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Explore the dynamic relationship between AI and human workers, delving into whether AI will compete with or complement the human workforce. Understand the potential for job displacement, productivity gains, and the future of collaborative intelligence.
Laiba Abdullah
Jul 24 2024 02:58 PM
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AI vs. Human Workers: Competition or Co-Creation?

Introduction

Of the most pressing debates of our time, one was bound to arise with the coming of artificial intelligence: "AI versus Human Workers: Competition or Co-creation?" Invariable discussion revolves around whether AI is going to substitute the human workforce, rendering jobs of humans redundant, or whether it will give a new look to coexistence and collaboration between AI and humans. This article shows whether AI is a threat to human employment or will be a new beginning for both of them. Secondly, covering fears of job displacement, aspects of productivity enhancement, and ethical considerations, we will provide a detailed overview of AI towards employment.

Will AI replace jobs with human beings and create a tsunami of unemployment? Or will they work with enhanced productivity and innovation to signify a new partnership phase between AI and humans? In this chapter, we want to get into a balanced view regarding the prospects of job displacement due to AI, the productivity gains that AI can bring in, and ethical considerations. Hopefully, our objective analysis of such factors will help to clarify whether AI is a threat to human employment or a technological wonder that marks the inception of a new era of collaboration.

Overall, AI's effect on the workforce is thus two-edged, filled with challenges and, at the same time, an array of opportunities. One does have a cause to worry about the issue of job displacement. But at the same time, one cannot easily overlook that AI could also give way to new opportunities, meaning enhanced productivity. If correctly done, these may aid in tapping AI as a tool for human empowerment rather than disruption.

The Impact of AI on Jobs

Displacement Fears

One thing that cannot be denied is the fact that majority of organizations are hel d with anxieties of AI taking over human employees. For instance, depending on the types of industries involved, the trends have seen higher losses in employment such as in manufacturing and retail industries because of mechanization. World Economic Forum has predicted that because of automation a total of 85 million jobs are likely to be displaced by 2025 whereas a total of 97 million new roles are expected to exist (World Economic Forum, 2021). The possibility of getting displaced at such large intensity, evokes tension in the hearts of every worker, and especially the workers who work low-skill repetitive common jobs that are likely to be automated. It is therefore fears caused by instability and volatility of these changes which have sparked off sorrows in employment security and future prospect. At the same time, it can be mentioned that it also creates new employment opportunities for people. Most of these new roles of work are likely to entail technical proficiency, innovation, and empathy – the relative strength of humans over artificial intelligence. In other words, there are certain drawbacks of automation, but at the same time, it opens the doors to create new and possibly more meaningful occupations.

The Shift to New Roles

While some jobs may vanish, artificial intelligence technology will also spawn new jobs that never existed before. These will likely be new types of jobs in fields that require high levels of technical skills, creativity, and emotional intelligence, all of which humans currently are better at than machines. Another profession, according to the same report by the World Economic Forum, is the area of AI, data, and digital marketing, for which people will need to be capable of learning and adapting constantly.

Figure 1 Impact of AI on jobs and productivity

The Benefits of AI in the Workforce

Enhancing Productivity

AI can dramatically improve productivity by taking over all of the tedious, repetitive work. The human workforce can then allocate more time to the challenging and creative parts of their job. For example, with customer service, AI sorts out the simple queries, and then the human element comes in for further, more complicated inquiries. In this respect, PwC says AI could be adding about $15.7 trillion to the global economy by 2030. This increased efficiency could lead to economic growth and returns to labor, possibly working on tasks that require more skill.

Improving Decision-Making

AI's potential effect on vast amounts of data will improve business decision-making. For example, AI-based analytics provide input that helps companies make strategic choices. This way, supported by Accenture as of 2022, through 2035, AI may boost labor productivity by even 40% (Accenture, 2022). For finance, medical, and logistics areas, AI contributes to raising numerous predictions' accuracy, including the performance of operations and forecasting, performing most excellent practice, and effective resource management due to crunching numbers.

It is something that the field's foremost thought leaders are suggesting: not competition but cooperation between humans and AI. Such collaboration has been termed "cooperative intelligence" and leverages the strengths of AI and human workers—the creativity, emotional intelligence, and the ability to tackle complex problems set out by humans on the one side, as well as speed, scalability, and processing power attributed to AI on the other. Put together, human intuition and the analytical strengths of AI can be dynamite in boosting innovation and efficiency in several sectors.

