Human Connection in an AI-Enhanced World: Through the Lens of Maslow’s (Amy Choi)

Apr 18, 2024

Amy Choi | Linkedin

Guest Writer

Lulu Gao | lulu@flintk12.com

Teacher reaching out to support student who has reached the top of a pyramid reminiscent of Maslow's hierarchy.

Amy Choi spent over a decade as an educator in both public and private schools before joining the team at Global Online Academy, first as the Associate Director of Faculty Experience and now as the Associate Director of Professional Learning. Global Online Academy is a nonprofit organization that reimagines learning to empower students and educators to thrive in a globally networked society. Most recently, she served as the Learning Architect at the Mount Vernon School in Atlanta, Georgia, a role that allowed her to act as a teacher leader and curricular specialist while remaining in the classroom.

Amy began her career in Seoul, South Korea, where she launched a new online curriculum initiative to prepare international students to study abroad in the United States. This experience shaped her educational philosophy of investing in relationships and people as the foundation. She returned to the States to earn her paralegal certification from Duke University and her Masters in Teaching from North Carolina State University.

Outside of the classroom, Amy is an active researcher and presenter on AI in education, faculty growth and wellness, and equitable assessment practices.

This piece was co-written by Amy and Lulu, Flint’s Head of Teacher Experience.

Introduction: Maslow’s Hierarchy in Your School's AI Strategy

Integrating artificial intelligence into education isn't just about keeping up with trends; it is quickly becoming essential for preparing students for the future. This shift promises to reshape learning, offering personalized experiences and insights like never before. Yet, in the midst of this technological advancement, a critical component remains at the heart of education: the human connection. It's imperative to ensure that AI tools don't just offer efficiency but also foster deeper relationships among teachers and students.

Adapting Abraham Maslow's Hierarchy of Needs to the school environment provides a framework for ensuring these relationships flourish, rooted in the foundational need for safety and security. This article aims to highlight opportunities for increasing human connection and leading students to self-actualized learning as we navigate the integration of AI.

Maslow's Hierarchy pyramid including physiological, safety, love and belonging, esteem, and self-actualization needs.

Safety as the Foundation

Safety and security are paramount in Maslow's hierarchy, serving as the foundation that we can build toward achieving higher needs and aspirations. In the educational context, this translates to creating an environment where students feel physically and emotionally secure, a prerequisite for effective learning and teaching. Moreover, ethical considerations around AI, particularly algorithmic bias, fall within this realm of safety. Ensuring that AI tools used in classrooms are designed and implemented with an awareness of their ethical implications safeguards against practices that could undermine the sense of security within the learning environment.

To encourage critical thinking and awareness around these issues, teachers can facilitate classroom discussions:

Who should make sure AI is fair: the people who make AI or the people who use it? Why do you think so?
What does the saying 'garbage in, garbage out' mean when we talk about AI? How can the information used to teach AI affect whether it's fair or not? How can we effectively prompt AI to promote rather than shortcut learning processes?
What do you think the future of AI should look like to make sure it's used in a good way? Are there any new technologies or rules you think could help?
How should we be careful when using AI to make big decisions, like in courts or hospitals? What kind of rules should there be to make sure it's fair?

By integrating discussions on algorithmic bias and the ethical use of AI into the curriculum, schools can prepare students not only to navigate but also to critically assess the digital tools that shape their learning experiences. This approach fosters a learning environment where technology enhances education without compromising ethical standards or the importance of human connection. Learning and growth require effort that has to come from the student. After all, if a student were trying to gain muscle, they wouldn’t have a robot lift weights for them, right? Teachers play a role in helping students understand what tools are safe and efficient to use in what ways and to what ends, whether it’s using AI to strengthen their understanding of a topic or dumbbells to strengthen their muscles.

Adapted from Dalle 3: “A buff AI robot lifting weights, with a thinner student alongside, completely awestruck by the robot's impressive 'muscles'.”

Safety Measurement as a School Priority

Furthermore, with the integration of AI, the potential to shift focus from administrative tasks to human relationships is immense. However, this potential can only be realized if schools consciously prioritize and measure the quality of these relationships. According to this critical perspective offered by Julia Freeland Fisher at the Clayton Christensen Institute, we can see AI's capacity to automate administrative tasks. However, this advantage hinges on a school's organizational commitment to prioritizing human connections.

As Fisher notes, the efficiency promised by AI tools should ideally lead to more meaningful teacher-student relationships. However, this requires schools to measure and value these relationships explicitly, integrating metrics that reflect the strength and quality of connections within the educational framework. Fisher characterizes relationship data as “missing metrics” of schools, including measurements of quantity, quality, structure, and mobilization ability of students’ networks.

Missing safety measurements according to Fisher and Dr. Mahnaz Charania including the quantity of relationships in student networks, the quality of those relationships, the structure of those networks, and the students' ability to mobilize their networks.

GOA has implemented longitudinal questions in its student surveys to gauge the depth and quality of relationships within our learning community. Longitudinal questions are particularly valuable because they track changes and trends over time, offering insights into how relationships and perceptions evolve throughout the educational journey. Unlike one-time survey questions, longitudinal questions can reveal patterns, growth, and areas needing attention, making them crucial for understanding the long-term impact of our educational practices on students. These questions include:

How well do people in your class understand you as a person? Consider how well they know/understand your interests, goals, aspirations, cultural background, communication styles, strengths and areas of growth, personal challenges, etc.
How connected do you feel to the teacher in this class? Consider how well they establish a supportive/inclusive learning environment, engage student ideas/questions, display genuine interest in student learning and well-being, communicate effectively, etc.

