POTUS Debate Missed Out On AI and LLM policy

So last night and this morning, I spent time listening to and reviewing different takes on the CNN POTUS Debate. Don’t worry, my blog post won’t discuss the logistics of the debate, who “won,” or who I support. But what struck a chord for me is that for more than a few minutes, the two men debated about vitality and golf handicaps but never discussed the biggest economic disruptor of the modern era.

I attended the ISTE conference in Denver earlier this week, where the main focus of discussions and Mainstage speakers centered around the impact of generative AI and LLMs on education and the workforce. It seems that educators and policy makers are heading in different directions, which raises concerns about the implications for my classroom and the country. To further explore this, I decided to consult the models themselves, and the outcomes were quite intriguing.

At first Google Gemini would not respond to my prompt because of the guardrails for the election. However, when I changed the prompt to talk about policy and oversight, it generated a response in 3 different styles and I selected the 2nd option because it was the most fleshed out answer. (See Below)

Image of Google Gemini responses

Why Federal AI Policy Matters for Educators (Gemini)

Large language models (LLMs) and artificial intelligence (AI) are poised to transform education. But to ensure this transformation is positive, we need consistent federal policies. A patchwork of state regulations would stifle innovation and hinder the responsible development of AI in classrooms.

Here’s why federal AI policy is crucial for educators:

Standardization: Federal guidelines ensure AI tools are developed and used safely and ethically across all states. This creates a level playing field for educators and protects students.
Innovation: Consistent regulations encourage companies to invest in AI education tools, knowing the market isn’t fragmented by state-by-state rules. This fosters innovation and leads to more powerful learning resources.
Clarity: Federal AI policy provides clear expectations for educators on how to integrate AI responsibly. This empowers educators to leverage AI’s potential while mitigating risks.
Research & Development: Federal funding can support research on the educational applications of AI. This ensures AI tools are designed with student learning in mind.

In contrast, a state-by-state approach creates uncertainty and confusion. Educators would struggle to navigate a maze of differing regulations. This could lead to:

Limited access to AI tools: Educators in certain states may be restricted from using cutting-edge AI tools due to local regulations.
Unequal opportunities: Students in some states may benefit from AI-powered learning, while others miss out.
Stifled innovation: Companies may be discouraged from developing AI education tools due to the burden of complying with various state regulations.

Federal AI policy is essential to ensure AI benefits all educators and students. It promotes responsible development, fosters innovation, and empowers educators to leverage AI’s potential to create a more engaging and effective learning environment.

Now when I did the same prompts with ChatGPT, it responded to both prompts which are quoted down below.

Images were changed to hide my account name. Also not sure what the Memory updated comment in the first response means. Images of ChatGPT responses.

The Vital Role of Presidential Candidates in Shaping AI and LLM Public Policy (CHATGPT)

As educators, we stand at the forefront of preparing the next generation for a future where artificial intelligence (AI) and large language models (LLMs) will play pivotal roles. The rapid advancements in these technologies are reshaping industries, job markets, and even the way we understand and interact with information. Given this, it’s crucial that our leaders, particularly presidential candidates, recognize the importance of sound public policy on AI and LLMs.

The Impact of AI and LLMs on Education

AI and LLMs have already begun to revolutionize education. From personalized learning experiences to AI-driven administrative tools, these technologies offer immense potential to enhance educational outcomes. For instance, AI can provide real-time feedback on student performance, helping educators tailor their teaching strategies to meet individual needs. LLMs, such as OpenAI’s GPT-4, can assist in generating lesson plans, grading essays, and even offering tutoring services.

However, the integration of these technologies also brings challenges. Issues like data privacy, algorithmic bias, and the digital divide must be addressed to ensure that AI and LLMs serve all students equitably. This is where sound public policy becomes indispensable.

Why Presidential Candidates Must Prioritize AI Policy

Ensuring Ethical Standards: AI and LLMs must be developed and deployed ethically. Presidential candidates need to advocate for policies that ensure transparency, accountability, and fairness in AI systems. This includes addressing biases that can perpetuate inequalities in education and beyond.
Protecting Data Privacy: With the increasing use of AI in schools, protecting students’ data is paramount. Policies must be in place to safeguard personal information and ensure that it is used responsibly. Presidential candidates should champion strong data privacy regulations to build trust in these technologies.
Bridging the Digital Divide: Access to AI-driven educational tools should not be a privilege of the few. Policies aimed at reducing the digital divide will help ensure that all students, regardless of their socio-economic background, can benefit from AI advancements. This includes investing in infrastructure, providing affordable internet access, and offering training programs for educators and students.
Promoting AI Literacy: As AI becomes more integrated into our lives, understanding its workings and implications becomes essential. Presidential candidates should support initiatives that promote AI literacy among students and educators, preparing them to navigate and shape an AI-driven future.
Fostering Innovation and Research: To stay competitive on the global stage, the U.S. must continue to lead in AI research and innovation. Candidates should advocate for funding in AI research and development, as well as collaborations between educational institutions, industry, and government.