AI and Human Co-Creation

Rather than viewing AI as a competitor, many experts advocate for a collaborative approach where AI and humans work together. In healthcare is supporting doctors to analyze medical images and predict outcomes of patients—which is improving both diagnosis and treatment. A good example is the current AI systems developed by IBM—the Watson For Oncology helps Oncologists make customized treatment plans by reviewing extensive medical literature and patient data. Similarly, in finance, AI guides an analyst through large datasets to extract trends and make recommendations about activities. The aforesaid are examples of creating value co-creatively between AI and humans. In manufacturing, for instance, AI-run robots engage with human workers to make tasks more efficient and safer for them. In particular, the type of robotics technology involved is termed "collaborative robots" and are also known as "cobots," meaning that they are intended to do something in support of human beings, especially in operations with great precision and endurance, and thereby to reduce the physical burden on human workers.

The Future of Work: Skills and Adaptation

Reskilling and Upskilling

The more conclusions are drawn towards the application of AI in the workplace, the further spread of new skills that will be required will be achieved. This poses the need to adjust the worker so that they are compatible with the working environments created for AI systems. It has become established and remains clear that government and businesses in general need to consistently and constantly train the workforce. This is due to the fact that the World Economic Forum anticipates that by 2025, over 50 percent of the global workers will require to be reskilled (World Economic Forum, 2021). The idea of learning throughout one’s working experience and constant shift in general have become rather more significant in the modern world.

Lifelong Learning
 Continued education is needed due to this seeming high rate in the development of technology. Lastly, institutions and organizations should develop a culture of learning throughout the workers’ lifecycle so that they arrive at the right level that can adapt to the technological changes. For this reason, learning is understood broadly in this case, incorporating technical skills as well as critical thinking, creativity, and the like, up to and including soft skills. Continuing education implies that one is ready for any other requirements that may come in the future with regards to the job market.

Ethical Considerations in AI Integration

Fairness and Bias

One of the most critical challenges being experienced in AI implementation is providing fairness and avoiding bias. AI has sometimes perpetuated the biases intended to obviate unless closely designed and monitored, such as partial algorithms used in the hiring process sending signals on gender and racial gaps. The developer must remember ethical AI in their development process so that it automatically applies to the AI system upon deployment. Just recently, in 2022, a study by MIT claimed that the end product, or the result of a discriminating AI system, imposes the need for a thoroughly tested and validated system to make unbiased decisions.

Job Quality and Work-Life Balance

While AI can improve productivity, its impacts on job quality and the work-life balance must be considered. Since the first use of AI is to upscale working conditions and the work environment, it must not be applied to cause stress or create overwork. For instance, the gig economy benefits significantly from AI-driven scheduling systems that maximize work hours to the fullest potential. Still, they run the risk of having schedules that are both unstable and unpredictable. Employers should strike the golden mean whereby workers benefit from AI, but at no single point should their well-being be compromised. This is humane and fair labor practices in the age of AI, where development can also be made sustainable.

Case Studies of AI and Human Co-Creation

Healthcare Innovation

AI has created new potential to supplement human abilities, particularly within the healthcare sector. For instance, in radiology, an area in which AI can be of importance, the AI algorithms used to assist in the analysis of medical images are pretty accurate. This helps radiologists to identify conditions like tumors and fractures. However, a report came out in The Lancet Digital Health in 2022 that declared an AI system developed by Google Health to detect breast cancer performs better than radiologists. But again, the radiologist has to affirm and then interpret the results by the AI for the benefit of the patient.

Financial Services Enhancement

AI has been developed for risk assessment and detecting fraud in the financial segment. They detect possible activities of fraud concerning the patterns of transactions. This way, the financial institutions remain very watchful to prevent themselves from fraud and keep the assets of their customers safe with alertness. AI-powered chatbots give improved and customized customer banking service for queries and even routine activities to maximize customer satisfaction. One of the recent reports by Deloitte states how, in 2021, the changes with an increase in analytics based on AI, financial firms are changing their strategies, including risk management.

