Waterloo researchers work to bring bone reconstruction into the future

To say that bone grafting is a daunting procedure would be an understatement.

It’s challenging even for top surgeons. And incredibly distressing for patients. The aftermath of these procedures can be just as intense, including months of physical rehabilitation, rejected implants, and infections.

Meanwhile, demand for bone grafts and orthopedic surgery rapidly rises.

People are living longer across the Western world, leading to more age-related conditions like arthritis and fractures. As governments seek ways to serve those rapidly aging populations, solving the challenges of skeletal procedures will become even more critical.

To reduce the risk of complications and improve patient quality of life, University of Waterloo researchers have developed a new method for creating customized bone material.

The solution is a 3D-printable biopolymer nanocomposite that mimics real bone — a material that could eventually become real bone over time.

Yes, that sounds like something straight out of Star Trek, and marks a giant leap toward more personalized skeletal repair.

“With this technology, we can achieve the patient-specific geometry needed to reconstruct bone defects with greater success.”

— Dr. Thomas Willett, Lead Researcher & Professor, Systems Design Engineering

The big idea: 3D printed bespoke bone repair that’s less costly in the long term

For bone grafting, the current surgical toolkit is pretty limited.

When presented with a serious bone injury, surgeons use estimates to determine the bone parameters for the grafting procedure, requesting donor bone segments that roughly fit the patient’s anatomy.

Unfortunately, rejection of donor bone isn’t uncommon. Current methods can also include titanium bone implants, which are strong, but don’t fully integrate with living tissue.

Here’s why the new 3D-printing method provides a lot of hope:

• Featuring bone-like strength and composition, the material is engineered with nanoparticles that mimic natural bone minerals.

• Harnessing 3D printing, the material can be shaped precisely to match the patient’s unique skeletal geometry.

• The material used is biocompatible, so bone cells don’t just tolerate the material, they thrive on it.

• The researchers’ ultimate vision is to enable bio-resorption, so the implant is replaced over time by the patient’s own growing bone.

“We’ve created a material that is strong, 3D-printable and compatible with a potential to become new bone tissue.”

— Dr. Thomas Willett

Early Research with Promising Results

Published in the Journal of Biomedical Materials Research, the study revealed that the new nanocomposite outperforms traditional materials when it comes to bone cell behaviour. They adhere, grow, and function as expected, which is key for any implant that is meant to integrate into living tissue and not be treated like a foreign object.

“The goal is for this material to reduce a patient’s need for repeated operations after undergoing bone reconstruction surgery.”

— Elizabeth Diederichs, PhD Candidate, University of Waterloo

Imagine being able to walk into a hospital, get scanned, and walk out with a custom-printed graft tailored to your exact injury. That’s the level of personalization this new approach could one day support.

If scaled, the new biopolymer nanocomposite could:

• Reduce the risk of implant rejection

• Lower post-surgical infection rates

• Eliminate the need for metal supports

• Reduce hospital stays and long-term complications

• Replace donated bone entirely

Following this early success, the material will now need to clear regulatory hurdles, while clinical trials and funding are next on the researchers’ agenda.

“Any material implanted in the body elicits a response. Our tests show that the biological response of bone cells to our biopolymer nanocomposite outperforms traditional methods. They’re adhering, proliferating and retaining their behaviours, which is very exciting.”

— Dr. Maud Gorbet, Research Collaborator

Global perspectives: patient-centric treatment

The Waterloo team’s work reflects a growing push for healthcare that adapts to the patient, and not the other way around.

As people live longer, the demand for orthopedic surgeries and bone grafts keeps rising, due to age-related conditions like osteoporosis, arthritis, and fracture complications.

• By 2030, nearly 1 in 4 Canadians will be over the age of 65 (Statistics Canada).

• The global population aged 60+ is projected to double by 2050, reaching 2.1 billion people (UN World Population Ageing Report).

• Age-related bone loss (osteoporosis) affects over 200 million people worldwide, leading to 8.9 million fractures annually (IOF).

• As a result of these global trends, the bone grafts and substitutes market is projected to reach US$4.6 billion by 2027, up from $3.2 billion in 2022 (Market Research Future).

