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WHAT IS A MONOPOLY?

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When you hear the word monopoly, what is the first thing that comes to your mind? Perhaps Monopoly the game. Perhaps you think of these giant companies that seem untouchable. Whether or not you know the definition of the word is irrelevant for this article, as there is so much more than taking it at face value. Together, we will delve into not only the definition, but also the types of monopolies and examples that you should know.

WHAT IS IT?

A monopoly arises when a company or person has exclusive or near-exclusive control of a market, thereby becoming the only large producer and seller of their product or service.
If the government doesn’t intervene, a monopoly can set its prices to have the highest returns possible, as they control the whole market.

This does not only impact consumers, but also workers. Since there is no competition, companies can drive salaries into the ground with little to no problems. This is when government intervention is needed.

THE TYPES OF MONOPOLIES

There are many different forms that a monopoly can take. Some of them are,

  • Natural Monopoly:
    This happens when a single company or firm can provide a lower cost of service than all other companies in the same sector, creating a nearly impossible route into the market.
  • Government Monopoly
    This is a monopoly owned by the government, hence the name. This can range from issues such as public transportation and postal services across the country to public utilities. This is used to ensure essential services remain accessible and affordable to everyone.
  • Technology Monopoly
    A company owns or has created a technology that dominates the entire market. A perfect example of this would be Google, as they were deemed to own over 90% of the global search engine market.
  • Geographic Monopoly
    A company is dominant in a specific geographic location. A Canadian example would be BC Hydro. This is not only a geographic monopoly, but also a natural and government monopoly.

EXAMPLES OF MONOPOLIES

If you look at the top businesses in the world, you will find many monopolies, whether that is NVIDIA, Amazon or Alphabet.

Looking back in history, we see a unique example. This was the monopoly over US sugar. Owned by the American Sugar Refining Company, they held a staggering 98% of the total market and were actually taken to court against the US government. Funnily enough, the court ruled that they were not a monopoly, which begs the question of how much influence that they really had.

Just because you see the word monopoly doesn’t mean that these companies are immediately breaking the law and require immediate government intervention. In Canada and many other places in the world, monopolies are legal as long as they act within the Country’s act related to free trade. In Canada, this is named the Competition Act.

Hopefully, from reading this, you have learnt something new.
If you are further interested, I urge you to research further into it, as the history of monopolies is very closely intertwined with politics, and that still hasn’t changed. You will not be disappointed by going down this rabbit hole.


WHAT IS MACHINE LEARNING?

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Over the last few years, I am sure that you have heard the words “machine learning” thrown around whenever AI, or any topic related to AI was brought up. Although on a deep level this can get extremely complicated, I am here to break down the key elements of the topic so that you won’t be left in the dark when this and other words like it are brought up.

WHAT IS IT

Contrary to what you may currently believe, machine learning is not artificial intelligence, but rather a subset of it.

Machine learning allows a computer system to learn from tasks without being explicitly programmed to do so.

Once trained, the model moves on by itself without real outside assistance.
This is very different from how traditional coding worked, with the program repeating the same process each time, and if better performance was needed, the code would have to be revisited.

HOW IT ACTUALLY WORKS

The process of how machine learning works at a glance is surprisingly straightforward. The model is given multiple datasets containing images, or data points to train on, and through these images, it picks up on various patterns and then makes informed decisions later based on these patterns.

The simplest example of this could be something like an AI designed to decipher whether there is a dog in an image or not.
To start, the model would be given thousands, if not tens of thousands, of images. Through these, it would pick up patterns about what a dog should look like. Note that these patterns won’t necessarily always be the same as what we agree on. If all the pictures with dogs were in fields, the AI would assign pictures with a green background to be dogs.
This is something that we can clearly see is not true without thinking twice, but for the program, it is incredibly difficult, if not impossible, to properly find these flaws, as it does not have a concept of what a dog really is.

TYPES OF MACHINE LEARNING

There are three main types of machine learning,

  • Unsupervised learning
  • Supervised learning
  • Reinforcement learning

The example I gave above about the dog was an example of Supervised learning. Giving a set of labelled data and allowing the model to identify patterns so that it can make predictions on new data.