The Role of Policy and Regulation

Government Initiatives

This is a section that delineates what governments of various states are doing in terms of facilitating the development of AI and creating policies and regulations with aims at the regulation of AI and work-related activities. For this very reason, there has to be the establishment of policies and rules to be able to guide the responsible development and deployment of AI technologies. There should be set guidelines on the use of AI in an ethical way and on the privacy and security of data. For example, strict data protection standards and related safeguards to ensure that the privacy of the users is not violated are outlined in the General Data Protection Regulation of the European Union. Furthermore, the government needs to actively invest in education and training to make sure the workforce can obtain the necessary skills for the same economy.

Corporate Responsibility

An AI should be implemented in a way that is ethical and accountable by organizations. They need to formulate policies for their teams developing artificial intelligence that improve diversity and ensure inclusiveness to counter bias. Audits need to be conducted in artificial intelligence systems regularly to find and correct potential biases while ensuring standard ethics. Finally, organizations should establish a learning culture and ensure that employees are provided with opportunities to grow in develop new skills. According to IBM (2021), 'An ethical approach to AI and re-skilling a targeted workforce establishes the foundation for the best opportunities for business outperformance within the AI-driven economy.'

Conclusion

Hence, the argument about "AI vs. Human Workers: New to the page Learning Map and packed with the same impact as the main question “Competition or Co-Creation?” AI is, to some extent, a threat to some segments of employees, mainly, those whose responsibilities can be easily delegated to machines. But at the same time, it opens up immeasurable horizons for enhancing the output and creating new occupational niches. By exploiting synergistic opportunities of combining HI&A, it is possible to ready workplaces with distinctive benefits where each party has a unique contribution to offer. This future though possible depends on investments made in education and the right use and creation of AI technologies and ethic. It becomes very important to make sure that the current workforce has the necessary skills for the evolving nature of jobs. 

 Lastly, the use of AI as a primary workforce doesn’t necessarily have to be negative to the number of human workers needed. Thus, it can transform into a synergy when AI works closely with the employees utilizing the best qualities of each focusing on invasive innovations for increasing productivity rates. This approach may cause in the future shift the design of mankind and AI to create in combination the value, which will positively influence the increase of quality at work and sustainable economic development. Thus, by adopting this approach, society will be able to reap the benefits of adopting this new technology that is AI, and at the same time ensure that human labor remains relevant.

 

Description

This blog post opposes and explores the contestation of whether AI is a threat or an asset to human employees. It deals with concerns over human displacement by machines in workplaces while at the same time embracing aspects like efficiency in production and better decisions. Introducing this principle known as ‘collaborative intelligence’, where AI and humans intersect in a number of industries for improved performance and creativity. There is emphasis on the need to reinvent the labor force particularly through reskilling and upskilling as a result of advancing technology. Also, it insists on ethical imperatives such as employment fairness or bias reducing and job quality, and work-life balance with a view of promoting the right employment of Artificial Intelligence.

 

 

 

 

 

References

  1. World Economic Forum, "The Future of Jobs Report 2020," 2021.        https://www.weforum.org/reports/the-future-of-jobs-report-2020.
  2. PwC, "Sizing the prize: What’s the real value of AI for your business and how can you capitalise?," 2017.        https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf.
  3. Accenture, "Artificial Intelligence: The Future of Growth," 2022.         https://www.accenture.com/us-en/insight-artificial-intelligence-future-growth.
  4. MIT, "AI Bias and Discrimination Study," 2022. https://www.technologyreview.com/2022/03/15/1048069/ai-bias-discrimination-study/.
  5. Deloitte, "AI and risk management: Innovating with confidence," 2021. https://www2.deloitte.com/us/en/insights/focus/cognitive-technologies/artificial-intelligence-fraud-risk.html.
  6. IBM, "AI Ethics: Advancing a comprehensive ethical framework for AI," 2021. https://www.ibm.com/blogs/policy/ai-ethics/.
  7. European Commission, "Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016," 2016.  https://gdpr-info.eu/.
  8. S. M. McKinney, M. Sieniek, V. Godbole, J. Godwin, N. Antropova, H. Ashrafian, T. Back, M. Chesus, G. C. Corrado, A. Darzi, M. Etemadi, F. Garcia-Vicente, F. J. Gilbert, M. Halling-Brown, D. Hassabis, S. Jansen, A. Karthikesalingam, C. J. Kelly, D. King, and M. Suleyman, "International evaluation of an AI system for breast cancer screening," The Lancet Digital Health, vol. 2, no. 7, pp. E407-E416, Jul. 2022.        https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30002-3/fulltext.

 

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