill that should never be underestimated.
"People, and their unique interpersonal and creative skills, will be central to the future of work. How we structure this future, and prepare our workers, will say a lot about us as a society. Our decisions now will be a key driver of our economic success."
- Chief Executive Officer Richard Deutsch - Deloitte Australia

With this being said, it's important that we never push interpersonal communication skills to the side. At the end of the day, this important skill could be the deciding factor in your success.

6. Data analysis

With technology prevalent in every industry, it's demanding a shift for people to become more analytical. Traditionally, roles that may not have ever needed to look at data are now making decisions from insights. This is necessary so they can prove ROI and subsequently plan for growth.

Having the skills to analyse data is something well sought after in the ever-changing job environment. For example, traditionally, a content writer may have never looked at data. However, today they must look at the performance of their content and capitalise on trends to improve reach.

"A lifelong learning approach to skills development will be valuable for employees seeking to reskill and upskill their analytics capabilities as required." - Deloitte

Did you know Employment Hero has a data-driven learning management system? Learn more about it by having a chat with our business specialists.

The Australian gig economy and the future of work

According to the Actuaries Institute, $6.3 billion is the amount attached to the Australian gig economy between 2015-2019. Fairwork defines the gig economy as any individual that provides services to consumers for a fee via a digital platform.

It is important to keep this module of working in mind when considering what skills can be in-demand in the future, with considerations for new ways of working that may also be popular/

From Airbnb hosts to Uber drivers and crypto-earning marketplaces, a range of platforms can provide greater choice and flexibility in the way we live and earn.

Common gig economy services in Australia include:

Ride-sharing services

Delivery services (food, drinks and consumables)

Personal services (creative or professional services, e.g. graphic design and web development)

Handy-person services like yard work and repairs

The future of work goes beyond standard skillsets and considers an entrepreneurial way of thinking as people place importance on being their own boss and enjoying work/life balance.

Key takeaways

With technology leading the way in every industry, it's important you keep your soft skills up to scratch. Skills for the future such as creative thinking, leadership, communication and having a growth mindset can set you apart from the rest.

These skills allow for innovation in your work and preparation for the future of work.

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6 of the most in-demand skills for the future of work

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Are you ready for the future of work? Read on as we share the skills you need to continually develop to future-proof yourself and your team.

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Rana Adil khan (3)30111638 COVID-19 crisis and challenges for graduate employment in Taiwan, Mainland China and East Asia: a critical review of skills preparing students for uncertain futures

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Rana Adil khan (3)30111638 COVID-19 crisis and challenges for graduate employment in Taiwan, Mainland China and East Asia: a critical review of skills preparing students for uncertain futures

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This article examines the increasingly important challenges of postgraduate employment, particularly in relation to the transition from education to work. It acknowledges the increasing importance of these questions in the research of contemporary global higher education and also notes their impact on social and political debates. During exponential technological advances and the profound consequences of the COVID-19 pandemic, concerns about university employment, unemployment, and underemployment have been exacerbated, leading to a serious global economic downturn. The article deals with these complex issues, particularly in mainland China, Taiwan, Hong Kong and other East Asian societies. The ongoing global crisis requires a reassessment of the role of higher education in preparing students for rapid social and economic change. The report highlights the need for institutions to adopt a more flexible approach in order to equip graduates with the skills needed to deal with uncertain and dynamic futures. In addition, the article supports further research not only on postgraduate employment, but also on broader issues, including university governance after COVID-19. This research is crucial to understanding the multifaceted challenges posed by the changing labour market and adapting educational institutions to better prepare graduates for the complexity of the new labour market. Finally, the article stresses the urgency for higher education institutions to adapt to the needs of students facing an uncertain future exacerbated by the global crisis. It advocates more research to address not only employment concerns, but also broader governance issues in the post-COVID-19 period. This summary summarizes the main points of the article and focuses on the challenges of higher education employment, the impact of COVID-19, and the need for adaptive approaches to higher education.
Harvard reference
Mok, K.H., Xiong, W. and Ye, H. (2021). COVID-19 crisis and challenges for graduate employment in graduate employment in Taiwan, Mainland China and East Asia: a critical review of skills preparing students for uncertain futures. Journal of Education and Work, 34(3), pp.1–15. doi:https://doi.org/10.1080/13639080.2021.1922620.

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Beer, P. and Mulder, R.H. (2020). The Effects of Technological Developments on Work and Their Implications for Continuous Vocational Education and Training: A Systematic Review. Frontiers in Psychology, [online] 11(918). doi:https://doi.org/10.3389/fpsyg.2020.00918.

There are various reasons why this article seems reliable.

Clearly Stated Research Objectives: The article's goal is to give readers a general understanding of how technology advancements have affected the nature of employment and how these advances may affect ongoing vocational education and training (CVET). The study's two specific research topics provide it a well-defined structure.
The article provides a solid theoretical framework by referencing theories from a number of academic fields, such as psychology, educational science, economics, management, and sociology. This interdisciplinary method guarantees a thorough comprehension of the topic area and improves the study's credibility.

The article provides a solid theoretical framework by referencing theories from a number of academic fields, such as psychology, educational science, economics, management, and sociology. This interdisciplinary method guarantees a thorough comprehension of the topic area and improves the study's credibility.

Thorough Literature Review: One of the article's many methods is the thorough literature review that was carried out. on academic research, this method is generally recognised for its rigorous methodology, which guarantees that the study is grounded on a thorough analysis of the body of current literature in the topic.

Logical Clarity: The article gives definitions and concepts about technology and how it affects the nature of work in a clear and concise manner. The terms and concepts utilised throughout the research are made easier for readers to understand thanks to this clarity.

Various Viewpoints on Technology's Impact on Work: The article takes into account a number of different viewpoints on the subject, such as upgrading vs. deskilling, contingency theories, and task-based approach economic research. This method offers a more comprehensive understanding of the topic and enhances the analysis.

Work qualities: In order to fully understand how technological improvements affect the workforce, it is important to grasp how technology affects work qualities such as autonomy and meaningfulness. This article addresses these issues.

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In short the article exhibits credibility due to its well-defined research goals, robust theoretical framework, methodical approach, and incorporation of various viewpoints. It makes a significant contribution to our knowledge of how technology affects the nature of employment and what that means for ongoing professional development.

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How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan

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Yang, C.-H. (2022). How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan. Research Policy, 51(6), p.104536. doi:https://doi.org/10.1016/j.respol.2022.104536.

The article above informs how the artificial intelligence change the productivity on work and employment nature and it is a really relevant and credible source due to the various reasons

Relevance and Timeliness: The subject of how artificial intelligence (AI) technology affects employment and productivity in businesses is both highly pertinent and timely. It's critical to comprehend how AI affects businesses as it develops and transforms a variety of industries.

