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AI Funding in Education

Big Picture

Artificial Intelligence (AI) is becoming more commonplace and user-friendly. However, many consumers are concerned about the technology, especially in education. Since AI is trained by programmers, it can replicate the biases and perspectives of the programmers themselves. AI also poses privacy and plagiarism issues, two major concerns for educators and general consumers alike. Since AI is still an emerging technology, the best method to ease those concerns is to define a framework for AI research and a criterion for universities interested in receiving funding for AI research from the U.S. National Science Foundation.

Operative Definitions

  1. Artificial Intelligence: Technology that models elements of human intelligence to process data.

  2. Algorithm: A step-by-step process to provide a solution in light of a prompt.

  3. Machine Learning: An AI training process. Data is given to the AI to increase its depth of knowledge to recognize patterns.

  4. Natural Language Processing: The branch of AI that processes and generates speech and text Chatbots. This allows advanced communication with mass market availability. 

  5. Computer Vision: A branch of AI that can scan and interpret images and video. 

  6. Deep Learning: The AI software that classifies information in order to make decisions.

  7. Generative AI: The use of AI to generate creative works based on prompts. This may include writing, photos, art, videos, sounds, etc. The AI is trained to avoid generating pre-existing material.

  8. Neural Networks: A branch of AI that learns from trial and error, much like a human brain. The successes and failures reinforce future attempts, allowing for adaptation.

  9. Large Language Models: Very large neural networks trained on extensive amounts of text from a selected language.

  10. Generative Pretrained Transformer (GPT): A form of AI that takes strings of inputs and processes them all simultaneously instead of one at a time.

Important Facts and Statistics

  1. The Artificial Intelligence industry was valued at $86.9 billion in 2022. It is projected to be valued at $407 billion by 2027. Programs such as ChatGPT show broad potential in education for students, educators and administration.

  2. In May 2023, the U.S. National Science Foundation announced a $140 million investment into artificial intelligence research at seven universities across the country.

Three-Point Plan

(1) Expand funding beyond the seven Artificial Intelligence research institutions.

In order to diversify Artificial Intelligence research and ensure equitability within the field of AI, the NSF will expand funding to seven public universities across the United States. The seven initial recipients of the 2023 NSF investment will lead the branches of AI research, and all other recipient universities will be assigned to one of the seven branches. In 2026, the NSF will expand funding to another seven universities, with a focus on funding public universities and universities with high percentages of underrepresented minorities in the field of computer science and artificial intelligence. 

(2) Define a curriculum for ethics in artificial intelligence.

This universal curriculum will include a class on the biases of AI and two classes on privacy issues in AI. Each participating research institution must require these classes in its undergraduate or graduate AI curriculum in order to receive funding from the NSF. Every three years following the initial expansion of AI funding, the NSF will re-evaluate the new ethical concerns attached to AI and adjust the curriculum accordingly.

(3) Monitor private funding of Artificial Intelligence research.

The NSF will create a database of private investors from participating universities that may accept funding in order to ensure that universities work within the ethical framework of AI research as defined by the NSF.


Why this Initiative is Important

The NSF will be able to generate new funding for programs designed to support AI research and learning outside of the seven original universities. This allows the Association for Computing Machinery (ACM) to lay out a standard curriculum for AI ethical teachings. This will plausibly the United States in the long run because of AI's societal potential. 

Economic Impact

Adoption of AI skills and ethics into course curriculum leads to economic growth. Learning AI fundamentals will accelerate the growth of this new industry. Not only will this create new jobs, but it will also improve the productivity in the already existing industries we know today. All these economic benefits translate into social benefits. But these developments must be guided by ethical considerations. Most concerning is the protection of privacy and human rights, as AI is widely used to collect and interpret data. Curriculum about ethical implications allows for a deeper understanding of potential future regulations of AI, and thus the best ways to take advantage of this emerging technology economically and socially. It all ties back together.  

The opinions expressed in this article are those of the individual author.


Abdous, M’hammed. “How AI Is Shaping the Future of Higher Ed.” Inside Higher Ed, 22 March 2023,

Calhoun, Vaughn. “The Future of Higher Education – the Rise of AI and ChatGPT on Your Campus.”, 23 May 2023, Accessed 21 July 2023.

Haan, Kathy. “24 Top AI Statistics & Trends in 2023 – Forbes Advisor.”, 25 April 2023, Accessed 21 July 2023.

Nietzel, Michael T. “NSF Announces $140 Million Investment in Seven Artificial Intelligence Research Institutes.” Forbes, 4 May 2023, Accessed 21 July 2023.

Sabzalieva, Emma, and Arianna Valentini. ChatGPT and Artificial Intelligence in Higher Education. 2023,

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