Algorithmic Bias: Who’s Training the Machines?

Algorithmic bias refers to the biases an algorithm picks up from its human creators. In addition, similar to how a child does from its parents. As artificial intelligence and machine learning have jumped. Out of science fiction into the real world. In addition, the potential negative impacts of biases in our systems have grown larger and more imposing.

Benin

But before we even begin discussing such a topic, we have to first break through a key myth most people have about computers and their programs: that they are objective. In reality, algorithms are as susceptible to influence as humans are because we’re the ones building them from the ground up in the first place. They don’t exist as entities in their own right, but as extensions of the human mind—just with more processing power.

That all sounds like a no-brainer when broken down that way, but there’s more. Here, we’re going to look at how machine bias may come about and the very real effects it has on the lives of people living today.

A quick look at cognitive bias

Cognitive bias

Definition: (noun) systematic patterns of deviation from norm and/or rationality in judgement.

Before we get into machine bias, let’s look at bias from a perspective a little closer to home—the ones that exist in our own minds. Cognitive biases are a recognised and highly studied field of modern psychology, touching on everything from the understanding of patterns to the influence of racism.

Basically, the human mind evolved to recognise patterns. It’s just what we do. The problem is that we are taught to irrationally see certain patterns over and above others. Eventually, we tend to ignore contradictory evidence, passing over blind spots in favour of sitting in our comfortable biases. After all, it’s human nature to enjoy a cosy comfort zone.

Some examples of cognitive biases include:

  • Bandwagon effect: the tendency Benin Phone Number to do or believe things because many other people do or believe them.
  • Confirmation bias: the tendency to search for, interpret, focus on and remember information in a way that confirms one’s preconceptions, ignoring competing evidence.
  • Dunning-Kruger effect: the tendency for unskilled individuals to overestimate their own ability and the tendency for experts to underestimate their own ability.
  • Hindsight bias: Thinking you knew something all along, but only after it has already occurred.

Keep in mind that most cognitive biases are almost entirely unconscious, like many of our psychological processes. They fly under the radar, which is why it’s so hard to detect them when it comes to building algorithms that eventually include those same biases.

 

How we raise an algorithm, and what we feed it

 

HowStuffWorks explained it like this:

“To make a computer do anything, you have to write a computer program. To write a computer program, you have to tell the computer, step by step, exactly what you want it to do. The computer then ‘executes’ the program, following each step mechanically, to accomplish the end goal. When you are telling the computer what to do, you also get to choose how it’s going to do it. That’s where computer algorithms come in. The algorithm is the basic technique used to get the job done.”

In the modern world, machine learning is being utilised in every industry, from law enforcement to social media. While the automation of certain processes can make it easier for people to dedicate their energies elsewhere, the presence of unavoidable bias in these algorithms means they can end up having some severe impacts on the people the systems oversee.

Leave a comment

Your email address will not be published.