Tight Method: The paper uses an exacting method that includes identifying AI-related patents using a keyword-matching technique and using firm-level data on AI breakthroughs. This approach guarantees an accurate and data-driven analysis.

Comprehensive Approach: The study compares the effects of AI patents with non-AI patents in addition to analysing the impact of AI patents. A more sophisticated comprehension of the economic effects of AI technology is made possible by this all-encompassing approach.

Contribution to the Literature: The study adds to the body of knowledge already available on the financial implications of artificial intelligence (AI), particularly as it relates to employment and company productivity. It closes a research gap by offering firm-level proof on the topic.

Policy Implications: For stakeholders in the sector and politicians, the research has real-world applications. Policies and tactics for handling the possible effects of AI on the labour market can be informed by an understanding of how AI technology affects businesses.

Clearly Displayed: The study has a logical organisation and is divided into sections that discuss various parts of the research, such as how the findings affect employment and productivity. It is simple for readers to follow the study's conclusions because to this organization.

In conclusion, this article's relevance, thorough methodology, thorough approach, contribution to the literature, policy implications, lucid presentation, and appropriate citation of relevant work make it a great resource. It helps to a fuller knowledge of this crucial subject and offers insights into the financial effects of AI technology on businesses.

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Artificial intelligence (AI) has witnessed rapid advancement in the past decade alongside related technologies such as machine learning, robotics, and neural networks. Since AI has potential as a new general-purpose technology (GPT) (Trajtenberg, 2018), breakthroughs in AI-related technologies (hereafter AI technology) have revolutionized the development of new manufacturing technologies and products that can be applied to a wide range of fields, such as the Internet of Things, dark factories, autonomous vehicles, remote medical monitoring/diagnosis systems, and others. The AI revolution has induced manufacturing sectors to head toward intelligent manufacturing, which is undergoing continuous development. ¹ Undoubtedly, the pace and scope of groundbreaking development in AI technology can substantially change firms' production methods, thereby affecting firm productivity. Meanwhile, there are wide concerns and increasing debates on its potential to cause job loss and wage stagnation for most workers (Brynjolfsson and McAfee, 2015). Therefore, examining the influence of AI technology on firms' productivity and employment is crucial and topical.

Numerous studies have examined the productivity and employment effects of innovations on firms in the past few decades. A technological change is expected to enhance productivity which is a measure of a technology's economic contribution. However, firms may not obtain productivity gains through new technologies, even for a GPT. The "productivity paradox" claimed in Brynjolfsson (1993) indicated that while firms had an appetite for investing in information and communication technology (ICT), which was a GPT in the 1990s, it caused insignificant productivity gains. Possible causes include learning and adjustment, ICT management, and redistribution and dissipation of profits. ² As reviewed by Mohnen and Hall (2013), various innovation types-product, process, organizational, and marketing innovations-contribute significantly to firm productivity, whereas some studies find an insignificant or negative relationship.

The influence of innovation on employment is controversial. Product innovation can create new jobs (or at least does not cause job destruction), but it could possibly lead to a polarization of jobs, whereas process innovations (generally labor-saving) are mostly job-destroying. (Dosi and Mohnen, 2019; Staccioli and Virgillito, 2021). The job-creation effect of innovation is particularly relevant to high-tech firms (Van Roy et al., 2018). Distinguishing embodied from disembodied technological changes, their employment effects also differ (Dosi et al., 2021). A GPT, such as computerization, may put approximately half of all occupations at risk (Frey and Osborne, 2017), but workers' job duration depends on their skills and the technology-skill complementarities (Castro Silva and Lima, 2017). ³

Being an emerging and influential GPT, does AI technology promote firm productivity or does it also suffer from the "modern productivity paradox" (Brynjolfsson et al., 2019)? AI enables firms to find productive new combinations of existing technologies (Agrawal et al., 2019a), thus improving firm productivity. AI can be the command center of a manufacturing process management system to improve the efficiency of input usage, and to analyze and adjust equipment performance from data. Machine learning is suited for augmenting or automating tasks that involve at least some prediction aspects (Agrawal et al., 2017); that is, the automation production that was "programmed" by engineers can be replaced by machine learning or deep learning designed to learn the production patterns automatically from data (Brynjolfsson and Mitchell, 2017). Brynjolfsson et al. (2018) also indicated that AI machine vision systems have a lower error rate than humans for the same dataset. Therefore, the manufacturing instruments, i.e. robots, can perform a variety of hand-eye coordination tasks rather than routine machine actions (Levine et al., 2016). Thus, it helps to improve productivity.

Alternatively, AI technology may not generate productivity gains immediately upon commissioning (Jovanovic and Rousseau, 2005). The potential time lag in the productivity effect of AI technology may be attributed to adjustment costs, complementary innovations, and organizational changes (Brynjolfsson et al., 2019). In practice, the adjustment and combination of AI and existing technologies may not be successful. AI technology is not a panacea that can be applied to all production processes and firms. For instance, some sudden occurrences of production process might be managed and judged better by experienced workers; the magnitude and level of AI technology introduced into the production process may not fit well with the existing manufacturing workforce and technologies. This is because the effective use of AI technology relies heavily on big data that must adapt to firm-specific human capital and manufacturing processes. Workers often have no incentives to learn them, being afraid of losing their jobs.

There are wide concerns and increasing debates on its potential to cause job loss and wage stagnation for most workers (Brynjolfsson and McAfee, 2015). The introduction of AI technology casts the fear of an era of mass joblessness. Continuing progress on the predictive power of AI, the so-called deep learning technique, which simulates the human brain by learning from big data, empowers AI to replace humans in decision-making across many professional areas. The scope of replacement includes not only manual tasks but also intangible inputs (Jones and Romer, 2010) and organizational processes (Jarrahi, 2018).

AI technology can generate 3D virtual paths and programmable intelligence and enable machines to think intelligently in coordination with the simulation of many examples or data (Goldfarb and Trefler, 2018). Thus, AI may perform better than humans using the deep learning model to analyze previous examples/data and simulate various situations based on big data. For example, the IBM Deep Blue first won against a world champion in the 1996 chess match by evaluating the function from past board game records. A significant advance is Google AlphaGo: this supercomputer completed self-learning through an artificial neural network (a deep machine learning method) to improve chess-playing capability and beat the top-ranked chess player in the world in 2017. AI has also penetrated many organizational processes (Jarrahi, 2018). Through the deep learning algorithm system, AI has developed strength in dealing with organizational decision-making processes that are uncertain, complex, and equivocal. Thus, AI technology can replace not only manual and routine tasks conventionally performed by humans, but also tasks that are based on human judgment and decisions in manufacturing and management processes.