The Role of Educators in Advocacy

As educators, we have a unique perspective on the needs and potential of AI in education. We must use our voices to advocate for policies that reflect the realities of our classrooms and the futures of our students. Engaging with presidential candidates, participating in policy discussions, and staying informed about AI advancements are critical steps we can take.

By emphasizing the importance of sound public policy on AI and LLMs, we can help shape a future where these technologies enhance education and society at large. Let’s ensure that our leaders understand the stakes and prioritize policies that will lead to a more equitable, innovative, and informed future for all.

Conclusion

The intersection of AI, LLMs, and education is a dynamic and transformative space. As we prepare our students for the future, it is essential that presidential candidates recognize the importance of crafting sound public policies that address the ethical, privacy, accessibility, and educational implications of these technologies. By advocating for informed and equitable AI policies, we can help ensure that the benefits of AI are realized across all facets of society, paving the way for a brighter and more inclusive future.

The Crucial Role of Federal Public Policy in Regulating AI and LLMs (CHATGPT)

As educators, we are acutely aware of the transformative potential of artificial intelligence (AI) and large language models (LLMs) in the classroom. These technologies can revolutionize education, offering personalized learning experiences, automated administrative tasks, and innovative teaching tools. However, the rapid advancement of AI and LLMs also brings significant challenges that require robust and cohesive regulation. This is where federal public policy plays a crucial role.

The Necessity of Federal Oversight

Federal public policy provides a unified framework that ensures consistent standards across the nation. This is particularly important for technologies like AI and LLMs, which do not adhere to state boundaries. Here’s why federal oversight is essential:

Uniform Standards and Regulations: Federal policies establish uniform standards for the development and deployment of AI and LLMs. This consistency is vital for ensuring that all states adhere to the same ethical guidelines, data privacy protections, and safety measures. Without federal oversight, states may adopt varying regulations, leading to a fragmented and potentially conflicting landscape.
Addressing Ethical and Privacy Concerns: AI technologies raise significant ethical and privacy concerns. Federal regulations can provide comprehensive guidelines on how to handle these issues, ensuring that all educational institutions across the country follow best practices. This includes safeguarding student data, ensuring algorithmic transparency, and preventing bias in AI systems.
Promoting Equity and Access: Federal policies can help bridge the digital divide by ensuring equitable access to AI-driven educational tools. States with fewer resources may struggle to implement robust AI programs without federal support. National policies can provide funding and resources to underprivileged areas, ensuring that all students, regardless of their socioeconomic status, benefit from AI advancements.
Facilitating Innovation and Research: Federal support for AI research and development fosters innovation. By providing funding and creating a collaborative environment between educational institutions, industry, and government, federal policies can drive advancements in AI technology. This unified approach ensures that the U.S. remains a global leader in AI innovation.

The Risks of State-Generated Policies

Allowing individual states to generate their own AI policies can undermine the regulation and growth of the industry. Here’s how:

Inconsistent Standards: Different states may adopt varying standards for AI development and use, leading to inconsistencies. For instance, a state with lax regulations may become a hub for unregulated AI practices, while another with stringent policies may stifle innovation. This patchwork of regulations can create confusion and hinder the nationwide adoption of best practices.
Regulatory Arbitrage: Companies may exploit differences in state regulations by relocating to states with more favorable (and potentially less stringent) policies. This regulatory arbitrage undermines the effectiveness of stricter regulations in other states and creates an uneven playing field.
Impeding National Collaboration: State-generated policies can hinder collaboration between states and institutions. Federal policies promote nationwide cooperation, enabling states to share resources, knowledge, and best practices. A fragmented approach can lead to isolated efforts and missed opportunities for collective progress.
Economic Inefficiencies: Companies developing AI and LLM technologies may face higher costs due to the need to navigate different regulatory environments. This can slow down innovation and increase the cost of bringing new technologies to market, ultimately impacting the education sector’s ability to leverage these advancements.

The Role of Educators in Advocacy

As educators, we play a pivotal role in shaping the conversation around AI and LLM regulation. We must advocate for strong federal policies that ensure ethical, equitable, and innovative use of these technologies in education. Here are some ways we can contribute:

Engage in Policy Discussions: Participate in local and national discussions on AI and LLM policies. Share your insights and experiences to highlight the importance of federal oversight.
Collaborate with Stakeholders: Work with other educators, industry experts, and policymakers to develop comprehensive policy recommendations. Building coalitions can amplify our voices and influence decision-making.
Educate the Community: Raise awareness about the significance of federal AI policies among your colleagues, students, and parents. Empower them to advocate for policies that promote safe and equitable use of AI technologies.

