FEATURED DISCUSSION

Sustainability

Artificial intelligence is rapidly expanding across research, industry and everyday life. As AI systems grow more powerful, so do questions about their environmental footprint — from the energy required to power large computing systems to the resources needed to operate digital infrastructure.

At Thompson Rivers University, sustainability is shaping how these conversations unfold. Infrastructure, governance and research are being explored together to ensure that artificial intelligence develops in ways that reflect the same environmental values guiding the university’s broader sustainability commitments.

Universities have an important role to play in this moment. They bring together research, education, infrastructure and public accountability — allowing new technologies to be explored responsibly while considering their broader impacts on communities and the environment.

Artificial intelligence requires significant computing power. As AI systems grow, the infrastructure needed to support them raises important environmental questions — particularly around energy use, water consumption and how large computing facilities fit within communities.

These questions are increasingly relevant in Kamloops.

A new data centre currently under construction along McGill Road will form part of Bell Canada’s Bell AI Fabric, a national platform designed to support advanced research, innovation and artificial intelligence adoption across Canada. Once complete, the facility will contribute high-performance computing capacity to Canada’s growing AI ecosystem.

As artificial intelligence infrastructure expands globally, facilities like this are prompting important conversations about sustainability and responsible development.

Energy

Energy use is one of the most significant environmental considerations associated with artificial intelligence infrastructure.

In British Columbia, most electricity is generated through renewable hydroelectric power. Operating computing infrastructure within this system significantly reduces the carbon footprint associated with high-performance computing compared to regions where electricity grids rely heavily on fossil fuels.

Locating advanced computing infrastructure within B.C.’s largely renewable electricity system allows facilities to operate with a lower emissions profile than many comparable facilities elsewhere in the world.

Water

Water use is another important consideration for many data centres. Cooling systems are required to regulate temperatures and maintain reliable computing performance.

Across the industry, there is increasing focus on technologies that reduce water use, including closed-loop cooling systems and air-based cooling approaches. Minimizing water consumption while maintaining system reliability has become an important design consideration for modern computing infrastructure.

Noise and community impact

Large computing facilities must also consider how they fit within their surrounding environment.

Noise levels, building design and operational impacts are typically addressed during planning and development. Facilities are designed to meet municipal and environmental requirements while minimizing impacts on surrounding communities.

As digital infrastructure develops near campus, conversations at TRU include how these facilities integrate with the campus environment and the broader Kamloops community.

Future opportunities for energy reuse

Modern data centres produce significant amounts of heat as a byproduct of high-performance computing. Around the world, some facilities are exploring ways to capture and reuse this heat to support district energy systems or nearby buildings.

At TRU, the university’s Low Carbon District Energy System (LCDES) — currently under development on campus — is designed to support low-carbon heating and cooling across university buildings.

While the data centre and LCDES are separate projects, future opportunities to recover and reuse waste heat from computing infrastructure could become part of broader conversations about how digital infrastructure and sustainable energy systems may work together.

Common concerns

Universities have a unique role in shaping how artificial intelligence develops.

They are places where new technologies can be examined critically, tested responsibly and connected to real-world challenges. They also bring together students, researchers, industry partners and communities in ways that allow important questions to be explored openly.

At TRU, conversations about artificial intelligence often include broader questions:

How should new technologies affect the environment?
What responsibilities come with large-scale computing infrastructure?
How can artificial intelligence support communities rather than simply disrupt them?
By bringing together sustainable infrastructure, responsible governance and applied research, TRU is helping explore how artificial intelligence can develop in ways that reflect environmental responsibility and community values.

A data centre currently under construction along McGill Road will form part of Bell Canada’s Bell AI Fabric, a national platform designed to support advanced research, innovation and artificial intelligence adoption across Canada.

Facilities like this provide the computing power required for advanced research, artificial intelligence development and high-performance computing. The project contributes to Canada’s growing digital infrastructure while supporting research and innovation across multiple sectors.

No. The data centre is not owned or operated by Thompson Rivers University.

The facility is part of Bell Canada’s Bell AI Fabric and is being developed independently of the university. Its proximity to campus reflects the growing technology and research ecosystem in Kamloops and the Interior of British Columbia.