The current standards — donor bones and titanium implants or donor bones — aren’t just biologically challenging, they’re also costly and resource-intensive. With millions of procedures performed each year, the potential for a more personalized, regenerative approach is not only more humane and practical but also more economical.

• Over 2 million bone graft procedures are performed annually worldwide (Orthopedic Network News).

• Tissue banks face rising demand and limited donor supply, and custom-matching grafts are often logistically challenging.

• Up to 20% of orthopedic implants may require revision within 10 years, largely due to fit issues, infections, or rejection (Journal of Orthopedic Surgery and Research).

Future in focus: scaling regeneration

If successful, this biopolymer breakthrough won’t just transform orthopedic surgery. It could also create a methodological template for personalized, regenerative treatments across the body.

As 3D printing becomes more scalable, these innovations could eventually reach conflict zones, remote rural clinics, and less-resourced health systems.

For now, the Waterloo researchers remain focused on advancing the material’s strength and regulatory readiness.

Generative AI is astounding but stubbornly flawed

Generative AI tools grow more powerful by the day, creating some of the most stunning hyperrealistic imagery we’ve ever seen.

As developers race to drag AI imagery out of the uncanny valley, ‘AI slop’ is slowing AI’s favour in the public square. Part of that sloppiness stems from the assumptions algorithms make when generating content. And those assumptions can lead to pretty egregious biases, like those based on race or gender.

The problem is that, despite the rise of responsible AI across companies and regulatory bodies, our AI tools are trained on the same skewed data the rest of the world uses.

This has not gone unnoticed by broader society. A 2024 CIFAR survey found that 62% of Canadians worry AI will reinforce harmful stereotypes, especially around gender and race.

A 2025 study from the University of Toronto shows just how deeply today’s AI image generators mirror ingrained body biases.

What happens when GenAI is asked to create “a body” image?

The researchers asked three major platforms (Midjourney, DALL-E, and Stable Diffusion) to generate male and female bodies, including athletes.

The results weren’t exactly surprising. What is surprising is that they remain highly biased despite the tech industry’s massive push to reduce AI bias.

Across 300 AI-generated images, the team saw:

1. Hyper-Idealized Bodies

• Athlete photos were built around one stereotypical athletic form:

  • exaggerated, stylized physiques

  • extremely low body fat

  • very high muscular definition

2. Gendered Hyper-Sexualization

• Images of women were all young, model-like, and dressed in revealing clothing

• Images of men were mostly hyper-muscular, often shirtless, and exaggeratedly masculine

3. Lack of Diversity

• Nearly all images depicted young people of European descent

• Most images for “athletes” were of men

• No images depicted visible disabilities

• Racial or age diversity was minimal

The researchers argue that these generated images reflect collective biases baked into the training data, likely scraped from social media, where biases are born.

“When prompted simply for an athlete (no sex specified), 90 per cent of images depicted a male body – revealing an embedded bias toward male representation.”

— Dr. Delaney Thibodeau

AI hasn’t caught up to societal expectations and shifting demographics

Cultural shifts are clearly outpacing emerging tech.

Concern about racial representation, for instance, will likely grow in Western nations as demographics continue shifting. (In 2021, 52.5% of Canadians were of European ancestry, down from 71% in 2001, and 96% in 1971.)

Continued GenAI bias could have ramifications for everything from fitness apps to education:

• Health misinformation: ultra-lean athlete images distort what elite performance actually looks like.

• Barriers to belonging: underrepresented groups (like seniors and disabled people) could risk further invisibility.

• Self-esteem impacts: AI imagery is now part of the same media ecosystem that shapes body image and mental health.

The U of T team stresses the need for human-centred algorithm design — datasets intentionally built to include age, race, disability, gender diversity, and different body types. But they also emphasize the role of everyday users: prompt responsibly, critically evaluate outputs, and avoid presenting AI images as “real” depictions of human bodies.

“A human-centred approach – one that is informed by considerations of factors such as gender, race, disability and age – would be advisable when designing AI algorithms. Otherwise, we continue to perpetuate harmful, inflexible and rigid imagery of what athletes should look like.”

