The Economic Impact of Artificial Intelligence: Job Displacement and Creation

From the recent release of a product that ‘replaces software engineers’ to Klarna AI. Today, I discuss the economic impact of AI, and how job displacement is happening quicker than we thought.

Artificial Intelligence (AI) is a transformative technology that is rapidly reshaping the global economy, revolutionising industries, and fundamentally altering the nature of work. As AI continues to advance at an unprecedented pace, it has become increasingly crucial to understand its economic implications, particularly in terms of job displacement and creation.

This blog post delves into the multifaceted impact of AI on employment, exploring both the challenges and opportunities it presents, and discusses the strategies and policies needed to ensure a smooth transition into an AI-driven future.

Caveat ~ As a technophile, I believe artificial intelligence will boost our human potential. It can help eliminate mediocrity and position us for excellence. As we shift away from ‘bullshit jobs’, we’re entering a phase of technological freedom where we’re no longer constrained by non-definitive work and can start creating whatever we can imagine, without the need for initial capital. However, I’m cognisant of the disruptive workforce impacts AI may have in the short-term, which is why I want to explore the paradox between AI’s utopian vision versus its potential dystopian realities. Let’s begin with ‘The Displacement Effect’…

The Displacement Effect:

AI-powered technologies such as machine learning, computer vision, and natural language processing are already being deployed to automate routine and repetitive tasks across various sectors, from manufacturing and customer service to data entry and analysis. This automation capability raises valid workforce displacement worries.

For instance, Klarna’s new ‘Klarna AI’ customer service tool handled two-thirds of their customer service chats in just the first month, performing equivalently to 700 full-time agents while matching human satisfaction scores and even improving resolution rates. An innovative achievement, undoubtedly, but one that also makes displaced human roles quite apparent.

As AI automation advances, we must confront this duality — the tantalising efficiency gains contrasted with potential job losses, particularly for more repetitive roles. My perspective is that embracing AI’s positive capabilities while proactively reskilling and supporting displaced workers will be crucial for a balanced, equitable transition.

A comprehensive study I read by the Brookings Institution estimates that approximately 36 million American jobs, or 25% of the total workforce, face high exposure to automation, with lower-wage occupations involving routine cognitive and manual tasks being the most vulnerable.

The displacement effect, however, is not uniform across industries or skill levels. While low-skill, repetitive jobs are more easily automated, high-skill roles are also being impacted. For example, AI-powered tools are assisting with tasks such as medical diagnosis, software engineering, legal research, and financial analysis, potentially reducing the need for human professionals in these fields. Source

A study by McKinsey Global Institute (Manyika et al., 2017) suggests that by 2030, between 400 million and 800 million individuals worldwide could be displaced by automation and need to find new jobs.

The study also notes that up to 375 million workers, or 14% of the global workforce, may need to switch occupational categories as a result of AI-driven disruption.

The Creation Effect:

Despite valid concerns about job displacement, it’s crucial to note that AI is creating new jobs and opportunities. The adoption of AI technologies by companies necessitates professionals who can develop, implement, and maintain these systems. The demand for AI specialists, data scientists, and machine learning engineers is surging, with job postings in these fields increasing by 74% annually.

This growth is encouraging as these skills are becoming more transferable due to the advancement of AI-powered learning tools. When I worked at DataCamp, a leading e-learning provider, I recognised the importance of making technological skills accessible at a low cost and available to learn anywhere. So, seeing the increased demand for remote technical roles gives me a positive outlook on the future.

Furthermore, AI is facilitating the creation of new products and services, leading to job growth in emerging sectors. For example, the emergence of autonomous vehicles is predicted to create jobs in fleet management, remote monitoring, and service roles. This is particularly significant in areas like Africa where infrastructure development is essential for GDP growth.

A report by PwC estimates that AI could contribute up to $15.7 trillion to the global economy by 2030, with approximately $6.6 trillion coming from increased productivity and $9.1 trillion from consumption-side effects.

This economic growth is expected to generate significant job opportunities across various sectors, including healthcare, education, and environmental services.

Preparing for the Future:

To minimise the potential negative impacts of AI on employment, policymakers, businesses, and individuals must focus on developing the skills and knowledge needed to thrive in an AI-driven economy. This includes investing in STEM education, promoting lifelong learning, and creating targeted training programmes for workers in industries most affected by automation.

Instead of using regulatory powers to ban these technologies from existing we need to actively apply pressure for them to integrate workers to learn how to use it. As reduction in laborious tasks equates to active productivity.

One commission that I see advocating for the integration is the European Commission’s Digital Education Action Plan (2021–2027), which emphasises the importance of developing digital skills and competencies across all levels of education and training. The plan aims to support the development of a high-performing digital education ecosystem and enhance digital skills and competencies for the digital transformation.

Another way governments and businesses can also implement policies and initiatives to support workers during the transition, will be by providing income support, retraining programmes, and job placement services. Denmark’s “flexicurity” model, for example, combines flexible labour market policies with strong social safety nets and active labour market programmes, helping workers adapt to changing job requirements and reducing the impact of job displacement.

Fostering collaboration between industry, academia, and government can help ensure that the development and deployment of AI technologies are aligned with societal needs and values.

The UK’s AI Sector Deal, part of the government’s Industrial Strategy, aims to boost the UK’s AI industry by investing in research, skills, and infrastructure, while also addressing the ethical, social, and economic implications of AI.

Case Studies:

Here are some recent case studies exemplified:

1. Healthcare: AI is transforming the healthcare industry, enabling faster and more accurate diagnosis, personalised treatment plans, and improved patient outcomes. A study by Accenture estimates that AI applications in healthcare could save up to $150 billion annually in the US by 2026. In addition to this, acquisitions of AI startups are rapidly increasing in the healthcare industry.