High-performance computing systems require significant electricity to operate and maintain safe operating temperatures.

The environmental impact of that energy use depends largely on how the electricity is generated. In British Columbia, most electricity is produced through renewable hydroelectric power, resulting in lower greenhouse gas emissions than electricity systems that rely heavily on fossil fuels.

Some data centres use water-based cooling systems to regulate temperatures and ensure reliable computing performance.

Across the industry, there is increasing focus on cooling technologies that reduce water use, including closed-loop systems and air-based cooling approaches.

Large computing facilities are designed to meet municipal planning, environmental and building requirements.

Noise levels, building design and operational impacts are typically considered during planning and development to ensure facilities operate within local standards and minimize impacts on surrounding communities.

Modern data centres produce significant heat as a byproduct of high-performance computing. In some regions, facilities are exploring ways to capture and reuse this heat to support nearby buildings or district energy systems.

At TRU, the Low Carbon District Energy System (LCDES) is designed to support low-carbon heating and cooling across campus. While the projects are separate, potential opportunities to reuse heat from computing infrastructure are being explored.

The growth of artificial intelligence and advanced computing infrastructure creates new opportunities for students at TRU.

Students may benefit through research opportunities, emerging curriculum and hands-on learning experiences connected to AI and data-driven technologies. Faculty research increasingly incorporates artificial intelligence in areas such as environmental science, health research and wildfire response.

As AI becomes integrated across industries, these experiences help prepare students for careers where understanding digital tools, data and artificial intelligence is increasingly important. Partnerships with industry may also support student scholarships, bursaries, internships and experiential learning opportunities.

Want to learn more?

Sustainability in artificial intelligence is not only about infrastructure. Governance, transparency and human oversight are equally important.

TRU horaizon guides how artificial intelligence is introduced responsibly across our university.
We encourage a human-led, values-first approach to all technologies.

We would love to continue the conversation. Sign up for our newsletter and stay in touch.

Overline

General questions

At TRU, we believe in augmented intelligence – that tools like AI can amplify what we as huamns are

AI basics

AI is powerful — but it’s not magic. It doesn’t read your mind, understand your goals on its own, or automatically produce perfect results.

Think of AI like a high‑powered bicycle:

It can go fast, it can climb steep hills, and it can help you reach places you never could on foot — but it still needs a rider. You steer. You balance. You decide where to go.

AI only works well when you give it:

and choose the final answer

Clear, clean information

If you feed AI messy, contradictory, or incomplete inputs, it will give you messy, contradictory, or incomplete outputs. Garbage in → Garbage out.

Instructions that point it in the right direction

AI won’t guess what “good” looks like.
You have to tell it the task, the tone, the format, the audience, and the goal — just like directing an assistant.

Human thinking, checking, and decision‑making

AI needs a human partner to:

correct mistakes
catch hallucinations
refine drafts
judge accuracy

AI can be wrong, incomplete, or biased. Users must check accuracy, evaluate sources, and apply judgment.

AI models generate responses based on patterns, not truth.

They can:

hallucinate facts
miss context
reflect bias in training data
provide outdated information

Responsible use means:

verifying important claims
cross-checking sources
reviewing tone and assumptions

AI output is a draft — not a final answer.

Not all tools handle data safely. Confidential, personal, or sensitive information should not be entered into public AI tools, but can be used with approved AI tools as long as this is done in accordance with FIPPA and TRU policy

There is more than one type of AI tool:

public tools
enterprise/approved tools
locally hosted tools

Each has different data protections.

Before entering information, ask:

Is this tool approved?
Is this data confidential?
Where is the data stored?
Who can access it?

Convenience should never override privacy obligations.

Human review is always required. AI assists with tasks, but users must verify accuracy, ethics, and appropriateness.

AI can scale work quickly — including mistakes.

Human oversight ensures:

accuracy
alignment with institutional values
ethical considerations
appropriate decisions

The faster the tool, the more important the human checkpoint.

Accountability always remains with the person using the tool.

Anyone at TRU can learn to use AI responsibly. Training, guidance, and resources support all skill levels.

