Artificial Intelligence (AI) has been a game-changer in various fields, including the workforce and mathematics. This scholarly study will explore the origins of AI’s first generation, focusing on key contributors, workforce impact, and how AI technology can enhance mathematics.


Keywords: artificial intelligence, workforce, mathematics, geometry




The Emergence of AI in Society

The roots of AI can be traced back to the mid-20th century when scholars and visionaries began to earnestly explore the potential of designing machines capable of exhibiting intelligent behavior. One of the defining moments in the birth of AI as a distinct field of study was the Dartmouth Conference, held in 1956 at Dartmouth College (McCarthy et al., 2006). This historic gathering, organized by computer scientists John McCarthy, Marvin Minsky, Claude Shannon, and others, brought together some of the brightest minds of the time to discuss the possibilities of &artificial intelligence,& a term coined by McCarthy specifically for the occasion.

During the Dartmouth Conference, participants engaged in lively discussions and presented their initial ideas and experiments, laying the groundwork for AI. This included proposals for developing programs that could play chess, prove mathematical theorems, and engage in open-ended problem-solving (Crevier, 1993). The conference marked the official beginning of AI as a recognized academic discipline, inspiring a surge of research and enthusiasm to shape the field in the coming decades.


Education now has so many resources and tools because of AI. Some apps, such as Photo math, break down mathematical education to the student& level of understanding. According to research, AI enables the creation of robots that improve the student& learning=experience. The most basic unit of education is early childhood education. The application of robots works with teachers to teach children routine tasks, including spelling and pronunciation, and adjust to the student& abilities (Chen et al., 2020). These AI bots are helping with the advancement of education because the AI bot can understand human cognitive ability. This helps raise test scores, which helps with overall school and district rankings. For example, if a district has a history of low-test scores and has recently implemented AI, test scores have increased. This shows how AI has changed education because students adapt more to the style.


Artificial Intelligence has changed the influence of technology on the world as we once knew it. AI uses different sciences, such as mathematics, statistics, and computer science, to imitate the cognitive abilities of humans. Since the advancement of social media with sites such as TikTok, Instagram, and Snapchat, AI has shown its capabilities from filters to altering facial features, such as removing beauty marks, changing eye color, etc. There is even a feature that allows users to chat with an AI robot on Snapchat. The AI robot can answer many questions, such as historical facts, weather, astrology, etc. AI has truly changed human interactions, but is
this good for the world? The purpose of this research is to see how AI can be used for good. Is AI helping with the advancement of science? Or is AI doing more harm than good?



AI and its Impact on the Workforce


AI is revolutionizing the future of work. According to the World Economic Forum (2023), generative AI will eventually automate 300 million of today& jobs. However, the BBC (2023) reports that AI is also expected to be a net job creator in five years. 49% of companies expect adopting AI to create jobs, which is significantly higher than the 23% of respondents who expect it to displace jobs.

AI is already displacing workers through automation, augmenting human performance at work, and creating new job categories (Brookings, 2023). For example, roles linked to AI, such as data scientists, big data specialists, and business intelligence analysts, are expected to increase by 30 to 35% (Brookings, 2023). Employment gains are expected to be particularly strong in the automotive and aerospace industry, where 73% of companies anticipate job growth (BBC, 2023). However, it should be noted that while AI can automate certain tasks, it cannot replace the human touch in many jobs.

AI is not solely focused on job displacement or creation; it also aims to augment human performance at work, increasing productivity and efficiency for workers and firms (BBC, 2023). For instance, AI can assist workers in writing cover letters and resumes, generating ideas, and responding to emails. Interestingly, educated white-collar workers earning up to $80,000 a year
are the most likely affected by workforce automation (Goldman Sachs, 2023). Jobs in agriculture, mining, and manufacturing are the least exposed to generative AI, while jobs in the information processing industries, such as IT, are the most exposed (Goldman Sachs, 2023). The McKinsey Global Institute (2021) suggests that by 2030, automation could replace activities that
account for up to 30% of hours currently worked across the U.S. economy (ChatGPT, OpenAI, 2024). This trend is accelerated by generative AI, which is expected to enhance how STEM, creative, business, and legal professionals work rather than eliminate many jobs outright (ChatGPT, OpenAI, 2024). Furthermore, AI is expected to have a significant impact on the economy. McKinsey Global Institute (2021) predicts that by 2030, AI could contribute around $13 trillion to global economic activity, resulting in a cumulative GDP that is approximately 16% higher than the present. This would translate to an additional annual GDP growth of 1.2%
(McKinsey Global Institute, 2021). This impact will primarily stem from labor substitution through automation and increased innovation in products and services.

However, it is important to recognize that AI can also worsen inequality and discriminate against workers (Nexford University, 2024). Workers in the oil and gas industry may be especially vulnerable, as 45% of companies anticipate losses in this sector (BBC, 2023).