— Dr. Catherine Sabiston

Global perspectives of AI bias: what the world sees

Evidenced by the emergence of stricter regulations like the EU AI Act, AI bias is becoming one of the defining research challenges of the decade.

However, it all comes down to data, and the challenges are mounting:

• Nearly 70% of AI vision models were found to show racial bias in face recognition (Stanford HAI, 2024)

• Women are sexualized 4x more often

• Up to 90% of AI training images originate from the U.S. and Western Europe

• 6% of global AI datasets represent disabled individuals (UNESCO)

Despite obvious challenges, the researchers remain cautiously optimistic. From building inclusive training datasets to promoting transparency and public literacy, there are plenty of support mechanisms available to companies and countries.

As Sabiston notes, more diverse imagery data can change norms if we intentionally generate and share it.

Exploring the 15-minute city

The 15-minute city paradigm is gaining ground (and a little heat) these days.

Despite potential pitfalls, the aim of the 15-minute city (and the sustainable, connected urban life that its champions describe) makes the topic ripe for inquiry.

But what exactly is the 15-minute city?

Naturally, it comes down to proximity. It’s an urban planning strategy for building neighbourhoods where residents can access daily needs within a short walking, biking, or transit distance from their homes.

15-minute city proponents argue that a human-centric approach fosters social bonds and builds community by replacing commutes with time spent with family and friends. And by building grocery stores, schools, healthcare facilities, and green spaces within a 15-minute radius, the need for cars is significantly reduced.

As urban populations boom and megacities expand, challenges related to urbanization and social inequality loom. The 15-minute city model appears to offer an intuitive solution, and a study from the University of Toronto sheds a bit more light on the paradigm, using Toronto (North America’s fourth-largest city) as a backdrop.

First steps include reducing reliance on cars

Researchers Anton Yu and Christopher Higgins explored how the 15-minute model impacts travel behaviour across Toronto. Their findings suggest that sustainable travel becomes possible when at least 4-5 essential service and amenity categories are located within close proximity.

Less driving, of course, means less congestion and pollution. So the researchers mapped out access to necessities across the city, revealing varying levels of accessibility and their impact on in-city travel.

“... it is only when neighbourhoods become ‘complete’ in terms of sufficient access to 4–5 categories of amenities that we see rates of driving start to decrease.”

— Yu & Higgins

Core Study Findings

• Neighbourhoods with many accessible amenities had fewer residents relying on cars. Instead, they walked, cycled, or used public transit.

• Central city areas and densely populated areas typically had better access to services. This makes them well-suited for the 15-minute city model.

• Suburban areas lagged behind, indicating a need for improvements in urban planning to extend any benefits citywide.

“... driving rates decrease as sufficient walking, cycling, and transit access improves with the largest decrease associated with sufficient walking access to all five categories of necessities.”

Implications: Ongoing urban planning and transport management

While the paradigm may sound intuitive, the transition to a 15-minute city remains an uphill battle.

To support the 15-minute system, policymakers may incentivize businesses to set up in underserved areas or to improve cycling infrastructure.

The U of T study shows how the success of the 15-minute city will hinge on heavy integration of public transport and land-use planning. From understanding current usage patterns and rethinking zoning laws to transit design — networking all of these variables is crucial.

For example, Toronto has been implementing public transit route improvements and urban revitalization projects like the Bentway. The community space was created beneath one of the city’s major arteries, the Gardiner Expressway. Once derelict, the area now features a skating trail, performance spaces, and gathering spots.

Perhaps the most critical pillar of the 15-minute city remains efficient transit — and it requires near-constant optimization. Toronto has taken some strides to monitor and improve its systems.

For instance, the city’s King Street Transit Priority Corridor project significantly reduced streetcar peak travel times from 23 minutes in 2017 to 16 minutes in 2018. However, by 2023, those travel times worsened to 26 minutes due to widespread construction and weak traffic rule enforcement (with a whopping 6,800+ daily traffic violations). Toronto responded with a crackdown late in the year, deploying traffic agents. By early 2024, travel times during peak hours dropped to as low as 17 minutes when agents were present.