If the datasets were not labelled right and wrong, with the AI meant to group them using patterns it observed between similar images with no prior information, this would be considered unsupervised learning.

Reinforcement learning is quite different from the rest and would not fit very well in the example above. This form of machine learning gives the AI direct feedback on each decision that it makes with a score or other ranking system. This is the type of machine learning that trained AI to play chess and Go at an extremely high level, beating the top players in the world.
This is the most exciting form of machine learning that you will see in the news since it is by far the most flamboyant.
The other forms of machine learning are still very important, dealing with issues like spam detection and recommendation algorithms (in conjunction with reinforcement), but rarely make headlines.

REAL WORLD APPLICATIONS

There are countless real-world applications of machine learning, and this number is growing every day.
Some of the major uses include, but are not limited to,

  • AI chatbots such as Claude, ChatGPT, Gemini
  • AI overviews on sites like Google
  • Social media feed curation
  • Autocorrect and predictive text

Machine learning is no longer a concept reserved for computer scientists and politicians. To fully understand the way that the world is moving, you must first understand key underlying concepts like these, even at a surface level, so that you can be well informed about the technology shaping the world.

THE AI THREAT TO DEMOCRACY ISN’T SURVEILLANCE. ITS MANIPULATION

Many people believe the biggest threat from AI is what it knows about you. They’re wrong. The real threat is what it can make you believe.

AI DISTRUST AND THE INTERNET

You wouldn’t be alone in thinking that the information that AI is feeding you is inaccurate. According to a YouGov survey posted in April 2026, over 65% of participants were concerned with AI creating fake or misleading content, specifically related to online content creation. We already see this, with fake and misleading articles being posted across the internet constantly.
Although this is nothing new, the rise of AI makes this process significantly easier.

Even though people have actively expressed distrust in AI misinformation, the practice of fact-checking your sources has significantly declined. A study done by SparkToro in 2024 concluded that over 58.5% of searches end in “Zero-ClickSearches” meaning that after someone searched, they did not click on any article. This number has only increased over the years as AI overviews have become increasingly more popular.

As a result, we are seeing a growing trend where people rely on AI-generated summaries and overviews without verifying the information themselves, even though the majority of the population has expressed distrust in exactly this.

COMPANIONSHIP WITH AI CHATBOTS

If you believe that AI spreading misinformation is limited to Google overviews, it does not stop there. Earlier this year, Linewize and Qoria released a study conducted in 2025 that produced concerning results.

The study collected data from over 1,000 schools’ staff across the United States, the United Kingdom, New Zealand, and Australia.

For the sake of clarity, we will focus only on the results from the United States. Nevertheless, the findings across each country shared similar characteristics.

  • 60% of USA schools report that students are confiding in chatbots/companion bots
  • Almost half of USA schools report that students are developing emotional attachments to said chatbots.
  • Only 3% of schools reported no concern at all for mental health impacts on students
  • 77% of respondents reported fear of students accessing misleading content

This is not only an extremely concerning study, but also a reflection of how the future of the world could go if AI emotional dependency increases at the rate that it has over the last few years.

At first, concerns surrounding AI in schools focused primarily on cheating and academic dishonesty. However, the issue has evolved into something significantly larger.

Let’s take a step back from this for a moment and analyze what this actually means.

1. Youth is becoming increasingly dependent on AI, frequently confiding in and relying on information that AI is giving them

2. Schools across the world have showcased an extremely high percentage of student emotional attachments to these AI Chatbots.

These two points together are already devastating for the future, as it is showing a trend towards not only attachment and validation to something not living, but a decrease in the tendency to critically evaluate situations and to gain an informed opinion.

The adult population is currently skeptical of AI, but the question arises: what happens when the youth grow up and become the adult population? How will the prior addiction to this new technology influence the future of the country and the world?

One conclusion drawn is that manipulation becomes extremely easy.

Governments around the world have expressed wanting to buy out large AI companies, and have started to build their own infrastructure. How will this affect future access to information?

Can we be certain that companies or governments will not use this information to manipulate the population towards certain decisions, just as they have done with various news outlets in the past?

