{"id":2171,"date":"2023-12-08T05:00:00","date_gmt":"2023-12-08T05:00:00","guid":{"rendered":"https:\/\/euroly.org\/?p=2171"},"modified":"2024-01-19T18:26:22","modified_gmt":"2024-01-19T18:26:22","slug":"the-artificial-intelligence-boom","status":"publish","type":"post","link":"https:\/\/euroly.org\/the-artificial-intelligence-boom\/","title":{"rendered":"The Artificial Intelligence Boom: Assessing Economic Gains for Libya"},"content":{"rendered":"\n

The emergence of OpenAI’s ChatGPT marks a pivotal moment in the field of generative artificial intelligence (AI), sparking a wave of investor interest and prompting crucial discussions about its potential economic impact. Goldman Sachs’ extensive analysis<\/a> suggests that generative AI could significantly enhance labor productivity growth, potentially by about 1.5% annually over a decade in developed markets, leading to a global GDP increase of approximately 7%<\/strong>. <\/p>\n\n\n\n

This raises a pivotal question: As this technological wave reshapes economies, to what extent will nations with developing digital landscapes, such as Libya, adapt and benefit from the AI revolution?<\/p>\n\n\n\n

Table of Contents<\/h3>What is Generative Artificial Intelligence?<\/a><\/li>
Impact of Generative AI on the Labor Market<\/a><\/li>
Productivity Gains from Generative AI<\/a><\/li>
Contextualizing the Impact of Generative AI on Libya<\/a><\/li>
Significant, yet Highly Uncertain, Impacts of AI<\/a><\/li><\/ul><\/nav><\/div>\n\n\n\n
What is Generative Artificial Intelligence?<\/strong><\/h3>\n\n\n\n
At its core, artificial intelligence emulates human intellect within machines, leveraging sophisticated technologies like machine learning, natural language processing, and advanced neural networks. These technologies empower computers to learn from data, understand human languages, and execute intricate tasks, including image and pattern recognition.<\/p>\n\n\n\n
AI is predominantly categorized into three types:<\/strong><\/p>\n\n\n\n
\n
Artificial Narrow Intelligence (ANI)<\/em>: Often referred to as weak AI, ANI specializes in specific tasks such as voice recognition. It’s commonly used in applications like chatbots and language translators.<\/li>\n\n\n\n
Artificial General Intelligence (AGI)<\/em>: A theoretical form of AI, AGI aims to match human intelligence across a wide range of tasks. It’s a long-term goal in AI research, focusing on machines that can autonomously learn and adapt.<\/li>\n\n\n\n
Artificial Superintelligence (ASI)<\/em>: This extends AGI’s concept, envisioning machines surpassing human intelligence. ASI remains theoretical, with its potential and implications a subject of ongoing debate.<\/li>\n<\/ol>\n\n\n\n
As AI continues to evolve, one critical question arises: How will the advent of Generative AI impact the labor market?<\/p>\n\n\n\n
Impact of Generative AI on the Labor Market<\/strong><\/h3>\n\n\n\n
Goldman Sachs\u2019 extensive research, covering over 900 occupations in the US and 2000 in the Euro area, offers a detailed perspective on the possible disruptions in the labor market due to AI. This study is notable for its intricate analysis of the vulnerability of various tasks within each occupation to automation by AI, with a focus on both the complexity and importance of these tasks.<\/p>\n\n\n\n
Key findings include:<\/strong><\/p>\n\n\n\n
\n
About two-thirds of US occupations show some degree of exposure to AI automation.<\/em><\/li>\n\n\n\n
A substantial part of the workload in these occupations (25-50%) could potentially be automated.<\/em><\/li>\n\n\n\n
High automation potential is noted in administrative (46%) and legal (44%) professions.<\/em><\/li>\n\n\n\n
Lower automation potential is seen in physically-intensive sectors like construction (6%) and maintenance (4%).<\/em><\/li>\n<\/ul>\n\n\n\n
The findings are similar in the Euro area<\/strong>, where approximately 24% of work tasks could be automated by AI<\/strong>. These occupation-level estimates are adjusted according to the employment share of each occupation, offering a detailed view of potential automation across various industries.<\/p>\n\n\n\n
$\"Share$ <\/figure>\n\n\n\n
When these findings are extrapolated globally, accounting for country-specific industry-employment profiles, it\u2019s estimated that generative AI could automate about 18% of work tasks worldwide<\/strong>. This impact is expected to be more significant in developed markets compared to emerging markets.<\/p>\n\n\n\n

Productivity Gains from Generative AI<\/strong><\/h3>\n\n\n\n
The integration of AI into the workforce is poised to significantly enhance productivity, primarily through two channels:<\/strong><\/p>\n\n\n\n
\n
Reallocation of Workforce Capacity:<\/em> Workers in occupations partially susceptible to AI automation are likely to shift towards more productive tasks. This trend is evident in firms that have adopted AI, with initial findings indicating a 2-3 percentage point increase in annual labor productivity growth. This reflects AI’s potential to free up human resources for higher-value tasks.<\/li>\n\n\n\n