Brynjolfsson and McAfee (2015) and Agrawal et al. (2019b) thought that there is no obvious answer to the question of the AI-employment nexus. While AI technology may destroy some jobs, it may increase jobs at the low and high ends from an aggregate perspective. From the firm perspective, if AI technology supplements and amplifies tasks performed by workers, both production efficiency enhancement and product extension effects might generate more jobs. For example, although robots are flexible, versatile, and autonomous machines, the adoption of robots relies on their comparative advantage in specific tasks. Robots did not significantly reduce total employment, although they did reduce the employment share of low-skilled workers (Graetz and Michaels, 2018). Thus, the employment effects of AI technology are probably task- and skilled-based, altering the allocation of tasks to labor and capital of production (Acemoglu and Restrepo, 2019).

Although there are widespread concerns and debates on how AI technology affects firm productivity and employment, firm-level evidence is scarce. Therefore, more firm-level analyses on AI invention and its effects are required (Raj and Seamans, 2019). To fill this gap, this study uses a firm-level panel dataset of Taiwan's electronics firms to examine the impact of AI technology on firm productivity, employment, and workforce composition. This study contributes to innovation literature in the following ways. First, it provides one of the first pieces of evidence on how AI technology affects firm productivity and employment. Specifically, we examine the potential impact of AI technology introduction on workforce composition. Quantifying the impacts of AI technology can have policy implications for governments to ameliorate its potential impacts on the labor market. Second, we employ the keyword-matching approach to identify patents that describe AI technology. The U.S. Patent and Trademark Office (USPTO) has created several hundred patent classes, including AI-related patent classes, such as 706 (data processing: artificial intelligence) and 901 (robots). However, using only patent counts from limited AI-related classes may undercount the true scope of AI-related inventions (Alderucci et al., 2020). This keyword-matching approach identifies AI technology patents more precisely and is applicable to patent offices that adopt only the International Patent Classification (IPC) system, which is more adequate and has been adopted in some prior work in this area (e.g., Keisner et al., 2016; De Prato et al., 2019; Van Roy et al., 2019). Third, we compare the productivity and employment effects between AI and non-AI patents. Considering the fast technological change, the advance of non-AI technology can also have considerable impacts on firms alone, as examined in existing studies. Ignoring the impact of non-AI patents may overestimate the economic impact of AI technology.

The remainder of this paper proceeds as follows. Section 2 provides an overview of AI technology patents and reviews related literature. Section 3 describes the data and some stylized facts. Section 4 presents the empirical results of the link between AI technology and productivity in Taiwan's electronics firms. Section 5 presents the influences of AI technology on employment and workforce composition. Concluding remarks are summarized in the final section.

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How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan

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Artificial intelligence (AI) has witnessed rapid advancement in the past decade alongside related technologies such as machine learning, robotics, and neural networks. Since AI has potential as a new general-purpose technology (GPT) (Trajtenberg, 2018), breakthroughs in AI-related technologies (hereafter AI technology) have revolutionized the development of new manufacturing technologies and products that can be applied to a wide range of fields, such as the Internet of Things, dark factories, autonomous vehicles, remote medical monitoring/diagnosis systems, and others.

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Rana Adil khan (4) 30111638 Agriculture and the Generation Problem: Rural Youth, Employment and the Future of Farming

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Rana Adil khan (4) 30111638 Agriculture and the Generation Problem: Rural Youth, Employment and the Future of Farming

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The report discusses the critical issues related to young people's disinterest in small-scale agriculture and rural livelihoods,and the challenges associated with this trend in rural employment scenarios. It argues that although small-scale agriculture can bean alternative to sustainable employment,it requires the support necessary to compete with large-scale enterprises. However, this assumption faces a crucial challenge: the obvious lack of interest among the younger generation in agriculture or rural development.The emerging field of youth research highlights several factors that contributeto this phenomenon. Firstly,there is a worrying trend towards "deskilling"among rural young people,with reduced skills sets and a devaluation of rural life and agriculture.Secondly, the chronic neglect of small-scale agriculture and rural infrastructure exacerbates the unfavourable nature of agricultureas a viable career path.Finally,even if there is a inclination to pursue agriculture, the obstacle to land acquisition remains considerable for young rural people. Article signals the potential in sustainabilityof small-scale agriculture as a lucrative career option, emphasizing the need to address these relevant issues. It emphasizes the urgent need to revive the interest of young people in small-scale agriculture by focusing on skill development,changing the perception of agriculture,investing in rural infrastructure and facilitating access to land.Resolvingthese challenges isessential for small-scale agriculture to become an attractive and viable. This will enhance their future standards as well.
Harvard reference
White, B. (2012). Agriculture and the Generation Problem: Rural Youth, Employment and the Future of Farming. IDS Bulletin, 43(6), pp.9–19. doi:https://doi.org/10.1111/j.1759-5436.2012.00375.x.

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The Future of AI: Top Skills to Have in a Generative AI World

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“The Future of AI: Top Skills to Have in a Generative AI World”

Lee, E. (2023). The Future of AI: Top Skills to Have in a Generative AI World. [online] Acer Corner. Available at: https://blog.acer.com/en/discussion/948/the-future-of-ai-top-skills-to-have-in-a-generative-ai-world?gclid=Cj0KCQjw-pyqBhDmARIsAKd9XING4pq7-WtYa6dC7c_fJYg0ntMDAKGTKezuXuey_g6fqAhShgcqi5QaAp6REALw_wcB [Accessed 1 Nov. 2023].

This blog post written by Esme Lee discusses the future of artificial intelligence and highlights the top skills that people should possess in a world driven by generative AI. It emphasises the importance of understanding and working with AI technologies, as they are expected to play a significant role in various industries. Some of the skills mentioned are AI-Prompting skills, creativity, critical thinking and digital literacy.

The reason I picked this blog is that generative AI has become all the more popular in recent years and is a very important and relevant subject for the future of employment. As mentioned in this blog “AI’s automatic working power could eliminate as many as 300 million full-time jobs”, so it’s very important that individual are aware of this development and understand the changes in the nature of work. This blog was written by Emse Lee, she is a science writer and editor in the UK, also has a strong interest in tech and business copywriting. She also has a background in educational neuroscience and holds a PhD from the University of Cambridge. This is clear to me that Esme Lee has a very good knowledge and understanding of this subject so she appears to a reliable source of information. This blog was also last edited on the 13th of September 2023 so it is vary recent and reliable so there no need for any concerns of out dated information. And to add this blog was uploaded on an Acer website, Acer is a  Taiwanese multinational hardware and electronics corporation specializing in advanced electronics technology, so this blog on the skills needed to live in a world of AI was published by a well known technology company which further more strengthens the reliability and credibility of this blog.