WHAT DOES THIS ACTUALLY MEAN FOR OUR FUTURE

Although the results for youth, not only in Canada and the United States but around the world, look very concerning, this does not mean the issue is too late to address.

The government must make new legislation to address this concern as soon as possible, as we are possibly fighting the largest mental health and addiction battle in human history.

Legislation moves slowly, but addiction doesn’t. Canada and other nations need to stop looking at what people are right now, but rather at what they are becoming before it is too late.

HOW DO CANADIAN FEDERAL ELECTIONS WORK

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I have talked to multiple people over the years about Canada’s electoral process, and I have found that most Canadians have a surprising gap in their understanding of how it actually works.

So, how does a federal election actually work?

HOW ELECTIONS GET CALLED

The Canada Elections Act sets fixed election dates every four years, normally in the third week of October. However, the Prime Minister can dissolve Parliament at any time by asking the Governor General to do so.

This is called a snap election, and is what happened in early 2025 when Prime Minister Mark Carney called an election after winning the Liberal leadership race following Justin Trudeau’s resignation.

After an election is called, there must be a campaign period between 37 and 51 days before voting occurs.
In addition, federal elections are nearly always held on a Monday.

There are a few reasons why a government may decide to call a snap election, including but not limited to:

  • Taking advantage of high polling numbers to gain a majority
  • Breaking the political deadlock in Parliament

HOW VOTING WORKS

To be eligible to vote in Canada, you must fulfill a few criteria, including

  • Be above the age of 18
  • Must be a Canadian citizen
  • Must be registered with Elections Canada either before or on election day

On election day, you have the option to vote at your assigned voting station. If you do not want to do this, you can also participate in advance polling, which is available during the days leading up to the election. You also have the choice to vote by mail.

One thing to note is that in Canada, you technically are not voting directly for the next Prime Minister. Instead, you are voting for the Member of Parliament in your riding. The party that wins the most seats in Parliament usually forms the government, and its leader becomes the Prime Minister

FIRST PAST THE POST

Canada uses the first-past-the-post system for federal elections.

This means that in each riding, the candidate with the most votes wins the seat, even if they do not receive more than 50% of the vote. This system has been heavily criticized over the years, as a governing party can have most of the country vote against it, while still forming government.

For example, in a riding where one candidate receives 35% of the vote, another receives 34%, and another receives 31%, the candidate with 35% would still win the seat even though most voters did not choose them.

For a party to form a majority government, it must win 172 out of the 343 seats in the House of Commons. This is especially important because a majority government does not have to rely on opposing parties as heavily to pass legislation through Parliament.

Multiple candidates and parties have promised electoral reform over the years, but Canada’s voting system has remained largely unchanged.

Canada’s electoral system is quite simple to participate in, but there is some confusion about how the process actually works due to the slightly more complicated inner workings of the system. I hope that from reading this, you have learned something new about the system, or at least cleared some doubt in your mind about what is going on.



WHAT IS CSIS?

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We all know about the United States of America’s undercover police, the FBI or Federal Bureau of Investigation. But how many Canadians can say they know the same about our own investigative division, CSIS?

Founded in 1984 after the RCMP was found to be conducting illegal operations, including break-ins and surveillance without warrants, the Canadian Security Intelligence Service serves as Canada’s primary domestic intelligence agency. Currently directed by Daniel Rogers, they investigate threats such as terrorism, extreme violence, espionage, foreign interference, cyber threats, and subversion (the act of undermining a government’s power). They report to the Minister of Public Safety, currently headed by Gary Anandasangaree since 2025.

Even though CSIS is our domestic investigative agency, there are a few major things that they cannot do, the most notable being to arrest, lay charges, or detain perpetrators. To get around this, they often work very closely with the RCMP, Canada’s national police force.

HOW DO THEY COLLECT INTELLIGENCE

There are multiple ways that CSIS can and does collect data, including, but not limited to,

  • Human sources (interviews, tips)
  • Electronic surveillance (could be enhanced with the addition of Bill C-22)
  • Public Information
  • Partner Agencies in other nations, such as MI5 in the United Kingdom

OVERSIGHT

The intelligence commissioner, currently Simon Noël, must approve certain surveillance activities proposed by CSIS for anything to come to fruition. In addition to this, the federal court must also issue warrants for more intrusive surveillance.
At the end of each year, CSIS publishes an annual public report; however, it is public knowledge that the majority of what they do is hidden.