Creation of New Occupations and Reemployment: <\/em>History shows that technological disruptions, while displacing some jobs, also lead to new occupations. Similar to the digital revolution, which created roles like web designers and digital marketers, AI is expected to boost labor demand in various service industries and lead to new job categories.<\/li>\n<\/ul>\n\n\n\n
Goldman Sachs’ analysis suggests that the widespread adoption of generative AI could potentially double the current rate of US productivity growth<\/strong>. This impact mirrors historical increases seen with transformative technologies like the electric motor and personal computer.<\/p>\n\n\n\n
$\"Contributions$ <\/figure>\n\n\n\n
Key aspects include:<\/strong><\/p>\n\n\n\n
\n
Productivity Boost for Non-Displaced Workers: <\/em>Workers in AI-exposed roles are likely to see a productivity increase, potentially echoing the 2-3 percentage point rise observed in early studies.<\/li>\n\n\n\n
Economic Impact of Worker Displacement: <\/em>While AI will lead to job displacement, many displaced workers are expected to find new opportunities in emerging sectors. Historically, technological shifts have created more jobs than they displaced, indicating a dynamic job market evolution.<\/li>\n\n\n\n
Long-Term Employment Trends:<\/em> Over time, technological changes have consistently led to the creation of new job types, with many of today\u2019s roles not existing several decades ago.<\/li>\n<\/ul>\n\n\n\n
Combining these factors, Goldman Sachs estimates that full-scale AI adoption could increase overall labor productivity growth in the US by about 1.5 percentage points annually<\/strong>, effectively doubling the recent pace of productivity growth.<\/p>\n\n\n\n
The productivity growth is not confined to the US; similar increases are expected in other developed markets. <\/p>\n\n\n\n
$\"Effect$ <\/figure>\n\n\n\n
The study anticipates a comparable rise in productivity across these economies, with global adoption of AI potentially enhancing annual productivity growth by over 1 percentage point. However, this impact might be delayed in emerging economies due to varying industry compositions and adoption rates.<\/p>\n\n\n\n
Contextualizing the Impact of Generative AI on Libya<\/h3>\n\n\n\n
Libya, with its unique economic landscape<\/a>, faces distinct challenges and opportunities in harnessing the potential of generative AI. A more in-depth economic calculation can help understand the possible impact on Libya’s GDP and labor market.<\/p>\n\n\n\n
GDP Growth Estimation:<\/strong><\/p>\n\n\n\n
\n
Global Context vs. Local Application: <\/em>While the global estimate of a 7% GDP increase over a decade due to AI is significant, applying this directly to Libya requires adjustments. Given Libya’s emerging market status and its nascent digital infrastructure, a more realistic expectation might be a smaller increment in GDP growth.<\/li>\n\n\n\n
Sector-Specific Considerations: <\/em>Key Libyan sectors, like oil and gas, are less likely to be immediately impacted by AI automation compared to more digitalized sectors. Therefore, the direct contribution of AI to Libya’s GDP growth in the short term might be relatively modest.<\/li>\n\n\n\n
Projected GDP Increase: <\/em>Considering these factors, Libya\u2019s GDP growth due to AI adoption might be more conservative, possibly in the range of 2-4% over the next decade, assuming gradual digitalization and AI integration.<\/li>\n<\/ul>\n\n\n\n
Labor Market Dynamics:<\/strong><\/p>\n\n\n\n
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Impact on Employment: <\/em>The adoption of AI in Libya might not lead to significant immediate changes in the labor market, especially in sectors dominated by physical labor. This slow transition might result in a gradual impact on productivity and, consequently, on GDP.<\/li>\n\n\n\n
Digital Infrastructure Development: <\/em>To harness the full potential of AI, Libya would need to focus on developing its digital infrastructure and upskilling its workforce, which would be a long-term endeavor.<\/li>\n<\/ul>\n\n\n\n