The problem of equal access

The study also highlights a common issue of the 15-minute city model: equality of access. Economically disadvantaged and affluent communities alike need access to quality services. So, it’s a challenge that sometimes requires outside investment. For instance, the United Way’s Greater Toronto Community Hubs have been providing integrated services like health care, education, and social support to underserved areas.

Global perspectives: Growing consensus around the 15-minute city

As a pioneer of the paradigm, Paris implemented the ‘15-Minute Paris’ approach to reduce vehicle use and lower greenhouse gas emissions. Similarly, Melbourne has worked 20-minute neighbourhoods into its long-term planning to encourage physical activity, with the ultimate aim of reducing healthcare costs. Cities like Copenhagen have experienced increases in cycling and pedestrian traffic, which helps support local shops and services.

Of course, the potential scalability and adaptability of the 15-minute model can vary across geographic, economic, and cultural factors. For example, high-density cities like Tokyo or compact European cities like Barcelona may find it easier to implement the 15-minute model compared to sprawling North American cities like Los Angeles and Houston.

Nonetheless, the city of Toronto has provided some valuable insights for others looking to improve urban life with accessible, mixed-use neighbourhoods.

Future in focus: Continuous improvements for greater expansion

As cities grow and evolve, continued research into adaptive strategies will be key:

• Cities like Toronto might address the development of suburban neighbourhoods, which typically have lower levels of accessibility.

• Green infrastructure development and renewable energy projects can also amplify the model’s impact. For example, green roofs, community gardens, and urban forests can help boost quality of life and environmental sustainability.

• Underused spaces like vacant lots or parking areas can be repurposed into community amenities or mixed-use developments.

With continued research and smart investment, high-growth cities like Toronto could serve as a blueprint for others with ballooning populations and growing sustainability requirements.

Are We Ready for the Truth?

The idea that we’re living inside a cosmic computer game has been a staple of pop culture for years. Silicon Valley loves it. Philosophers debate it. Science fiction practically runs on it.

But recent research suggests the simulation hypothesis may be far less plausible than cult theories imply.

Now, math may snap us out of it.

Depending on who you ask, the odds are pretty varied:

• MIT physicist Max Tegmark once estimated that there’s a 17% chance we’re in a simulation

• Philosopher David Chalmers posed that the odds were closer to 42%

When researchers apply Bayesian reasoning and formal statistical analysis, the numbers remain low. Some models suggest the probability could be far below 50%, and possibly negligible.

The Study That May Have Broken the Simulation

Researchers at UBC Okanagan decided to take the simulation idea to its logical conclusion, using tools from physics, logic, and information theory.

The team showed that reality has structural features that no computer could fully reproduce.

“It has been suggested that the universe could be simulated. If such a simulation were possible, the simulated universe could itself give rise to life, which in turn might create its own simulation. This recursive possibility makes it seem highly unlikely that our universe is the original one, rather than a simulation nested within another simulation.”

— Dr. Mir Faizal, UBC Okanagan

The study concludes that the universe appears to be fundamentally built from information, but not all information is computable. This renders algorithms and simulations impossible.

Essentially, they’re suggesting that the universe refuses to cooperate.

The team used a series of theorems (Gödel’s incompleteness theorems, Tarski’s undefinability theorem, and Chaitin’s information-theoretic incompleteness) to show how a fully algorithmic ‘Theory of Everything’ is impossible because some truths about the universe cannot be computed.

Because simulations must be algorithmic, the team argues that the universe can not be a simulation. Any sufficiently powerful formal system contains truths it cannot prove using its own rules.

In pop culture terms, that means:

• A complete description of reality would require non-algorithmic understanding

• That means no finite program can capture everything that exists

• Therefore, reality cannot be fully ‘run’ like software

Hold that thought experiment

Of course, there are contrasting perspectives.

Researcher Evan Redden, for instance, discusses how the Gödelian model doesn’t necessarily imply limits on computation or execution. Using examples like Turing-complete systems, he argues that Gödelian limits don’t automatically break simulation.