Something key to note is that if Bill C-22 is passed, and companies are forced to retain private consumer metadata for at least a year, your data may not stay in Canada. CSIS routinely shares intelligence with partner agencies around the world, and more data on Canadians simply means more data that can cross borders.


CSIS has been quietly operating since 1984, and most Canadians will never interact with them. That’s by design. But in an era where your digital footprint grows every day, knowing who can access it and what they can do with it matters more than ever.

How to become a member of parliament

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When important topics are widely debated, people naturally become more drawn to politics to find out whether their beliefs are actually being represented. Canada is no exception — the 2025 federal election saw a voter turnout of 69.7%, the highest since 1993, according to CTV News. But voting is just one way to engage.
For those who want to go further, the question becomes: how do you actually get into Canadian politics?

THE BASICS

There are 3 levels of Canadian politics: Municipal, Provincial, and Federal. Municipal governments represent cities, provincial governments represent provinces, and the federal government represents the country as a whole.

At the federal level, elected representatives are called Members of Parliament, or MPs. According to the House of Commons, Canada has 343 electoral districts, which correspond to 343 seats in the House of Commons: the elected chamber of Canada’s Parliament, where MPs vote and debate on legislation.

Now you might be asking yourself what the difference between a municipal government and a member of parliament is, since they both represent a geographic area within a province. The key difference here is their jurisdiction, or what they are actually accountable for. Your mayor covers local issues such as garbage, public transit and parks, whereas your MP covers significantly different issues such as national defence, immigration, criminal law, income tax, etc.

Also note that ridings are based on population, with each one in Canada roughly housing 108,000 people, differing greatly from cities, as your city could be part of two different ridings at the same time.

STEP ONE: JOIN A PARTY

There are 5 main federal parties in Canada

  • Liberal
  • Conservative
  • NDP
  • Green
  • Bloc Québécois


To join these parties, you must pay a membership fee. These range from $0 to $25, with the Liberal party representing the $0 membership fee. You must also be a Canadian citizen or have permanent residence; however, to actually run, you must be a Canadian citizen. Remember to stay active in your local riding. This is the way to build up relationships to help with your nomination.

STEP TWO: WIN A NOMINATION

Before you can even run in the election, you must first win the “mini election” inside your own party. Through this, they will decide who will represent the party as a candidate member of parliament in your riding.

To even get on the ballot for this, you will need nomination signatures from other members in your riding.

It is important to note that the party leader can override the local ballots by choosing a candidate themselves.

When choosing a riding to break into, try not to choose one with a dominant leader who is already inside your party. As a result, there is significantly less incentive to give you a chance to replace them. Hyper-competitive ridings are much easier to break into, since the party is always looking for a better chance to win.

STEP 3: RUN IN THE ELECTION

Next, you will have to run against the other parties in your riding, going through a similar process to when you ran inside your riding.

This time, you will have to campaign significantly more. This includes town hall meetings, public debates and various advertising campaigns. You will also need to have a campaign manager to ensure a certain level of success.

A significant roadblock in this process will be funding. The Canada Elections Act imposes strict limits for ridings, as well as the fact that individuals are limited to $1,750 per year to a party and $1,750 per year to a candidate. This can make acquiring funding difficult.

Running to be any political figurehead is difficult; I won’t sugarcoat it. However, it isn’t impossible. People often believe that they have no shot at something like this, but digging deeper into the process, we can see that the system is a lot more open than most might understand it to be, and that truly anything can happen.

Canada’s AI minister just hit one year in power. Here’s what he’s built


One year ago, Evan Solomon, former host of both Power Play and Question Period, was appointed the first Minister of Artificial Intelligence and Digital Innovation just weeks after being appointed MP for Toronto Centre. He openly declared that Canada is in a “Gutenberg-like moment,” emphasizing his opinion that artificial intelligence is a civilization-altering shift.

From this, he laid out the following core priorities to accelerate Canada’s economy and technological growth.