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Generative artificial intelligence (AI), by its name, refers to any algorithm (such as ChatGPT) that generates content. This can take on multiple formats-whether it be visuals, videos, audio, text, simulations, or even code, generative AI has the power to change the workplace foundationally. OpenAI's wildly popular ChatGPT and Dall-E-2 are used for text and image creation respectively; the recent Google Bard is another example of a chat software that pulls information from the wider Internet.

Generative AI's capacity to create is simply unprecedented; in current times, when material can be produced in a matter of seconds with prompts, several types of traditional jobs are made redundant and a shift in skills will be needed to build a competent, AI-ready workforce. Graphic designers or writers may lose opportunities when a potential client can simply go to a cheaper, quicker robot; customer service representatives are in a similar boat, with AI being able to serve clients around the clock and with good efficiency. In health, machine learning can generate diagnoses of illnesses and even create customized treatment plans. Ironically, with generative AI's code-writing abilities, even coders who train in information technology itself may see their positions at risk.

These scenarios are by no means unreal or "too far in the future". Just this year, a Goldman Sachs report estimated that AI's automatic working power could eliminate as many as 300 million full-time jobs. Interestingly, however, through replacing jobs characterized by fixed thinking procedures, it is said that AI can potentially also yield a productivity bloom and perhaps even lead to a 7 percent increase in the annual value of goods and services globally.

The age of generative AI may be daunting, but it will be less so with the right knowledge, technique, and directions for training. The dynamics of AI now demand an interesting, renewed set of techniques for anyone who wishes to be a competent worker. Here, let's look at seven resourceful skill sets to have:

1. AI-prompting Skills

When thinking of applications such as Google Bard, Siri, Alexa, or the widely popular ChatGPT, what is the first step that springs to mind? That's right-to effectively use these AI systems, it is necessary to give the system instructions. These skills, known as 'prompting', help to form required responses in the shortest amount of time possible.

AI-prompting may seem like a simple input of instructions, but it does, in reality, require prolonged practice. Ensuring clarity of instruction itself is not always easy, and given how generative AI draws on information from massive datasets, it is imperative to be able to give scope and context, with just enough instructions. Knowing how to command systems in a way that makes it yield only relevant (no-nonsense) information is critical.

2. Digital Literacy

Generative AI can help humans achieve a limitless number of projects, but digital literacy-one's ability to navigate the IT world and create insight during the process-is essential for deciding what generative AI can realistically do in the first place. By extension, what applications it can have for specific fields is another important one to consider. What would AI imply for, let's say, nurses and teachers? How may these implications develop over the years? These are only a few of the many questions that workers with digital literacy can potentially answer.

3. Awareness of Cybersecurity and AI Ethics

In every realm of information technology, concerns about cybersecurity and ethics exist. AI systems can be vulnerable to cyber attacks, and in a similar vein, AI can also generate material for harmful actions. Deepfake AI, for instance, can mislead public perception of what is true and what isn't, potentially leading to crime that infringes upon intellectual property rights or other personal rights. With generative videos of celebrities saying things that they've never said, it isn't hard to imagine how some types of generative AI may cause public mayhem.

With the cyber landscape being more and more complex and "messy" with generative AI, it would be useful to have a strong awareness of what to look out for in relation to security and ethics.

4. Critical Thinking

Perhaps the most key skill in an AI age, critical thinking is central to human development more broadly and also the answer to solving AI-related problems. Generative AI is not perfect and may sometimes yield incorrect output (for instance, yielding a text with facts that are not accurate). Critical thinking, therefore, allows an individual to know what to verify in an overwhelming pool of AI-generated content; how to verify this content is equally important. Similarly, in a world where robots and humans co-exist, knowing what tasks to delegate to AI, and what type of innovation is needed for a business are still crucial tasks that only humans can decide.

5. Creativity

Generative AI creates content by drawing within set algorithms and finite databases. It can create complex technical instructions, but ultimately, only the human mind is capable of thinking outside of the box for novel ideas in creating products or finding solutions. The concept of creativity can be broad and it may take on different forms across industries. If the goal of generative AI is to create, then a skilled, AI-ready human would need to surpass that and produce an even more empowering, robot-proof product.

6. Interpersonal Skills

In an AI world where robots take the stage, interpersonal skills will not cease to be key. While interpersonal skills can bear many forms, a particularly irreplaceable quality that humans have is that of empathy. The sensitivity to what others think and feel is crucial yet often overlooked in business. It is worth remembering that the purpose of AI is ultimately to make human lives more convenient, and that businesses cannot run properly without the building of genuine human connections. Whether it be trust-building with different parties in a business setting, or understanding what clients need, interpersonal skills take time to develop and, for the moment at least, cannot be easily picked up by robots.

With the workplace being reliant on human critical thinking and creativity in an AI-powered world, strong teamwork would be needed to meet the demands of increasingly complex or novel projects. The communication of ideas and conflict resolution would therefore be vital to the progress of any workplace project.

7. Capacity to Learn in an AI Age

AI is bringing technology to develop at unprecedented speed, and it wouldn't be realistic for a single set of skills to last for an entire career. One's learning quotient (also known as LQ)--the capacity and willingness to learn-hence becomes rather key. Although it isn't possible for employees to possess every piece of knowledge on AI in the workplace, simply carrying the potential to learn, adapt, and apply new skills would be imperative.

How can these skills be cultivated?

These seven skills are easier said than done. Even if the technical skills can be trained over time (AI-prompting, cybersecurity awareness, and digital literacy), soft skills are often multi-layered and can take a lot of time to train. Although businesses can now offer future-proof training sessions, the fundamentals of critical thinking, creativity, and learning capacity may be best taught in school up until the workplace. That is, it would be helpful for both schools and businesses to equip the modern generation for a generative AI-heavy world.

Skills to have in a generative AI world: Light at the end of the tunnel

The rapid advent of AI may create fear among many of us, but it is also helpful to remember that no one is alone on the path to becoming AI-ready. Only a couple of decades ago, the global job market was compelled to adapt to the Internet in the workplace-while it did make many workers redundant, much of the world persisted, quickly adapting its workforce and cultivating IT skills on a massive scale. The future of AI will bring a transition like none other, but it will also stimulate humans to finally develop skills that are, well, inherently human- those wouldn't be easily replaceable by computers. Therefore, from a certain perspective, these skills inspire us to actually uncover the best of our potential. If you're looking to gear up with training for a LinkedIn profile renewed for the current age, there is no better time than now.

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The Future of AI: Top Skills to Have in a Generative AI World

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Generative artificial intelligence (AI), by its name, refers to any algorithm (such as ChatGPT) that generates content.