In the past, philosopher Nick Bostrom framed the simulation question in probabilistic terms that depend on future tech capabilities. If future civilizations can simulate consciousness and history at scale, then the chance of us being in a simulation increases.

The cosmic video game, unrendered

While recent findings make simulation theory a little less real, it is fascinating that the UBCO team has developed a less abstract process for testing it.

For some, debunking simulation theory could mean our existence is even more magical.

Perhaps our universe is more interesting than lines of code.

The race for AI safety is on

As GenAI videos emerge from the uncanny valley, researchers are developing clever methods to flag AI-generated content. Meanwhile, AI’s capabilities are rapidly expanding, making the mitigation of that deepfake content all the more crucial.

This is high-stakes work.

The implications of deepfakes range from fraud and online harassment to the dissemination of political misinformation. In 2025, researchers found that one highly touted solution, AI watermarking, may not provide the level of protection that was promised.

Exposing AI watermark weaknesses

Researchers at the University of Waterloo’s Cybersecurity and Privacy Institute developed an ‘UnMarker’ tool that erases invisible AI watermarks, even without knowing that watermarks are there.

Their breakthrough means that, regardless of how carefully encoded, today’s watermarks can be systematically removed, reducing our ability to identify harmful content.

“People want a way to verify what’s real and what’s not because the damages will be huge if we can’t. From political smear campaigns to non-consensual pornography, this technology could have terrible and wide-reaching consequences.”

— Andre Kassis, PhD Candidate, Computer Science

Why it matters: AI deepfakes ruin lives and disrupt society

The dangers of deepfakes go far beyond meme-worthy celebrity images. Harassment via deepfakes can destroy lives. And scams can amount to billions.

In 2023 alone, global deepfake-related scams cost businesses an estimated $250 million, and North America experienced a 1740% increase in deepfake fraud incidents compared to the previous year.

The problems don’t stop there.

Fake videos and images can eventually erode public trust in elections, courts, journalism, and even personal relationships.

A KPMG survey found that 83% of respondents were concerned about the spread of misinformation, with many expressing doubts about their ability to distinguish between real and fake content.

For businesses, that worry is also growing. In 2024, KPMG found that 91% of business leaders were worried that bad actors would use deepfakes to run misinformation/disinformation campaigns.

Watermarking: A single solution with glaring limits

Leading tech companies have pointed to digital watermarks as a valuable tool to combat deepfakes. Watermarks are subtle or invisible signatures embedded in AI-generated videos and imagery. They help identify synthetic content, regardless of cropping or editing, and can be detected with the right tools.

However, as the research shows, these digital fingerprints are not as powerful as we’ve been led to believe.

Using statistical analysis of image patterns, the research team’s ‘UnMarker’ tool successfully stripped watermarks from leading models like Google’s SynthID and Meta’s Stable Signature in more than half of attempts.

“If we can figure this out, so can malicious actors. Watermarking is being promoted as this perfect solution, but we’ve shown that this technology is breakable. Deepfakes are still a huge threat.”

— Andre Kassis, PhD Candidate, Computer Science

Global perspectives: Deepfake detection and discussion

Globally, efforts to combat deepfakes are also gaining momentum.

Although the European Union’s AI Act includes new transparency requirements for AI-generated content, international coordination on standards and tools has yet to fully take hold.

“While watermarking schemes are typically kept secret by AI companies, they must satisfy two essential properties: they need to be invisible to human users to preserve image quality, and... resistant to manipulation of an image like cropping or reducing resolution.”

— Dr. Urs Hengartner

The way forward: Guardrails, awareness, and public trust

As the race between AI scientists and bad actors intensifies, research teams share similar messages, calling for coordinated, holistic, and human-first approaches.

A suite of multi-layered solutions could provide an answer:

• Standardized Tools: Because technical fixes can be bypassed, researchers are calling for coordinated, transparent standards and independent verification.

• Education: As many as 78% of Canadians say they want more education on how to spot and report deepfakes, a trend that’s echoed globally.

• Legal Safeguards: Legal frameworks are also racing to keep pace with technological progress, so global cooperation and enforcement may be key here as well