When it comes to issues like whether to hire someone for a job, give them a mortgage, or even identify them as a suspect in a crime, human bias can have far-reaching ramifications.
And as more industries turn to technology — and specifically algorithms — to cut costs and increase efficiency, a new consideration arises: When it comes to some of those difficult decisions, can algorithms really yield fairer results?
Algorithms should be immune to the pitfalls of human bias. But despite their seemingly neutral mathematical nature, algorithms aren’t necessarily any more objective than humans.
In fact, without proper checks and balances, their use could perpetuate, and even accentuate, social inequality.
“The prerequisite to algorithmic decision-making is having a ton of data,” says futurist and CBC commentator Jesse Hirsh, who recently completed a Masters in media production, with a focus on algorithmic media and transparency.
In other words, algorithms are everywhere.
Device of our data-rich world
Any organization with lots of data at its disposal is likely using algorithms to sort that information, organize it, and ultimately make decisions based off it.
We already know our Facebook timelines are organized based on what the algorithm deems most relevant to us. And we may take for granted the fact that Netflix uses algorithms to help suggest what movie or television show we want to watch next.
But what might surprise some people is just how many other industries and sectors are already using algorithms to help make decisions. And it’s not just trivial decisions, but ones that have complex social implications and the potential to have a profound impact on people’s lives — ranging from hiring and financial lending, to criminal justice and law enforcement.
Organizations are increasingly turning to algorithms to help make decisions about things like insurance rates, credit scores, employment applications and school admissions, Hirsh says.
“There’s also tons of legal ones that look at potential court decisions, tax issues, and in the U.S., parole.”
Trusting machines more than people
The impetus to turn to algorithms is clear; we want these systems to be just and fair. Getting a job should be based on merit, not gender, and getting a loan should be…