  • Support the technical ingenuity of domestic Artificial Intelligence firms
  • Support social ingenuity – protecting consumer privacy and data


From this, notably stating how one cannot exist without the other, and how they must increase in parallel for Canada to effectively move forward with artificial intelligence.

HIS PHILOSOPHY

Throughout the last year, Solomon has stayed true to a single mantra.
“Light, tight, and right.”
This represents how he believes the future of AI regulation should be in Canada, with light meaning that regulation should be minimal, tight referencing that the regulation that does exist should be very specific in what it says, and right. The regulation should be around that with actual risk. If something is not risky, no regulation is needed.
Whether this is the right approach has been debated extensively, with critics arguing that Canada is already falling behind international peers in AI governance.

SO WHAT HAS HE DONE?

  • Launched an Artificial Intelligence Advisory group that ran through October 2025, with the idea to give new recommendations on Artificial Intelligence.
    In the end, 32 total reports were delivered by members.
    In addition, a public consultation was run side by side. Just over 11,000 Canadians responded, a fraction of the country’s population of almost 40 million.

  • Outlined Ottawa’s 6 pillars of AI strategy that will help them complete their goals related to Artificial Intelligence. However, we still await the full document regarding the national artificial intelligence strategy

  • Given $8.5 million to 40 projects across Atlantic Canada.
    This, however, is quite modest compared to the $2 billion funding of the Canadian Sovereign AI Compute Strategy – Canada’s plan to create its own AI Infrastructure to remove dependence on larger tech giants.

  • Revamping Bill C-27. Originally killed when Parliament was prorogued, Solomon aims to bring it back, stating that it is “not gone” but needs to be revisited. Over the course of the year, no meaningful public progress has been made on this, whereas major parts of the world have adopted federal laws on artificial intelligence, such as the EU. However, Canada has addressed some AI concerns, such as deepfakes, through Bill C-16.


Over the last year, Evan Solomon has been laying the groundwork for the future of artificial intelligence in Canada, but when it comes down to it, groundwork isn’t true governance. Canadians might have to start asking themselves if his mantra “light, tight, and right” is doing Canada a disservice, given his apparent lack of urgency around true AI regulation.

The Bill That Can Hand Ottawa Your Private Data

Earlier this year, on March 12th, Bill C-22 was introduced in Parliament by the Minister of Public Safety, Gary Anandasangaree. If passed, this will not only drastically increase mass government surveillance but also chase companies out of Canada that work in the technology privacy sector.

These ideas are not new to Parliament. Similar surveillance provisions were previously bundled into Bill C-2, or the Strong Borders Act, which encompassed not only government surveillance but also border security and immigration measures. Due to intense pushback from the private and technology sectors, the bill was ultimately split into two, with Bill C-22 covering surveillance and Bill C-12 focusing on immigration and border control.

So what does this bill actually mean for you?
The bill aims to grant the government sweeping authority over electronic service providers, compelling them to hand over private consumer metadata if under a warrant. But it goes further than that. Under the bill, companies must also store all consumer metadata for up to a year in anticipation of a potential handover. This means that your data is being held before anyone even asks for it.

WHAT IS METADATA
To understand why that’s alarming, it helps to know what metadata actually is. Think of it like a letter and an envelope. The message itself is the letter, but the metadata is everything on the envelope: who you sent it to, when you sent it, and where you were when you did. Critically, while the bill outlines a one-year retention period, it also allows the government to extend this through ministerial orders, meaning that the window could grow.

THE INDUSTRY REACTS:
This requirement has driven major tech companies to threaten to leave Canada entirely if the bill passes. NordVPN, one of the largest VPN providers in the world, posted on X that “we will consider all viable options, including limiting or, if necessary, removing our presence from Canadian jurisdiction.” Signal, the encrypted messaging app relied on by members of Parliament themselves, has made the same threat.

The risks from this bill don’t stop at government surveillance. Forcing companies to retain metadata they wouldn’t otherwise collect creates a goldmine for hackers, and the bill makes no account for what companies may do while this data sits in their servers. Bill C-22 represents a serious invasion of online privacy. Canadians should be asking not just what this bill does, but where it stops.