2035: A Day in the Life

Inspired by a graduate class discussion post, I envisioned what a day in my life could look like as a chemistry teacher in 2035, especially in regards to how AI has woven its way into education. I am often asked if AI will replace teachers, of which my answer is always “Absolutely not. It will make human teachers better.” This short story is how I explain what I think the future will look like. Afterwards, I have a “How We Got Here Section” with how policy and governance will help this come to be.

My day in 2035 starts the moment my bedroom lights gently brighten. They do not flick on. They rise slowly like a warm sunrise as they are tied to my circadian rhythm. Overnight my home’s ambient sensors followed my sleep phases and adjusted temperature and airflow based on biometrics. No alarms needed. The system knows the difference between feeling rested and being jolted awake and it always chooses the kinder option.

In the bathroom my mirror greets me with a soft “Good morning Christiana.” A quiet two minute toothbrushing timer glows around the edge of the glass. While I brush it shows my day’s schedule, the groups for the titration lab and any safety notices from the chemistry wing. My AI home assistant named Argon summarizes family updates. My 17 year old son, Rowan, has his robotics scrimmage that evening and my daughter Mae,who is 12, has her solar car project check in. Lumen also reviews the morning headlines I care about. New pedagogy research. Updates on AI ethics. NASA mission briefs. And occasionally a wonderfully odd science article I can use to hook my students later. AI is everywhere but it is quiet and respectful like electricity. It powers the flow of life without demanding attention.

I still drive my car because I like driving. The car simply stays aware for me. Traffic flow AI predicts patterns ahead so the ride feels more like gliding than stopping and starting. As I pull into school my faculty badge syncs with the building. It activates the ventilation profile for the chemistry labs and the system increases air exchange for titration day because it already knows today’s plan.

Before AP Chemistry arrives my instructional AI partner Catalyst helps prepare the lab. It scans burets for micro fractures with a spectral sweep. It verifies that the 0.100 M sodium hydroxide solution is still within tolerance. It generates adaptive pre lab questions for each student based on their past misconceptions and learning patterns. It logs chemical usage into our environmental impact ledger so we can stay transparent about waste and sustainability as well as prepare orders for next school year.

But I am still the architect. I set the sequence of learning. I decide which conceptual hurdles will matter. I choose the struggle points that will lead to the biggest intellectual payoff. Catalyst clears the noise so I can focus on the craft.

My students pour into the classroom buzzing and excited. Titration days have the same energy as a holiday. Each lab bench has a micro augmented reality overlay that students can summon when they want volumetric hints. Their goggles record their procedures so they can reflect later. A safety watcher quietly monitors clamp placements and liquid levels and alerts me if something looks risky.

But here is the real magic. Students still swirl their Erlenmeyer flasks by hand. They still lean in and argue whether the faint pink endpoint is actually faint enough. They still count drops when they want the tactile feel of the moment. I circulate the room and laugh with them and guide their reasoning and listen to their arguments about acid base behavior. AI tracks the data but humans interpret it. This generation knows how to verify cross reference and question. They grew up understanding deepfake detection and digital ethics so they are naturally skeptical in the best possible way.

Students who finish early test simulated titrations where the acid is impure or the equipment is miscalibrated. The simulation helps them visualize error propagation but they still explain the analysis themselves. At the end of class Catalyst compiles each student’s titration curve and highlights patterns worth discussing and pushes a reflection prompt to their portfolios. My role is still beautifully human. I teach them how to think.

During my planning period I visit the robotics lab where students are tuning drivetrain adjustments for an upcoming showcase. Their robots have AI assisted stability systems but every structural element is still built by students. The room hums with energy and creativity. No algorithm can replicate that spark.

After dinner Rowan shows me a balancing prototype he and his team built. Mae asks for help reading a graph from her solar project. We sketch ideas on the kitchen holo canvas. Lumen offers a few design suggestions but the kids pick the quirky one the imaginative one the one that makes no technical sense until it suddenly does.

Before bed Lumen dims the lights and adjusts the environment to prepare for healthy sleep. It feels like living in a personalized wellness ecosystem designed to protect the human parts of life rather than overshadow them. Technology is not the star. It is the stagehand that makes the human moments brighter.

How We Got Here

The world of 2035 grew out of a decade of intentional technological evolution rather than sudden disruption. The process began when global trade systems shifted toward ethical resource management. Rare earth minerals and semiconductors were no longer treated as disposable commodities because nations established a shared agreement for how they would be mined reclaimed and circulated. This work was supported by the rise of closed loop recycling which turned old electronics into a reliable source of reusable materials. Over time these changes stabilized the technology supply chain and reduced the environmental strain that had threatened to derail innovation in the late 2020s.

As artificial intelligence became more complex the energy demands of training and running large models pushed countries to rethink how data centers operated. Instead of scaling back progress, leaders invested in clean energy infrastructure. Small modular nuclear reactors paired with river cooled systems powered most major data farms by the early 2030s. AI began operating on near zero emission energy and thermal recycling systems reused waste heat to power nearby facilities. This shift turned AI from an environmental threat into a sustainability partner.

Policy developed at the same pace. In 2031 the United States passed the Human Centered Artificial Intelligence Integrity Act which created clear nationwide expectations for privacy safety and transparency. The law inspired other nations to adopt similar protections and within a few years, most of the world had converged on a shared framework that defined ethical AI use in schools, workplaces and communities. These guidelines did not restrict innovation. Instead they made it possible for people to trust the systems shaping their lives.

Instructional design also evolved. Universal Design for Learning became non negotiable and AI literacy grew into a core subject taught from elementary school to graduation. Students learned to question sources analyze digital evidence collaborate with AI tools responsibly and use technology to support creativity, not replace it. Robotics programs, clean energy, STEM initiatives, advanced laboratory systems and adaptive learning models all emerged from this new educational foundation.

Everything about the 2035 classroom is built on these developments. Cleaner energy, smarter policy, better design and ethical AI brought us to a world where technology enhances human potential without erasing the human element.