How does the adoption of AI Technology affect the rate of development across nations

The Renaissance marked the inception of a new side of human endeavor. Specialization into fields which led to the progression of science, law, and art that worked towards defining the current and leading thoughts in these fields today. Conversely, a divergence was created between lower and upper classes in regards to the level of education they received, with corruption from higher classes being used to protect their interests while the poor were left to suffer leading to significant political turmoil (Murphy, n.d). In retrospect, the romanticization of the Renaissance can be observed and parallel to the rise of Artificial Intelligence (AI) technologies in the information age. Investor sentiment glamorizes the rise of AI technologies as in the case of the meteoric rise in stock price of NVIDIA, a company which builds software and hardware architecture which are used to process data for AI. For all this glamor surrounding AI, a significant polarity is being created between nations with the proper infrastructure to build and integrate AI technologies, and nations which lack these capabilities. The adoption of AI technologies will affect differences in rate of development by introducing new inequalities in education, science, and the global economy.

In the education sector, AI has a wide range of integrations. A popular form of applications are adaptive learning platforms which optimize learning for students. These platforms function as a response to the norm of standardized education by offering students personalized learning (Hamilton, 2023). A form of AI known as a Language Learning Model (LLM) supplements learning in the classroom by offering students the ability to interact with a model which can answer virtually any question a student needs the answer to. Adaptive learning platforms and LLM’s intrinsic values are augmented through their ability to lighten the workload of teachers, allowing for more valuable time spent with students helping to explain concepts and advance their learning. These kinds of benefits can be explored in schools and learning institutions in nations with the proper infrastructure to support AI technologies. Students from nations which lack these proficiencies suffer from a debilitating and growing competition with students who have had sufficient exposure to these concepts and forms of learning. Not only does this leave a wound in the youth of a nation locking them into a steep learning curve regarding their ability to use these technologies in the future. These absences usher the pathway to an overall deficiency for the rate of development of a nation.

As it stands in the medical space for nations like the United States there is active integration of AI into machines and tools which is taking our current medical understanding to ambitious heights through multiple methods. One method is feeding medical data into AI models which assesses information from the data and supplies intelligent information regarding disease diagnoses which plays a large part in early prevention for cancerous growths and crippling afflictions. The data being accumulated from disease prevention models can be used and taken one step further towards fully personalized treatments for people, a significant advancement in the field of human health (Tomberlin, 2023). Along with the patient facing side of these technologies, there is the institutional side to appreciate in regards to how AI software helps reduce needless paper waste by streamlining information through computers. Globally, trillions of dollars go into the healthcare industry and it remains important to consider inequities created in different nations through the advent of AI. Medicare professionals in nations not suited for AI development will not have access to advanced tools to organize their work and will get abandoned in the past. Tying into the education sector, less AI capable nations effectively hamper the youth of the best opportunities by creating a steep gradient in skill level by undervaluing people from these nations in comparison to AI capable nations, where the youth is immersed in AI technologies. Nations with less developed AI technologies will suffer from a populace with comparatively less access to advanced healthcare tools compared to that of a country that has well established AI integrations, this overall trend can cause a drop in economic sectors and create a polarity in lifespan between the general populace of two nations with contrasting AI capabilities. The significant AI advancements like disease prevention and personalized medicine therapies will act as a boon to nations that have resources to support AI research and integration and contrarily, a depreciator to nations which cannot.

As the information age has pushed through since the mid 20th century, data has become one of the if not the biggest buzzword of our times. Data is the make or break component of any successful application of AI. With data playing such a fundamental role in finance and economics, machine learning integration allows itself to operate very intuitively in this sector. Bayesian analysis is considered the earliest application of AI in the stock market using statistics. Data plays an integral part in the workings of the financial sector, with quant analysts being valued in high finance institutions like hedge funds. Institutions like banks, funds, and firms can see great returns due to their strengths for financial modeling and AI algorithms. The portions of these returns that can be attributed to AI technology integration have important differences in their decision making process considering most AI technology does not involve emotion based decision making, but rather, pure data driven analysis. These models are built for assessing risk and making educated decisions by constantly learning from their performance (Hossain, 2024). Financial institutions in countries with underdeveloped AI technologies stand at a junction where they lack the proper infrastructure for AI analysis in their trading and financial decision making and will fall behind due to the inequality created by the superior attributes of AI technologies in more developed nations. This disparity created can be observed in the economy through the financial service industry that makes up twenty five percent of the world's economy that has also come to adapt significantly more AI technologies (Ross, 2021). 

Like the Renaissance, the AI boom may be romanticized in the future as its integrations become more widespread in fields like education, medicine, and high finance. While simultaneously parallelling the Renaissance due to the divisions and inequalities created by AI as a detriment to nations which can’t support these integrations in fields crucial to the well being of people in these nations. To ensure that this future glamor can be received in good faith, there should be early detection of inequalities that are created in nations with contrasting AI capabilities and an egalitarian stance should be established on accessibility and potential to use artificial intelligence. The conclusion becomes increasingly more clear that with the great boons that come with AI integration in a nation's operations, a great disparity is created between nations with and without the infrastructure to support it.

Works Cited

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Hossain, S. (2024, February 18). The Integration of AI in Finance - Md Shahriare Hossain Arafat - Medium. Medium; Medium. https://medium.com/@Shahriare/the-integration-of-ai-in-finance-652b514fd2b1

Lu, X., Zeng, Q., Zhong, J., & Zhu, B. (2024). International stock market volatility: A global tail risk sight. Journal of International Financial Markets, Institutions & Money, 91, 101904–101904. https://doi.org/10.1016/j.intfin.2023.101904

Murphy, H. (n.d.). Pro and Con of the Renaissance Era. Adobe Spark. https://express.adobe.com/page/qwghjmobVUO7W/

Ross, S. (2021, September 30). What percentage of the global economy is comprised of the financial services sector? Investopedia. https://www.investopedia.com/ask/answers/030515/what-percentage-global-economy-comprised-financial-services-sector.asp

Swaine-Simon, S. (2018, March 8). The History of AI in Finance. Medium. https://medium.com/district3/the-history-of-ai-in-finance-7a03fcb4a498

Tomberlin, C. (2023, December 21). Revolutionizing Healthcare: How is AI being Used in the Healthcare Industry? Los Angeles Pacific University. https://www.lapu.edu/ai-health-care-industry/