Computer Science: Controversial Topics?

Here are controversial topics in computer science:

There are more than a few controversial topics in computer science.

Some of the most discussed, for very different reasons, are artificial intelligence, privacy, paradigms in thinking, mining, and security.

Some have serious ethical questions while others are mostly debated in academia.

So if you want to learn all about the controversial topics in computer science, then this article is for you.

Let’s get started!

Computer Science: Controversial Topics? (All the Info)

What Are the Controversial Topics in Computer Science? (5 Topics)

I briefly listed the five topics in today’s discussion, but the truth is that controversy comes up a lot with computer science.

The more powerful we make computers, and the more we relegate to the digital world, the more we have to consider the ethics of these actions.

There are countless controversial topics in computer science.

I’m merely focusing on these five because they tend to have the most impact on daily life (or in some cases, I think they’re the most interesting).

#1 Artificial Intelligence

First on the list is artificial intelligence.

It comes up a lot and in many different contexts.

Will robot overlords destroy humanity?

Are self-driving cars the enemy of cab drivers?

There’s a lot to consider, so for our first topic, we’re going to break things into pretty small parts.

What Is Artificial Intelligence?

Artificial intelligence (AI) is the pursuit of algorithms and programs that can run without direct human control.

Some of these algorithms participate in what is known as machine learning.

Others have such complicated and robust instructions that they can react to an incredibly wide variety of circumstances.

In the machine learning realm, neural networks are probably the best-known examples of artificial intelligence.

With a neural network, programmers set up a bunch of variables.

The algorithm is then able to adjust the variables on its own until it optimizes the situation.

This has been used to make machines that play chess, analyze human language, and a whole bunch of other things.

When it comes to complicated algorithms, heuristics dominate the field.

The idea here is to anticipate any condition or obstacle the computer will face and give it a preprogrammed response.

To the casual observer, heuristics seem adaptable and able to think on their own.

A great example of heuristic functions is cybersecurity software.

Why Do People Argue About Artificial Intelligence?

Regardless of the design or application of AI, there is a lot of controversy around the topic.

If you ask around, you can probably find people in your own life who fear the consequences of continuing to develop AI.

It has been a common topic in science fiction, and even Elon Musk, a huge promotor of artificial intelligence, has called it the biggest existential threat to humankind.

For the most part, there are two camps that create controversy.

The first is concerned with rogue or dangerous AI.

Most of those arguments are rooted in misunderstanding how it works.

The second camp is concerned with the negative consequences tied to automation, and those concerns have real merit.

Misunderstanding

AI today is largely misunderstood by the masses, and it is nothing like the dystopian evil robots you may have seen in science fiction movies or shows.

Modern AI is really just a matter of using math to optimize systems.

That’s it.

Even the most sophisticated algorithms today do not really learn.

They adjust according to mathematical formulas, and they are not at all like human intelligence.

With current technology, there is no such possibility as a rogue artificial intelligence.

That remains in the realm of fiction, and this aspect of AI controversy really is borne of misunderstanding.

Job Losses

On the other hand, concerns about artificial intelligence killing jobs are warranted.

It’s hard to say that AI could lead to devastating economic outcomes, but in at least some areas, jobs have been lost to AI automation.

It is a real thing, and that merits the controversy behind it.

Here’s a simple example.

When was the last time you asked a librarian to help you research something?

When was the last time you asked Google?

Even though librarians still exist, the field has diminished by huge margins since the advent of search engines, and it’s not the only field to lose jobs to automation. 

Manufacturing positions have also shrunk in the face of automation.

There are many concerns that self-driving vehicles will replace millions of jobs around the world.

It’s a source of major controversy, and for the foreseeable future, advancements in AI will have to contend with the threat of displacing human workers.

#2 Privacy

One of the most politically argued topics in computer science is that of privacy. 

The European Union famously passed a series of privacy protection regulations in the past few years.

It changed how people all over the world interact with the internet.

That’s a small example of how people argue the right to privacy in a digital world.

It’s a topic that has been around since before the internet, and as computers and computer-related communications improve, it only grows more important.

What Is Privacy in Computer Science?

When it comes to the realm of computer science, privacy refers to how personal information is collected, cataloged, treated, and shared.

In this case, we aren’t talking about your computer spying on you through the webcam (although that is possible).

Instead, the topic really focuses more on how computer scientists build software and tools that collect and manage personal data.

If you have ever read a software user agreement (yeah, they’re long and tedious), then you know.

Tech companies, as a rule, reserve the right to collect data related to how you use their products.

There are plenty of cases where they share that collected data with other companies or entities.

So, the question of privacy is really one of ethics.

What Makes Privacy a Hot Topic?

It’s not hard to understand why people care about privacy.

But, a quick story can really highlight the depths of concern and how controversial this can become.

Some years ago, Target invested heavily in targeted advertising.

They used software to analyze purchases, and that software was sophisticated enough that it could figure things out about people based on what they bought.

It tried to predict health changes, lifestyle changes, and other life events.

It turned out to be very good at predicting pregnancy. 