Safe use does not require deep technical knowledge.

It requires:

asking clear questions
reviewing outputs
understanding limitations
following guidance

AI literacy is becoming similar to:

digital literacy
research literacy
information evaluation skills

It improves with practice and support.

AI & Me

There are many ways to get involved depending on your interest.

Level Up – Kick-off your AI learning journey with our AI fundamentals course.
horaizon Circles – join a AI and Extended Reality Circle, an Agent Circle, or a peer group built around your specific interests.
Volunteer – help shape the work itself, whether as a project lead, a sounding board, or wherever your time allows.
Join our newsletter to stay in touch with new events popping up throughout the semester.

Responsible experimentation is encouraged. Early questions and early reporting are supported, not punished.

Innovation requires exploration.

TRU supports:

trying new workflows
learning new tools
asking questions early
reporting issues openly

What matters is:

transparency
responsible data use
willingness to seek guidance

Avoiding experimentation entirely can create greater risk by slowing learning and adoption.

AI shifts work but does not eliminate the need for people. Roles involving judgment, leadership, collaboration, ethics, and strategy have become even more important. AI enables efficiency, but humans remain essential.

AI changes how work happens.

Tasks may shift:

manual drafting → AI-assisted drafting
repetitive analysis → AI-supported insights
administrative triage → automated workflows

But human strengths become more central:

decision-making
communication
strategy
empathy
institutional knowledge

AI removes friction — not human value.

AI & TRU

AI use is permitted. What matters is how you use it. Like other digital tools, AI comes with clear expectations and guardrails.

AI is treated like email, spreadsheets, and search engines — a tool whose appropriateness depends on the situation.

It is:

encouraged for brainstorming, outlining, or summarizing
appropriate for administrative drafting and workflow support
limited or restricted when independent skill demonstration is required

For example:

A student using AI to generate ideas and then writing their own analysis → appropriate.
A student submitting AI-written work as their own where original work is required → inappropriate.
Staff using AI to draft a communication and reviewing it before sending → appropriate.

The key question is not whether AI exists — it’s whether its use aligns with expectations, learning outcomes, and professional responsibilities.

AI use is not automatically misconduct. Appropriateness depends on the expectations for a course, assignment, project, or task. Some require disclosure; some prohibit AI; others encourage it.

AI becomes misconduct only when it replaces required learning, originality, or accountability.

Think of AI like a calculator:

allowed in some contexts
restricted in others
required in certain professional settings

Examples:

Using AI to summarize readings before class → generally appropriate.
Using AI to complete a take-home assignment meant to assess personal understanding → misconduct.
Using AI to help structure a report and then writing it yourself → appropriate.

Integrity is about honesty, transparency, and meeting expectations — not about avoiding tools entirely.

Expectations vary by course, program, role, or unit. Instructors and supervisors set context‑specific guidance depending on learning outcomes, research needs, or job duties.

A single rule would not work because different environments have different goals.

For example:

A writing class may restrict AI to support skill development.
A business program may encourage AI for research synthesis and analysis.
Administrative teams may use AI for workflow efficiency.
Researchers may use AI for literature scanning or coding support.

AI policy must be flexible enough to protect learning while still enabling innovation and productivity.

Context determines appropriateness.

AI supports human work; it does not replace it. Teaching, grading, decision‑making, research design, and accountability remain human responsibilities.

AI can:

generate drafts
summarize information
analyze patterns

But it cannot:

understand institutional context
make accountable decisions
mentor students
apply ethical judgment
design research with intent

AI handles tasks. Humans provide purpose, direction, and accountability.

The more AI handles repetitive work, the more human roles shift toward:

oversight
leadership
critical thinking
collaboration

Learning and professional judgment remain essential. AI should support understanding and not replace skill development or critical thinking.

AI can produce convincing outputs quickly — but that does not mean they are correct or appropriate.

Without understanding, a person cannot:

identify mistakes
refine results
judge relevance
defend their work

Using AI without comprehension is like presenting a report you never read.

AI helps people learn faster and work more efficiently — but responsibility for the work remains with the human using it.

Have more questions? Reach out to horaizon+faq@tru.ca