By asking these questions over time, we're not just capturing a snapshot but monitoring the ongoing relationship dynamics within the school. This longitudinal approach enables us to identify trends and make informed decisions to enhance the educational experience, ensuring that every student feels understood and connected on both an academic and personal level. This method is instrumental in fostering a safe, inclusive, and effective learning environment that prioritizes the well-being and development of our students and teachers alike.

The transformative potential of AI in education hinges on our ability to use it as a tool to enhance, rather than replace, human interactions. Adopting measures that value the quality and depth of teacher-student relationships ensures that the efficiencies gained from AI contribute to a more connected, supportive learning environment. This means looking beyond just academic metrics to understand how students are connecting with their educators and peers.

Towards Love, Belonging, and Esteem in Education

When students feel safe and are learning safely, AI becomes a tool for empowerment, connection, recognition, and freedom. This could involve creating learning experiences that are personalized, engaging, and grounded in ethical considerations, where AI tools are used judiciously to enhance, rather than replace, human interaction. Here are two examples that can push us towards this goal: through personalized learning pathways and reflective practices and self-assessment.

Example A: Tailoring educational content to match the unique interests, strengths, and learning styles of each student

For example, an AI could analyze a student's previous assignments, interests, and performance to recommend personalized projects or topics. A practical prompt you might use is: "Based on a student's interest in environmental science and strong performance in projects related to renewable energy, suggest personalized project ideas that combine these interests with their learning style, focusing on hands-on and interactive activities."

Alternatively, you could ask: "Recommend tailored reading materials for a student who enjoys historical fiction and needs to improve in understanding historical events and contexts. Include options that cater to auditory learners and provide engaging, story-driven content." This personalization supports belonging and esteem by encouraging students to pursue their passions and interests deeply, fostering a love for learning that goes beyond the classroom and toward self-actualization.

Example B: AI-powered analytics to offer students insights into their learning patterns, strengths, and areas for improvement

Tools that track progress over time and provide feedback on various skills can encourage students to set personal goals and reflect on their learning journey. For instance, a prompt like: "Analyze a series of quiz results and homework assignments to identify patterns in a student’s learning progress over the last semester. Highlight strengths in analytical thinking and areas for improvement in data interpretation, offering suggestions for personalized study strategies" could be used.

Or, for guiding self-assessment, you might ask: "Provide a template for a self-assessment questionnaire that encourages students to reflect on their recent project on climate change. Include questions that prompt them to evaluate their research skills, ability to work in a team, and the effectiveness of their presentation techniques." This reflective practice, supported by AI's personalized feedback, empowers students to take ownership of their education, a critical step towards self-actualization.

Self-actualization and Future Projection for AI

Maslow describes self-actualization as “to become everything one is capable of becoming”. Just as Maslow emphasized the process of becoming, self-actualized learning just might need to emphasize the process of learning. His theory also asserts that the drive to self-actualize emerges only after more basic needs have been met. An optimistic view of AI and the field of education’s general progression could deem student-driven learning equivalent to the drive to self-actualize within the context of school. The process through which teachers and mentors encourage student agency would then be pivotal in each student’s actualization journey.

With AI, this could mean that teachers take a step back and allow students to shape more of their learning—letting students take the wheel to dictate content while teachers coach them on quality and direction. Bloom’s 2-Sigma Problem has shown the benefits of 1:1 tutoring and when coached well, students can leverage the power of AI to initiate and pursue individualized learning paths. Teachers’ roles will change and it’s increasingly more important to show students the path toward and benefits of self-actualized learning. Teach a student to fish (for knowledge) and they'll learn for a lifetime.

Using Dalle 3: “Image that shows the idea of "teach a student to fish (for knowledge)" and you'll feed/help them learn for a lifetime.”

Conclusion: The Human and the Loop

The promise of AI in education is not just about making teaching more efficient or personalizing learning. It's about how these technologies can make schools more human. The heart of learning is human connection.

With AI’s ability to automate basic knowledge transfer, that impactful 1:1 review session you had with a student who came in to see you after school could happen during class through diversified teaching. You could have more time to make those personal moments 50% of your time rather than 5%. With AI’s ability to synthesize information, projects that couldn’t be scoped wider because of time limitations can now have briefs and outputs personalized to each student’s interests. Students can leverage AI to quickly gather, synthesize, or express ideas across a variety of topics, with you as their guide pushing them to think critically and reflect on the flood of information available at their fingertips.

AI can promise more frequent feedback and new kinds of assessment, but what will truly revolutionize education is what you choose to do with what AI can provide and what more you can accomplish with its help. The efficiencies AI offers should not lead us away from the human element in teaching but rather back to it, providing more space and time for the relationships that drive meaningful learning experiences. By prioritizing and measuring these connections, we can ensure that AI enhances the educational journey, making it not just more personalized, but more human. Teachers will be not merely humans in the loop, but architects of learning who dictate how to draw that loop.