Conclusion

The future of AI and LLMs in education hinges on robust and cohesive federal public policy. By advocating for uniform standards, addressing ethical concerns, promoting equity, and fostering innovation, federal oversight ensures that these technologies are used responsibly and effectively. As educators, we have a responsibility to champion these policies, ensuring that AI advancements benefit all students and pave the way for a brighter educational future.

After getting both to generate, I was able to ask ChatGPT to respond to the Google Gemini response and vice versa. ChatGPT generated a more readable response and comparison. One of the interesting suggestions from Gemini was combining the two responses into one those circumventing it’s previous response about not comment or politics.

“By combining these elements, you can create an even more comprehensive and informative blog post on the crucial role of federal public policy in regulating AI and LLMs in education.”

Before posting, I went back into both models and asked them to generate online citations that explain the generated prompts. The ChatGPT response cite the same source more than once which makes me wonder if it created the citation list based on the order of the metadata in the original prompt or if multiple webpages cited the same material.

Google Gemini Citations

Examples of AI and LLM Applications in Education

Personalized Learning: AI tutors can tailor instruction to individual student needs, providing targeted support and maximizing learning potential. (Source: “https://www.edweek.org/technology/personalized-learning“)
Automated Grading and Feedback: AI can automate grading of essays and multiple-choice questions, freeing up educators’ time for more personalized instruction. (Source: “https://jise.org/Volume23/n1/JISEv23n1p71.pdf“)
Intelligent Content Delivery: LLMs can personalize learning materials based on a student’s reading level, interests, and learning style. (Source: “https://arxiv.org/abs/2402.09269“)

Chat GPT Citations

“Artificial Intelligence in Education: Promises and Implications for Teaching and Learning.” Brookings Institution, 2019, https://www.brookings.edu/research/artificial-intelligence-in-education-promises-and-implications-for-teaching-and-learning/.
“How AI Is Changing Education.” World Economic Forum, 2020, https://www.weforum.org/agenda/2020/01/ai-education-schools-learning/.
“State Regulation of Artificial Intelligence.” National Conference of State Legislatures, 2020, https://www.ncsl.org/research/telecommunications-and-information-technology/state-regulation-of-artificial-intelligence.aspx.
“The Importance of Standardizing AI.” Harvard Business Review, 2020, https://hbr.org/2020/01/the-importance-of-standardizing-ai.
“Ethics Guidelines for Trustworthy AI.” European Commission, 2019, https://ec.europa.eu/digital-strategy/our-policies/europe-fit-digital-age/ethical-guidelines-trustworthy-ai_en.
“Internet/Broadband Fact Sheet.” Pew Research Center, 2021, https://www.pewresearch.org/internet/fact-sheet/internet-broadband/.
“Advancing Equity in Education.” U.S. Department of Education, 2020, https://www.ed.gov/equity.
“National Artificial Intelligence Initiative Act of 2020.” U.S. Congress, 2020, https://www.congress.gov/bill/116th-congress/house-bill/6216.
“The Case for Federal AI Regulation.” MIT Technology Review, 2020, https://www.technologyreview.com/2020/02/14/844716/the-case-for-federal-ai-regulation/.
“State Policy and Regulation.” Council of State Governments, 2020, https://www.csg.org/.
“Regulatory Arbitrage and Market Frictions.” Brookings Institution, 2019, https://www.brookings.edu/research/regulatory-arbitrage-and-market-frictions/.
“AI Policy Collaboration.” Harvard Kennedy School, 2020, https://www.hks.harvard.edu/faculty-research/policy-topics/technology-policy/ai-policy-collaboration.
“Economic Impacts of AI.” Organisation for Economic Co-operation and Development (OECD), 2019, https://www.oecd.org/ai/economic-impacts-of-ai/.
“Educators Advocate for Better Ed Tech Policy.” EdTech Magazine, 2021, https://edtechmagazine.com/k12/article/2021/03/educators-advocate-better-ed-tech-policy.
“How to Regulate Artificial Intelligence in Education.” Brookings Institution, 2020, https://www.brookings.edu/research/how-to-regulate-artificial-intelligence-in-education/.
“How AI Is Changing Education.” World Economic Forum, 2020, https://www.weforum.org/agenda/2020/01/ai-education-schools-learning/.

Needless to say, even the LLMs and GenAI bots can generate statements about the importance of creating national policy for their use. I wonder if after a few days, if the responses will be different. To see the whole set of responses from Gemini and ChatGPT hit the links below:

This is part of my Generative AI in the Classroom series where I write about how AI is changing education and what I have learned from using it. Read the rest of this series here.