\n<\/iframe>\n<\/div><figcaption class=\"wp-element-caption\">Libyan Spider, a prominent technology developer and provider in Libya.<\/figcaption><\/figure>\n\n\n\nIn conclusion, the impact of generative AI on Libya\u2019s economy will likely be more gradual and modest compared to global averages<\/strong>, primarily due to its current stage of digitalization and economic structure. Strategic investments in technology, policy-making, and workforce development will be key to leveraging AI for economic growth. The long-term outlook, however, remains promising<\/strong>, with AI offering avenues for economic diversification and incremental productivity gains.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"significant-yet-highly-uncertain-impacts-of-ai\">Significant, yet Highly Uncertain, Impacts of AI<\/h3>\n\n\n\nThe potential boost to productivity growth from the widespread adoption of generative AI, while substantial, is accompanied by significant uncertainty. This uncertainty is primarily rooted in factors such as the evolving capabilities of AI, the extent of job automation, and the speed of its adoption across industries. As a result, the projected increase in annual productivity growth in the United States could vary extensively, ranging from 0.3 to 3.0 percentage points. However, the boost is generally expected to be economically significant across most scenarios. In emerging markets like Libya, where digital infrastructure and AI adoption are still developing, these impacts might manifest differently and over a longer period.<\/p>\n\n\n\nThe extent of the productivity increase is directly tied to the capabilities of AI and the rate of its adoption in various sectors. For instance, less advanced AI capable of performing simpler tasks (like skimming an article for key points) will have a lesser impact compared to AI that can undertake more complex analyses (such as evaluating the costs of medical care services across hospitals).<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"930\" src=\"https:\/\/euroly.org\/wp-content\/uploads\/2023\/12\/Martyrs-Square-Tripoli-Libya-1-1024x930.jpg\" alt=\"Martyrs' Square, Tripoli, Libya\" class=\"wp-image-2180\" srcset=\"https:\/\/euroly.org\/wp-content\/uploads\/2023\/12\/Martyrs-Square-Tripoli-Libya-1-1024x930.jpg 1024w, https:\/\/euroly.org\/wp-content\/uploads\/2023\/12\/Martyrs-Square-Tripoli-Libya-1-300x272.jpg 300w, https:\/\/euroly.org\/wp-content\/uploads\/2023\/12\/Martyrs-Square-Tripoli-Libya-1-768x697.jpg 768w, https:\/\/euroly.org\/wp-content\/uploads\/2023\/12\/Martyrs-Square-Tripoli-Libya-1-1536x1394.jpg 1536w, https:\/\/euroly.org\/wp-content\/uploads\/2023\/12\/Martyrs-Square-Tripoli-Libya-1.jpg 2048w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Martyrs’ Square, Tripoli, Libya.<\/figcaption><\/figure>\n\n\n\nPredicting the timing of AI’s macroeconomic impact is also challenging<\/strong>, as evidenced by the historical precedent set by technological breakthroughs like the electric motor and personal computer. These technologies saw significant productivity gains materialize roughly 20 years after their introduction, following widespread adoption. Current global interest in generative AI could potentially accelerate its adoption, but the actual rate of integration into business operations remains modest<\/strong>. As of 2019, AI adoption rates among US firms stood at only 3.2%, and despite the growing corporate interest in AI, only about 20% of CEOs anticipate a reduction in labor needs due to AI in the next 1-3 years. Factors such as data privacy concerns continue to pose barriers to the rapid integration of AI into everyday business workflows<\/strong>.<\/p>\n\n\n\nGiven these considerations, it’s likely that the tangible effects of generative AI on aggregate productivity, particularly in countries like Libya, will not be immediately visible<\/strong>. However, the potential for AI to automate a wide range of work tasks, combined with projections of substantial productivity increases, underscores the profound economic potential of AI. If AI lives up to its promise, it could lead to a considerable increase in global GDP \u2013 potentially up to 7%, or almost $7 trillion, over a 10-year period<\/strong>. This positions generative AI as a significant upside risk for global economic growth in the medium to long term.<\/p>\n","protected":false},"excerpt":{"rendered":"The emergence of OpenAI’s ChatGPT marks a pivotal moment in the field of generative artificial intelligence (AI), sparking a wave of investor interest and prompting crucial discussions about its potential economic impact. Goldman Sachs’ extensive analysis suggests that generative AI could significantly enhance labor productivity growth, potentially by about 1.5% annually over a decade in […]<\/p>\n","protected":false},"author":1,"featured_media":2182,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2171","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"acf":[],"_links":{"self":[{"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/posts\/2171","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/comments?post=2171"}],"version-history":[{"count":0,"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/posts\/2171\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/media\/2182"}],"wp:attachment":[{"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/media?parent=2171"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/categories?post=2171"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/euroly.org\/wp-json\/wp\/v2\/tags?post=2171"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}