Understanding AI and Its Evolving Role
In the ever-evolving landscape of technology, the emergence of artificial intelligence (AI) has captured the attention of educators, parents, and students alike. As AI systems continue to advance, it is crucial to explore their integration into the learning process, striking a delicate balance between human involvement and the potential benefits of AI-driven tools.
“Predicting the future is easy. It’s trying to figure out what’s going on now that’s hard,” as Ethan Mollick eloquently stated in his book, Co-Intelligence: Living and Working with AI. Mollick’s journey into the world of AI began with a profound realization: a single AI prompt could accomplish 80% of what a team had developed over months. This revelation led him to the concept of “alien co-intelligence” – a form of AI that can interact effectively with humans without being human or even sentient.
Mollick identified AI as a General Purpose Technology (GPT), a transformative advancement akin to steam power, personal computers, or the internet, with the potential to revolutionize every industry and aspect of human life. However, the field of AI has been plagued by hype cycles and boom-and-bust cycles throughout its history, often struggling to handle “unknown unknowns” until the development of Large Language Models (LLMs).
LLMs use statistical methods to complete text, with their pretraining process being a significant and often undisclosed step that is both expensive and potentially controversial, as it likely includes copyrighted material. The legal implications of this pretraining vary worldwide, with the United States taking a more laissez-faire approach. Prelearning can lead to the incorporation of biases, errors, and falsehoods, but no more so than material developed by humans. Fine-tuning, such as Learning from Human Feedback, attempts to mitigate these issues.
While some AI systems, like DALL-E and Midjourney, can create images, others, like Claude, cannot. Prompts are crucial in providing context to AI queries, and AI can exhibit both surprising strengths and odd weaknesses, exceeding expectations in some cases while disappointing with fabrications in others. It is important to keep in mind that much of the pretraining material is skewed towards American, English-speaking, white, and male perspectives, and AI tends to prioritize “pleasing” users over providing accurate answers to prompts.
To address these concerns, standards, agreed-upon norms, transparency, accountability, and human oversight are necessary. Mollick presented four principles for effectively collaborating with AI: 1) Understand AI’s unpredictable and surprising nature, 2) Recognize that AI lacks clear instructions or guidelines, 3) Acknowledge that AI output can vary based on the persona assigned to it, and 4) Be aware that users may begin to believe they are conversing with a sentient being.
The Evolving Role of AI in Education
As AI continues to advance, its potential impact on the educational landscape becomes increasingly apparent. Mollick noted that Large Language Models (LLMs) predict the most likely words to follow a prompt based on statistical patterns in their training data, without regard for truth, meaning, or originality. They cannot distinguish opinion or creative fiction from fact, figurative language from literal, or unreliable sources from reliable ones.
While AI may often be used for boring or repetitive tasks, it excels at creative tasks and can outperform humans in many common psychological tests of creativity. However, creative humans can leverage AI to generate ideas and refine them. AI should be used in any brainstorming activity, and unique responses can be generated by understanding the underlying culture and crafting prompts that ask for less likely answers.
One concern is that relying on AI for first drafts may diminish human creativity, originality, and the ability to synthesize and analyze. Almost all jobs, except those involving physical movement, will overlap with AI to some extent, particularly highly compensated, creative, and educated work. While jobs may not necessarily be replaced, they may change, with mundane tasks being delegated to AI and humans focusing on more creative and critical thinking tasks.
Trusting AI too much and outsourcing critical thinking could potentially hurt human learning, skill development, and productivity. Mollick proposed a framework for dividing tasks into three categories: 1) Centaur (clear delineation between person and machine), 2) Cyborg (blended human and machine work), and 3) AI-only.
AI adoption is happening rapidly and at all levels of organizations, defying the usual Rogers Innovation Diffusion Theory. As AI removes mundane tasks, the remaining work can be more meaningful and high-value. Those with the weakest skills benefit the most from AI, but it raises the bar for everyone. Amara’s Law suggests that we tend to overestimate the impact of new technology in the short run and underestimate its effect in the long run.
The chapter on AI as a tutor was particularly interesting. AI has the potential to address Bloom’s 2 Sigma Problem, which states that the average student tutored one-on-one performs two standard deviations better than students using traditional education. AI can serve as a personalized and individualized tutor, complementing teachers and requiring students to know more facts to use it effectively.
To prevent students from simply looking up answers without reflection or critical thinking, homework methodologies need to be reshaped, similar to the rethinking of math education after the introduction of calculators. Students will need to understand the purpose of assignments rather than merely posting text they find online. In the short term, students must be trained in AI literacy and prompt engineering, focusing on deeper thinking rather than accepting the first result. Long term, AI will improve at self-prompting. Chain of thought prompting, which involves focusing on teaching students to be the human in the loop, is essential as AI works more like a human than software.
AI revives the concept of the flipped classroom and has the potential to be the ultimate educational technology. With AI capable of creating text, audio, and images, and the possibility of hallucinations, it is becoming increasingly difficult to trust the authenticity of what we see, hear, or read. Mollick presents four scenarios for the future:
- AI as a powerful tool, providing invaluable assistance to humans.
- AI as a rival, potentially replacing or outsourcing certain tasks.
- AI as a companion, working alongside humans in a symbiotic relationship.
- AI as a threat, if left unchecked or developed without proper safeguards.
Keeping Humans in the Loop
The integration of AI into the educational landscape raises important questions about the role of humans in the learning process. Mollick emphasizes the need to keep the “human in the loop” when it comes to AI-driven tools and resources.
As an experienced educational writer, I recognize the potential benefits of AI in enhancing the learning experience, but I also understand the importance of maintaining human involvement and oversight. The human touch is essential in guiding students’ critical thinking, fostering their creativity, and ensuring they develop a deep understanding of the subject matter.
One area where AI can potentially be leveraged is in the dissertation process. While AI should not be used to replace the human element entirely, it can be a valuable tool in assisting students with their research and writing. By creatively integrating AI-driven resources, such as automated text generation or image creation, students can be empowered to explore their ideas more effectively.
However, it is crucial that the human element remains at the forefront. Dissertation supervisors must play a active role in helping students navigate the use of AI, ensuring that they are not simply relying on AI-generated content without a deep understanding of the underlying concepts. The goal should be to use AI as a collaborative tool, with the human guiding the process and ensuring the authenticity and quality of the final product.
In the end, the key to success lies in striking the right balance between human and AI involvement. By embracing the strengths of both, we can create a learning environment that is engaging, efficient, and thoroughly grounded in the core principles of education.
Conclusion: Navigating the Future of Learning
As we move forward in this era of AI-driven innovation, it is clear that the role of AI in education will continue to evolve. While the potential benefits are vast, it is crucial that we approach this integration with a clear understanding of the limitations and risks involved.
The “human in the loop” approach, as advocated by Mollick, is a crucial guiding principle. By maintaining human oversight and involvement, we can harness the power of AI while ensuring that the learning process remains firmly grounded in human values, critical thinking, and creativity.
At Stanley Park High School, we are committed to staying at the forefront of these technological advancements, while always prioritizing the needs and well-being of our students. We will continue to explore the integration of AI-driven tools and resources, but we will do so with a steadfast commitment to preserving the human element in the learning process.
As we navigate this exciting and rapidly changing landscape, we encourage our students, parents, and the broader community to engage with us in this conversation. Together, we can chart a course that leverages the best of both human and artificial intelligence, ensuring that our students are equipped with the skills, knowledge, and critical thinking abilities necessary to thrive in the flat world of the future.