AI and Mathematics


AI has contributed significantly to solving important mathematical imaging problems, such as denoising, edge detection, and inpainting. AI-driven systems already help mathematicians analyze the behavior of partial differential equations, which can model physical processes from ocean currents to nuclear explosions (Clavin, 2022). Machine learning, a subfield of AI, is being embraced by mathematicians. It can help them brainstorm and generate new ideas. For instance, it can test for counterarguments to a thesis, write an abstract for research, or generate a tweet to promote a paper (MIT, 2024).


AI has also been used to solve complex optimization problems that were previously unsolvable (World Economic Forum, 2023). One tough problem that machine learning may unravel is the Riemann hypothesis (MIT, 2024). AI applications in education are becoming more popular. AI is a leap across creative and innovative thinking in various fields, including mathematics education (Mohamed, 2022). The use of AI can enhance students’ mathematical skills and cognitive skills in learning (BBC, 2023). A study revealed that AI had a small effect on elementary students’ mathematics achievement (Brookings, 2023).


Mathematics has been connected to AI and contributes ongoing futuristic needs for AI. AI can provide a decisive edge and open up new avenues for research in the mathematical fields (Fink, 2024). Google DeepMind predicted 2.2 million new crystal structures are part of continuous research that grows exponentially to enhance AI projections of conjectures. The more imagination and intuition of mathematicians are required to make sense of AI outputs (Fink, 2024).


Geometry is a branch of mathematics concerned with properties of space such as the distance, shape, size, and relative position of figures. This definition is written over and over in math textbooks, online as well as dictionaries all over the world. Mathematicians have been using proofs in geometry and analytic geometry courses in high schools and colleges. Many research students and their research mentors have communicated that geometry is the foundation of mathematics. Stump (2021) stated that researchers continue testing relationships on more complicated examples (from icosahedra to huge, randomly shaped polyhedral) and discards any
properties that aren’t relevant. These examples are merely geometric figures diagnosed over and over as research continues to prevail. AI can step in and assist with this research as we advance in the sciences throughout the curriculum and industry so we can make examples relevant to learners of all levels.



AI & its ability to Solve Math Problems


Artificial Intelligence (AI) has been progressively making substantial advancements in numerous domains, with mathematics being no exception. The utilization of AI in deciphering mathematical formulas has piqued the interest of a multitude of researchers and educators. The overviews will explore the ways in which AI can aid in resolving mathematical formulas, drawing upon a variety of sources.

Hao (2020), in an article published in the MIT Technology Review, reported that AI has been employed to solve partial differential equations (PDEs), which are notoriously challenging to resolve. PDEs are integral to numerous fields, including physics and engineering, and their resolution can often be a complex task. However, the employment of AI has rendered this process considerably more efficient. The AI could solve these equations with greater accuracy and speed than traditional methods. Intriguingly, the AI was also capable of solving entire families of PDEs without necessitating retraining, thereby demonstrating its adaptability and learning capabilities.

Microsoft Copilot (2023) also offers insights into how AI-powered mathematical problem solvers, such as Copilot, can assist with calculating mathematical equations. These AI tools are user-friendly and aid users in understanding and completing various mathematical calculations independently. They can handle a broad range of mathematical problems, from simple arithmetic to complex calculus problems. The employment of AI in this context not only accelerates the calculation process but also enhances the learning experience for users.

DeepMind, a leading AI research laboratory, has also made significant contributions to this field. As reported by Nature (2022), DeepMind’s AI was capable of inventing faster algorithms to solve challenging mathematical puzzles. The AI was able to discover shortcuts in fundamental mathematical calculations by transforming the problem into a game and leveraging machine-
learning techniques. This approach not only resulted in faster solutions but also introduced new ways of conceptualizing mathematical problems.

Tech Pilot (2023) discusses how AI is revolutionizing mathematics education and problem- solving. By automating calculations and enhancing visualization, AI tools are rendering mathematics more accessible and engaging for students. These tools can handle a wide range of mathematical problems, from simple arithmetic to complex calculus problems. The employment of AI in this context not only accelerates the calculation process but also enhances the learning experience for users.

Robots Science (2023) mentions how AI tools can rapidly solve computations like algebra, calculus, trigonometry, and more. These tools enable students to focus on higher-level concepts, thereby enhancing their understanding and appreciation of mathematics. The employment of AI in this context not only accelerates the calculation process but also enhances the learning experience for users.

AI has demonstrated considerable potential in resolving mathematical formulas. From solving complex PDEs to assisting students with their mathematics homework, AI is revolutionizing the way we approach mathematics. However, it’s important to note that the effectiveness of AI can vary based on the complexity of the formula and the specific AI tool employed. Therefore, it’s crucial to consider the context and specific needs when evaluating the use of AI for mathematical problem-solving. As AI continues to evolve, we can anticipate witnessing even more innovative applications in the field of mathematics.