2. Manufacturing: The manufacturing sector has been an early adopter of AI and automation technologies, leading to significant productivity gains and cost savings. However, this has also resulted in job losses, particularly for low-skilled workers. A study by the International Federation of Robotics found that the operational stock of industrial robots worldwide increased by 15% to 2.4 million units in 2017, with the automotive and electronics industries being the largest users.

3. Finance: AI is revolutionising the financial services industry, from fraud detection and risk assessment to personalised investment advice and algorithmic trading. A report by McKinsey & Company estimates that AI could potentially deliver up to $1 trillion of additional value annually in the global banking industry. However, the adoption of AI in finance also raises concerns about job losses, particularly in areas such as customer service (as mentioned above) and data analysis.

The Path Forward: As we navigate the complex landscape of AI and its impact on employment, it is crucial to adopt a proactive and multifaceted approach. This involves:

1. Investing in education and skills development: Governments, businesses, and educational institutions must collaborate to develop curricula and training programmes that equip individuals with the skills needed to thrive in an AI-driven economy. This includes a focus on STEM subjects, digital literacy, and soft skills such as creativity, critical thinking, and adaptability.
2. Promoting lifelong learning: In a rapidly evolving technological landscape, continuous learning and upskilling are essential. Employers should provide opportunities for on-the-job training and professional development, while governments can support lifelong learning initiatives through funding and incentives.
3. Implementing supportive policies: Policymakers must develop and implement measures to support workers during the transition to an AI-driven economy. This can include income support schemes, retraining programmes, and job placement services. Additionally, policies that encourage the development and adoption of AI technologies in a responsible and inclusive manner should be pursued.
4. Fostering collaboration and dialogue: Open and ongoing dialogue between stakeholders, including governments, businesses, labour unions, and civil society, is essential to address the challenges and opportunities presented by AI. Collaboration can help ensure that the benefits of AI are distributed equitably and that potential negative impacts are mitigated.
5. Emphasising ethics and responsible AI development: As AI becomes more prevalent, it is crucial to ensure that its development and deployment align with ethical principles and societal values. This involves addressing issues such as bias, transparency, accountability, and privacy. By prioritising responsible AI development, we can work towards a future in which the benefits of AI are maximised while potential harms are minimised. The ultimate goal.

Wrapping up:

The economic impact of AI on employment is a complex and multifaceted issue, with both job displacement and creation effects. While the net impact remains uncertain, it is clear that AI will significantly transform the nature of work and the skills required to succeed in the future job market.

To harness the potential of AI while mitigating its negative impacts, we must adopt a proactive and collaborative approach. By investing in education and skills development, implementing supportive policies, fostering dialogue, and emphasising responsible AI development, we can work towards a future in which technological progress and human well-being go hand in hand.

As a ethnic minority myself, this step-change is integral in creating an even-playing field amongst workers as we democratise the ability to learn something new (and useful) through AI powered resources and power tools.

As we embrace the transformative power of AI, it is essential to remember that our ultimate goal is not merely to maximise economic growth but to ensure that the benefits of this technology are distributed equitably and that no one is left behind. By taking bold and decisive action today, we can shape a future in which AI serves as a catalyst for positive change, empowering individuals, communities, and societies to reach their full potential.

Thanks for reading.

References:

1. Accenture. (2018). Artificial Intelligence: Healthcare’s New Nervous System. https://www.accenture.com/_acnmedia/PDF-49/Accenture-Health-Artificial-Intelligence.pdf
2. Andersen, T. M. (2017). The Danish labor market, 2000–2016. IZA World of Labor. https://wol.iza.org/articles/the-danish-labor-market
3. European Commission. (2021). Digital Education Action Plan (2021–2027). https://ec.europa.eu/education/education-in-the-eu/digital-education-action-plan_en
4. International Federation of Robotics. (2018). World Robotics Report 2018. https://ifr.org/downloads/press2018/Executive_Summary_WR_2018_Industrial_Robots.pdf
5. LinkedIn. (2020). 2020 Emerging Jobs Report. https://business.linkedin.com/talent-solutions/emerging-jobs-report
6. Manyika, J., Lund, S., Chui, M., Bughin, J., Woetzel, J., Batra, P., Ko, R., & Sanghvi, S. (2017). Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages. McKinsey Global Institute. https://www.mckinsey.com/featured-insights/future-of-work/jobs-lost-jobs-gained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages
7. McKinsey & Company. (2020). AI-bank of the future: Can banks meet the AI challenge? https://www.mckinsey.com/industries/financial-services/our-insights/ai-bank-of-the-future-can-banks-meet-the-ai-challenge
8. Muro, M., Maxim, R., & Whiton, J. (2019). Automation and Artificial Intelligence: How machines are affecting people and places. Brookings Institution. https://www.brookings.edu/research/automation-and-artificial-intelligence-how-machines-affect-people-and-places/
9. Nedelkoska, L., & Quintini, G. (2018). Automation, skills use and training. OECD Social, Employment and Migration Working Papers, №202. https://doi.org/10.1787/2e2f4eea-en
10. PwC. (2018). The macroeconomic impact of artificial intelligence. https://www.pwc.co.uk/economic-services/assets/macroeconomic-impact-of-ai-technical-report-feb-18.pdf
11. UK Government. (2019). AI Sector Deal. https://www.gov.uk/government/publications/artificial-intelligence-sector-deal/ai-sector-deal
12. World Economic Forum. (2020). The Future of Jobs Report 2020. https://www.weforum.org/reports/the-future-of-jobs-report-2020