In a famous case, a teenage girl started receiving targeted ads for prenatal vitamins and other pregnancy-related goods.

When her dad saw the ads, he was angry and raised a fuss with Target.

The end result was that the girl was in fact pregnant, and the software had worked correctly.

But, this result made people uncomfortable.

What else can computer scientists do with private information?

Many find the idea unsettling, and the controversy includes a constant battle over where ethical lines should be drawn.

#3 Paradigms of Thinking

Getting away from ethical dilemmas and unintended consequences, there is the concept of paradigms of thinking.

Computer scientists, neurologists, psychologists, and other experts often argue about the potential and limitations of a computer system.

Is it ever possible to build a computer that thinks like a person?

That simple question is hotly debated among academics.

What Are Paradigms of Thinking?

This is a very different controversy in the world of computer science.

In this case, computer scientists often argue about the paradigms of thinking.

What is that?

It’s a way of describing how thinking works.

In order to make a program that can complete a task, you have to think about how a computer understands inputs and arrives at outputs.

Imagine a computer program that plays chess. How do you tell the computer what move has been made?

How can the computer then contextualize that knowledge in order to select its own move?

At the deep level, these are very intriguing questions, and they don’t have perfectly clear or agreed-upon answers.

Why Do People Care So Much About Paradigms of Thinking?

As opposed to the other controversies on this list, this one is more of an academic debate.

Can a computer system ever truly emulate human thinking?

No one is sure, and you have academics on both sides of the argument.

After all, neural networks were designed by taking inspiration from the human brain.

Despite that, neural networks still operate in a way that is very far from human thinking.

Ultimately, this controversy is important in research and academia.

As researchers figure out more about how to define paradigms of thinking, they can design computer systems around those paradigms and achieve more useful, powerful, and sophisticated computer tools.

#4 Mining

Another contested idea is that of mining.

This can refer to data mining or cryptocurrency mining (and potentially some other related topics).

The big picture is that a lot of computer resources are devoted simply to mining.

Those resources cost money, and they use up a lot of electricity.

As we move more and more into the realm of big data and heavy mining, what consequences do we need to consider?

What Does Mining Mean?

This is not about computers digging in the dirt for gold.

Instead, it’s the digital analog to that idea.

You’ve probably heard of cryptocurrency.

Well, cryptocurrency mining is how computers generate digital currency like bitcoins.

I’m going to skip the technical explanation of how all of that works.

What you need to know for this conversation is that mining uses a lot of computational power.

And, this isn’t relegated to mining for coins.

Remember when we talked about privacy?

Well, that involves something known as data mining.

Computers work very hard to collect and catalog all of your personal information.

So, it’s using up a lot of computation in order to work.

What Makes Mining Contested?

The biggest controversy tied to mining isn’t about privacy, monetary policy, or anything close to those ideas.

Instead, it’s about power consumption.

Computationally intensive tasks require a lot of electricity to run.

So, when millions of computers are mining for currency or data, it’s eating up electrical power.

The concern is that this leads to increased power consumption and the negative consequences that can come with it.

If you’re concerned about greenhouse gas emissions, then computer mining is something to take very seriously.

Even if you’re not overly concerned with the emissions, mining increases power consumption, and in the grand scheme of things, that can drive up the cost of electricity.

Running computers isn’t free, and this uses a lot of computer resources.

#5 Security

The last of today’s topics is computer or cyber security.

It’s a major component of computer science, and there are definitely some hot-button issues tied to it.

I’m going to skip the purely academic arguments for today.

They get pretty deep in the computer science weeds.

Instead, I’m going to focus on a controversial ethical topic.

Is hacking ever ok?

What Is Special About Security in Computer Science?

Security is important to a lot of people in a lot of ways.

When it comes to computer science, the topic is usually centered on cybersecurity.

To keep it simple, cybersecurity is the practice of protecting computer systems from unwanted access.

We could go a little deeper, but that’s probably good enough for today.

So, there are a lot of computer scientists working on ways to make computer systems more secure for any number of reasons.

After all, we bank online, have private conversations online, and even use internet-enabled devices to run the utilities in our home towns and cities.

At the same time, there are a lot of computer scientists constantly working to crack these systems.

It’s a substantial back-and-forth, and most of us are just caught in the middle.

What Is the Controversy About Security in Computer Science?

This controversy is a little different.

Most people agree that hacking is bad and that security is good. But, things get a little muddled where states are involved.

Cyber warfare is a thing in the modern world.

Countries use hacking and computer attacks to contest with each other while civilians are caught in the middle.

But, because such activities are state-funded and sanctioned, there is an argument about the ethics of cyber warfare.

Is it ok to be a professional computer scientist working for your own government to carry out an attack on an enemy?

Even grayer is where states aren’t involved.

There are well-known hacker groups like Anonymous.

They often use their resources to go after groups or institutions that they deem immoral.

Assuming they’re right (which is a big assumption), is it ok to hack an evil organization?

Or, does that just leave the whole digital world less secure?

These arguments form the gist of the controversy.

You can see how it might evolve from here.