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"The 20 Skills and Competencies Everyone Needs to Succeed in a Digital World"

Marr, B. (2022). Future Skills. John Wiley & Sons.

This is a guide book written  by Bernard Marr that highlights the essential skills and competencies required to thrive in today's digital landscape. It covers topics such as data analysis, digital marketing, cybersecurity, and more.

The reason I chose this book is because it is very relevant to our topic and was written by a very well known reliable author. The author, Bernard Marr  is a bestselling author, keynote speaker, strategic performance consultant, and analytics.. He has also worked with and advised many of the world's best-known organisations. By his background it is clear to me that Bernard has the experience and knowledge of this subject and his words can be trusted. He also attended and graduated from Crafield School of Management and The University of Cambridge Judge Business School, this means he also has the relevant qualifications of understanding this topic. This book was published on June 2022, so it is over a year old but in my opinion it is still relevant and reliable for our topic and should not cause any concerns. I also chose this book because the skills that are discussed are directed towards a digital world and the future of work is technology, and this has become very clear since the covid-19 pandemic there has been a major advancement in technology in the workplace and this book begins by highlighting the importance of understanding and working confidently alongside technology.

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Future skills you'll need in your career by 2030

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Future skills you’ll need in your career by 2030”

Lukins, S. (2019). Future Skills You’ll Need In Your Career By 2030. [online] Top Universities. Available at: https://www.topuniversities.com/student-info/careers-advice/future-skills-youll-need-your-career-2030 [Accessed 2 Nov. 2023].

This article discusses the future skills that people  will need in their careers by the year 2030. It highlights the rapid advancements in technology and the changing nature of work, which will require individuals to adapt and acquire new skills. The article highlights several key skills that will be in high demand, including critical thinking, problem-solving, creativity, emotional intelligence, digital literacy and adaptability.

To begin, the main reason I chose this article is because the first thing that is discussed that interested me is that people of the future will likely working a job that doesn’t exist yet. And in terms of our subject this is very relevant because individuals will need to develop skills for job roles that don’t exist yet and are “impossible to predict” This article was last updated on the 1st of June 2023 and originally published in 2019 which makes this article relevant because it’s in recent years and solely discusses skills for 2030. But what makes this article trustworthy is it’s author, Stephanie Lukins, she  created and published a wide range of articles for universities and business schools across the world. So this isn’t a new topic for Stephanie, it shows that she has experience and knowledge in this subject. And her background, she attended the University of Portsmouth where she earned a BA in English Language and an MA in Communication and Applied Linguistics. This doesn’t show that she is officially qualified and all knowing for this subject so this could question the article’s credibility but the skills she discusses counteracts this point as she brings up many interesting and relevant ideas for the skills we will need in the future.

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Sponsored by the University of the Witwatersrand
In 11 years' time, the year 2030, it's highly likely you'll be working in a job that doesn't even exist yet - and no, we're not talking about building flying cars or developing the world's first time machine. The world of work is evolving quickly, which means you have to figure out how to prepare for a future job role that's impossible to predict.

Of course, there isn't a crystal ball that can tell us exactly what skills will be needed and what won't be needed. However, with the help of the University of the Witwatersrand, we've come up with five skills we believe you'll need to succeed in your future career, whatever it ends up being.

Cognitive flexibility

The rise of digital technologies means you're going to need to be able to handle the plethora of opportunities and challenges that come with it.

Do you have the ability to adapt to change and conceptualize complex multiple ideas all at once? If so, you're showing qualities that reside in advanced multi-taskers and which are highly valued by employers and recruiters.

Digital literacy and computational thinking

As the world continues to rely on highly technical and continuously evolving technologies, the need for those with the digital skills to match also increases.

You've most definitely heard of STEM, but have you heard of SMAC (social, mobile, analytics and cloud)? Although it may seem like we're being bombarded with digital buzzwords, being digitally literate offers capabilities beyond what was once thought possible when it comes to emerging technologies, such as artificial intelligence (AI), machine learning, Internet of Things (IoT), and data science.

"We need to train scholars to deal with the challenges of the 21st century, some which we may not yet have encountered," says Professor Adam Habib, Vice-Chancellor and Principal of the University of the Witwatersrand.

"We need to work across sectors to develop the technology required for us to leapfrog across eons of poverty, unemployment and inequality, and in so doing to create a new world order that prioritizes humanity before profits and power."

A master's degree in artificial intelligence or e-Science can help advance your digital skillset and accelerate your technical acumen in these emerging fields, from learning about data visualization and exploration, to computational intelligence, and natural language technology.

Judgement and decision-making

Although robots and automation technology may be better than humans in other ways such as calculations and diagnostic solving, it's still going to be humans that deal with the subjective side of data analytics.

Considering we're on the cusp of the fourth industrial revolution, we're still going to need to have somebody who is able to show the world what numbers mean and their significance.

Emotional and social intelligence

For everything that can be replaced by digital technologies and artificial intelligence, emotional and social intelligence remain uniquely human capabilities.

In some sectors, these qualities are absolutely crucial. The demand for jobs in healthcare, for example, are on the increase - demonstrating how some roles will always require a human element. Your future job is more than likely going to include working closely with others, so having empathy, the ability to collaborate, as well as excellent communication skills is something you're most definitely going to need.

Creative and innovative mindset

Despite a report by the World Economic Forum in 2018 suggesting robot automation will create more jobs than they displace, you'll still do well to keep on top of your creativity skills and maintain an innovative mindset.

Much like having an excellent sense of social intelligence, natural creativity is something which can't be easily replicated by the latest digital technologies. As long as you can think outside the box, you'll be just fine.

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Future skills you'll need in your career by 2030

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Discover the five skills employers will be looking for in the future and how you can get them.

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The Employability Skills Needed To Face the Demands of Work in the Future: Systematic Literature Reviews

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The Employability Skills Needed To Face the Demands of Work in the Future: Systematic Literature Reviews

Fajaryati, N., Budiyono, Akhyar, M. and Wiranto (2020). The Employability Skills Needed to Face the Demands of Work in the Future: Systematic Literature Reviews. [online] Degruyter.com. Available at: https://www.degruyter.com/document/doi/10.1515/eng-2020-0072/html?lang=en.

This article discusses the impact of technological advancements, such as automation and artificial intelligence, on the job market and the workforce. The article examines the potential benefits and challenges associated with these changes, including job displacement, skill gaps, and the need for lifelong learning.

The main reason I chose this article is that it discusses what is needed for individuals to succeed in future job roles, it discusses that it is important for “institutions of education to prepare their students who not only have technical skills but also employability skills.” I believe this is relevant to our topic because it discusses how we will develop these future skills and how it will help us succeed. This article was published on the second of July 2020, and in terms of our topic I believe this is still relevant for today. The writers of this article are all from the Sebelas Maret University, which is a top 10 business school from Indonesia, so it’s safe to say that they are all qualified and have the education and knowledge of this subject, so this strengthens credibility and reliability of this source. The only concern I would have with this source is because they are from another country it is hard to find further information on their background, if I could find further information on them it may show some inexperience and make the credibility questionable. But overall the things that are discussed are very relevant in the development of future skills for employment.

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1 Introduction

Employability skills are indispensable in the current era of technological disruption and globalization. Employers complain about the insufficiency of skills among the workers [ 1]. Approximately 75 million young people in developing countries are unemployed, and in most countries, youth unemployment rates are 2 to 4 times higher than adults. Further, education providers must support them with knowledge and skills either soft or hard skills relevant to the world of work to make them productive and able to be employed by the industry. Beside technical skills, employers are looking for workers who have some abilities in communication, collaboration, problem solving, and critical thinking ability. More than 50% of stakeholders could not find the right competencies in job seekers in accordance with the vacancies they provided so that more than 80% of jobseekers failed to get a job [ 2].

The disruption and globalization era inevitably presents a formidable challenge for the community related to the opening of countries around the world in this case regarding products, services, and labor migration between countries. They also have brought many widespread changes in the world of business, banking, transportation, social society, and even education. The ability to deal with those changes in the era is deemed critical then.

Disruption initiates a new business model more innovatively. The conventional ways, in turn, are abandoned and moved to technology and digitalization. It has caused various problems, including high unemployment.

The high level of unemployment is often associated with the failure of the education system in generating graduates supported with employability skills and high competitiveness. Lack of expertise among job seekers is the cause of increasing unemployment [ 3]. If the skills' gap of the job seeker is related to the world of education, then this problem is related to the issue of education quality.

Based on the problems, it is necessary for the institutions of education to prepare their students who not only have technical skills but also employability skills. The biggest challenge in education today is to generate graduates who have academic skills, ability in mastering technical skills, and balanced employability skills [ 4]. Employability skills are knowledge, skills, and competencies that workers need to have in improving their ability to get and keep a job, progress at work, face change, get other jobs if the worker wants to quit from a job or dismissed and enter more easily into the labor market at different periods of their life cycle. People will be more easily employed if they have extensive education and training, high skills, ability to work in teams, the ability of information and communication technology (ICT), ability to solve problems, and communication skills. This combination of skills enables them to adapt to the changes in the world of work [ 5].

People need to develop their potential to have employability skills. This is supported by the Australian Government stating that employability skills are important not only to get a job but also to develop their potential for company success [ 6]. In addition, people should have the following skills to survive in the job market, including the ability to communicate, problem solving, working in teams, long life learning, and being adaptable to change [ 5]. This statement is in accordance with the Indonesian Middle Term Program Plan (RPJM) from 2020-2024 stating that to improve the qualified and competitive human resources, it is needed to gain qualified instructional as well by integrating soft skills [ 7].

Based on the problems and the importance of students as prospective workers having employability skills and becoming graduates who are ready to work and to be accepted by the workforce, it is deemed necessary to identify the employability skills needed by employers as an effort to face the disruption era.

Considering the importance of employability skills, this research collected data from previous studies that discussed employability skills to deal with the era. In addition, this literature study contributes to show the work skills needed by employers so it can assist education providers in preparing their students to enter the work-force.The data were collected from 2014 to 2019 and they were identified using the Systematic Literature Review (SLR) and mapping method. By the SLR and mapping Method, a systematic review and journal identification can be carried out in each process following the steps or protocols set. The SLR and mapping method can avoid subjective identification. Futhermore, different with other literature reviews proccess, systematic review and mapping methods are employability skills needed by the workforce and reduce bias. It is expected that the identification result will be the literature in terms of of the SLR and mapping method use in journal identification.

2 Research Methods

2.1 Method Review

This research was conducted using the Systematic Literature Review (SLR) and mapping approach - a process of identifying, categorizing, analyzing, evaluating and interpreting all research relevant about employability skills in order to figure out in an auditable, accurate, and fair way [ 8]. It can also be stated as a process of identifying, assessing, and interpreting all available research evidence with the aim of providing answers to certain research questions [ 9]. According to Kitchenham [ 9] and Neiva, David, Braga, and Campos [ 8], this review comprises three main stages:planning, conducting, and reporting the study.

2.2 Review and Mapping Planning

The first stage consisted of identifying needs and developing a review protocol. In Phase 1, the purposes of identifying needs were to find out the definition of employability skills according to the researchers, to identify the types of employability skills needed by employers, and to figure out the way to implement employability skills in learning according to the researcher's suggestions. Phase 2, meanwhile, was to develop a review protocol by making a research question. The research questions are divided into mapping questions and SLR questions. The Mapping questions are useful for brainstorming in the very beginning steps of a literature study and directing the scope to be studied. The questions used in systematic mapping are as follows:

MQ 1: Which article discusses the most comprehensive about the employability skills needed by employers?

MQ 2: Which article discusses the most complete process of learning employability skills in school?

MQ 3: What research method is the most widely used researcher to assess a person's level of employability?

Then, the SLR research question are as follows:

1. RQ1: What is the definition of employability skills according to the researchers?

2. RQ2: What are the types of employability skills required by employers?

3. RQ3: What are the types of employability skills needed by employers in the industry revolution 4.0 and the future?

4. RQ4: How should the education system implement employability skills in school?

2.3 Review and Mapping Conducting

The second stage of SLR is conducting, which consists of five steps: research identification, selection of primary studies, study quality assessment, data extraction & monitoring, data synthesis.

1. Identifying the search terms from research questions

2. Identifying search terms in years, titles, abstracts, and relevant keywords. Articles used were between 2014 - 2019.

3. Identifying synonyms, alternative spellings, and antonyms of the search terms [ 10]

1. QA1: Are journal and proceeding articles published in 2014-2019?

2. QA2: Do journal and proceeding articles provide a clear definition of employability skills?

3. QA3: Do journal and proceeding articles state clearly about the employability skills required by employers?

4. QA4: Do journal and proceeding articles state clearly about the employability skills needed in the industry revolution 4.0 and in the future?

5. QA5: Do journal and proceeding articles discuss how employability skills should be applied in schools?

1. Y (Yes): for journal and proceedings articles published in 2014 - 2019

2. Y (Yes): for journal and proceedings articles providing a clear definition of employability skills

3. Y (Yes): for journal and proceedings articles clearly stating the employability skills needed by employers

4. Y (Yes): for journal and proceedings articles clearly stating the employability skills needed in the industry revolution 4.0 and the future

5. Y (Yes): for journal and proceedings articles discussing the implementation of employability skills learning in schools

6. N (No): for journal and proceedings articles not writing the criteria in the question above.

3 Review and Mapping Report

3.1 Significant Journal Publication

In this systematic literature review, 66 articles, both journals, and proceedings were found after going through the planning and conducting process. The articles obtained were from the IEEE, Springer, and ScienceDirect publishers. The search results were then be reselected through inclusion and exclusion criteria.

3.2 Results of Inclusion and Exclusion Criteria Selection

The results of the search process have been selected based on inclusion and exclusion criteria. Of 66 significant articles, there were only 15 articles left and then data scanning was performed. Figure 2 shows the grouping Journals and Proceedings of search results.

The results indicate, only eight journals and seven proceedings fulfill the inclusion and exclusion criteria.

3.3 Quality Assesment Result

Table 2 below shows the results of the Quality Assessment.

Based on the results of the quality assessment from the primary study above, all articles, both journals and proceedings published in 2014 - 2019, were used in this SLR research and answer QA1. Eight articles providing a clear definition of employability skills (QA2), all articles state clearly about the employability skills required by employers (QA3), only four articles state clearly about the employability skills needed in the industry revolution 4.0 and in the future (QA4), then five articles discuss how employability skills should be applied in schools (QA5). The data were chosen for having sufficient problems, approaches, and information about the issues raised in the study.

Meanwhile, to answer the mapping question (MQ1), an approach to note-taking is carried out. From the results of the analysis of the 15 articles above, there are 5 dominant articles discussing the employability skills needed by employers. But the most comprehensive and clear in describe employers' needs for employability skills that job seekers must have is Pengnate's research [ 11]. Another advantage, Pengnate used forty (40) employers from four (4) industry sectors as respondents. The data obtained is obviously gained from the stakeholders, as job seekers recruiters.

The identical approach is carried out to answer MQ2. There are 4 dominant articles discussing learning process of employability skills. On the other hand, the most completed research article in depth exposed of learning process and employability skills transfer towards students was done by Jayaram and Engmann [ 15]. This study explores about the innovative and effective instructional model along with its on target successfulness principles that must be delivered to improve employability skills needed by employers.

Regard to MQ3, the research method applied from those 15 articles includes development, quantitative by questionairre, qualitative in interview, and literature study research. From all the researches as mentioned above, literature study is most commonly used as research method.

4 Review and Mapping Discussion

4.1 Systematic Mapping Discussion

Through a note-taking approach, it has been done a systematic mapping to gain an answer from the research mapping (MQ) and the research questions (RQ). Regarding this, a research done by Pegnate is the most comprehensive and clear in discussing employability skills needed by employers. He points out research on employers' perception on employability skills needed on the career field through questionnaire. The employability skills needed by the employers are personal qualities; core skills; and subject knowledge. The researcher also states the suggestions towards the educational institution about things to do in assisting the students with working skill. On the other hand, this research has not exposed clearly and in details in how to assist them with working skill through instructional process at school. He only gave general description in terms of improving instructional process on working based, training to meet the career field needs, and personal quality improvement (11).

Whereas, the article published by Jayaram & Eng-man was the most completed of all discussed employability skills. Itexplained the innovative and effective instructional models involving its principles to improve employability skills needed by employers. This article shows on how to establish an innovative model to transfer the skills to the students and its supporting needed to create an effective model. It also includes the use of innovative information, communication, and technology (ICT), stakeholders-multi partnership, innovative budgeting mechanism, and ascertain the readiness of teachers and trainers.Moreover, the supporting environment for a policy is very important to make sure that the model is financially supported efficiently, applied effectively, and continuously in long term (15). In contrary, the explanation in this article only gives a general description while the detailed implementation technically has not exposed clearly yet.

During answering the mapping question, the other interesting facts were revealed. One of them there are articles that discuss the development of a weighted score clustering model that can identify the level of students employability skills. After being identified, the education provider determines the specific skills training that needs to be held to improve their employability skills. The development of this model is carried out considering the importance of employability skills when graduates enter the workforce. However, the model was developed only to identify problem solving and thinking skills, while other employability skills components have not been developed [ 13].

Beside model development, it was found system that was able to assess students' aptitude, soft skills, and subject knowledge. This will prepare them better in the competitive workplaces and have work readiness. But the system developer does not clearly state what indicators are used to evaluate students' aptitude and soft skills.Actually these indicators are very important to know and can help other researchers who want to develop a similar system as an effort to increase employability skills. In addition, the way that needs to be done to correct these deficiencies is not suggested more deeply by researchers [ 14].

Other articles tend to reveal what employability skills are needed by employers [ 12, 16, 17, 18, 19, 21, 22, 23, 24, 25], the gaps between the desire to transform students' life skills through learning process and educational curriculum with the needs of workplace [ 16, 19, 24, 25] and how should the education system implement employability skills to face the demands of employment and the industrial revolution 4.0 [ 17, 20]. These studies are interesting because they illustrate the needs of the world of work today and the future and what education providers need to do to overcome these problems. However, most researchers only give some simple pure expressions and general comments.

4.2 RQ1: What is the definition of employability skills according to the researchers?

Employabiliy skills are the personal attributes enabling the people to get a job and support an individual's career life more easily. They are a set of skills to perform a particular job including technical skills, higher order thinking skills, personal skills, people skills/social skills, generic skills, and self-perceived employability skills. The lack of employability skills may cause unemployment and hinder people's career development. To be successful in their work, people need to have employability skills or a mix of them in addition to have technical skills. It is very important for individuals to have those skills. Technological development might influence the employability skills required. Therefore, people are required to renew their skills in accordance with the demands of the workplace, otherwise, it will be difficult for them to get involved in the desired work/industry [ 11, 14, 26, 27]. Then, the OECD stated that employability refers to an ability to find a job and adapt to labor market demands [ 28]. Employability skills are non-technical skills needed to enter the workforce, to stay afloat and develop a career in the workplace, or for career development in a new workplace [ 29]. In summary, employability skills are the set of skills employees should have to perform a particular job and to adapt to any changes in the workplace.

4.3 RQ2: What types of employability skills do employers need?

Researchers stated that employers demand their employees to develop all the skills and knowledge to produce a better result and improve performance [ 30]. From the literature study, one of the results of the research stated that employers need employees who have three key types of skills: cognitive, non-cognitive, and technical. Although basic cognitive and technical skills are important in the workplace, non-cognitive skills such as communication, punctuality, problem solving, and flexibility are most important [ 15]. Additionally, employers need those able to adaptable in a dynamic work environment [ 27].

In short, according to the review of literature, as shown in Figure 3, most employers seek candidates who have skill in communication, technology, problem solving, and team working.

The study results have been supported by Brewer that employees must have continuous learning ability and adaptability; communication skills; independent problem solving ability; technological skills, creative thinking skills and ability to work in a team [ 5]. This statement is in line with the other researchers explaining that employers are looking for employees who have employability skills such as the ability to communicate effectively and work in teams [ 31]. Further, employers expect that these soft skills will sustain technical expertise possessed by job seekers, so they are able to solve problems encountered while working [ 14].

4.4 RQ3: What type of employability skills needed by the world of work in the industry revolution 4.0 and in the future?

In the era of technological disruption of the industrial revolution 4.0, it is not enough to have technical skills, but it is necessary to develop methodological and social skills [ 19]. Another opinion stated there are the top three skills that are highly needed in the future include cognitive abilities, complex problem solving skills, and systemskills [ 31]. This is supported by the World Economic Forum, which states that new skills are needed to face the industrial revolution of 4.0 [ 32]. Further, BRICS (Brazil, Russia, India, China and South Africa) declared that the important skills to have for Industry 4.0 are knowledge about ICT, the ability to work with data, technical know-how, and personal skills [ 31]. While the BRICS personal skills' indicator is almost the same as the eight skills grouping of the Australian Government's employability skills framework. The eight skill groupings are communication, team work, problem solving, initiative and enterprise, planning and organizing, self-management, technology, and learning skills [ 6].

In addition to hard skills and formal qualifications, employers also place importance on the practical skills or competencies of new prospective employees to successfully carry out various work tasks. A range of skills relevant to work widely used in the era of disruption and in the future includes three main groups: cognitive abilities, basic skills, and cross functional skills [ 32]. Then, the World Economic Forum stated that the top ten of skill demand by 2020 will be dominated by soft skills and technological skills [ 33]. This shows, although technology is developing rapidly, soft skills and technological skills are still very needed in the industry revolution 4.0. and in the future.

4.5 RQ4: How should the education system implement employability skills in school?

According to the study of the literature review, it can be concluded that strengthening employability skills for students is no longer an option, but a necessity that needs to be done by the education system. If the employability skills of young people are the problem that needs to be solved, the school must support the development of competencies and skills for students who do not have or lack the skills needed in the workplace. Therefore, educational providers need to think about how to implement appropriate teaching employability skills for students. The education system needs to provide students with direct learning that reflects real-world problems and work opportunities in an interdisciplinary way [ 34]. This statement is supported by Anderson and Gantz that in facing the acceleration and development of the world of work, education providers in making learning objectives must consider a number of the core skills that employers/stakeholders expect to have when they graduate [ 35].

Based on the primary study, a researcher exposed that to have a readiness for fresh workers and give a relevant working skill by the career field or working are, it is needed an effective and innovative model to improve working skill required by employers. Instead of a model to transfer it in order to be adopted properly by them, it is also necessary a support to gain it in effective way. It focuses on the improvement of input , output, or process. Innovative ICT's and Teacher training resources which involve into the input are in line with the emphasis on non- cognitive skills and workplace learning as in output. Last, the process itself covers innovative financing and multi-stakeholder partnership. The researcher explained that it is required to have teachers' readiness to deliver the content of knowledge effectively and being able to keep and apply it in long term. It is done to set them be ready getting into the working area. That is why, it is obviously crucial to make a joint partnership between the educational institution and the industry area to create an effective curriculum. Moreover, the researcher declared that the use of innovative ICT will expand its learning experience, having flexibility in time and space, and building their independent in learning. The ability to learn independently is what needed by the employers. The emphasization on learning at the working space and non- cognitive skill are absolutely essential as it plays very important role as their outcomes while getting into the working area. Some aspects will contribute more in this way to create an effective model consisting of a) skills gap analysis, b) curriculum articulation, c) assessment and accreditation, d) industry involvement and accreditation, e) communication and information sharing [ 15].

Another opinion states the implementation of employability skills in school can be done by combining the skills needed in the workplace in the learning process [ 14]. The education system needs to embed the employability model into the curriculum to bridge the gap between what skills industry needs and what skills the graduate [ 27]. The economist added that to be effective, employability skills must be integrated into every subject area so that the skill development becomes inseparable from knowledge sharing because soft skills cannot be taught in an isolation [ 36]. For example, in Indonesia, as stated in the RPJM 2020-2024 to improve quality and competitive human resources, one of the government's efforts is to improve the quality of teaching and learning by integrating employability skills in the learning process [ 7]. This is supported by Munadi research stating that employability skills in the form of communication are taught by discussions, questions and answers, and presentations. Teamwork which includes the division of tasks and respect among group members is learned through groupwork,while problem solving is learned through discussion of given tasks [ 29]. If an education system want to prepare the graduates to be tomorrow workforce, then they must develop lifelong learners [ 37]. In addition, in the learning process, educators need to consider how to improve and hone the skills needed by the world of work today and in the future.

Referring to the literature study, the most required employability skills component by the employers are problem solving skill, team working, communication and the usage of technology to be integrated in the instructional process. Those four models are truly significant in social learning model. This model supports the employability skills where social and intellectual aspects can be learned together. One of the model in social learning in group investigation. It trains the skills of problem solving, cooperation, and communication.As an addition, it is assumed that this model is able to deliver knowledge academically by involving social aspects [ 38]. To go deeper on the skill in utilizing technology, it needs a blended learning. The combination of group investigation and blended learning can be taken as the way to improve students' employability skills. It is an activity and learning format that runs through direct meeting and online with some characteristics as follows; 1) student centered on active and creative learning, 2) the rising interaction between student- instructor, student-student, student's content, and the resources of student-external factor, 3) formative and summative evaluation mechanism to be integrated student and instructor [ 39]. It is also in accordance with instructional that focuses on the future. In brief, the mixture between group investigation model and blended learning is one of the ideal way to accelerate students' employability skills.

5 Conclusion

Employability is a skill that individuals should have to continue their career in life. To face global competition and future world work, individuals need to renew their employability skills. Based on the results of a study from 15 kinds of literature, employability skills must be owned by workers according to the employer including communication, team working, problem solving and technological skills. Then, the relevant skills towards working are widely used in the era of disruption and in the future including three main groups: cognitive abilities, basic skills, and cross functional skills. But most of the projected skills in the future will be dominated by soft skills and technological skills. Because of the significance of employability skills, the education system needs to apply employability skills in every learning process. As in Indonesia, to improve quality and competitive human resources, the government in accordance with the technocratic design of RPJM 2020-2024, seeks to improve the quality of learning through the integration of employability skills in each subject.

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The Employability Skills Needed To Face the Demands of Work in the Future: Systematic Literature Reviews

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The qualified human resources with high competitiveness and employability skills are needed to face the era of technological disruption, but employers find a lack of expertise among job seekers. Insufficient skills are related to the issue of education quality.