How correcting for cognitive biases makes life more fair

How much does cognitive bias change people's perception? Well, the history of computing would be a lot different.

Michael Li: A sort of interesting fact is that, while today programming is viewed as an extremely male-dominated field, it was totally the opposite at the dawn of computing.

So if you look at who the original programmers were, they were actually women! All programmers from the very beginning were women and it was because this job was seen as being “beneath” men. And so somehow in the interceding 30, 40, 50 years, that gender of dynamics has completely shifted around.

But what we’re seeing now is that sometimes it’s the implicit biases that we have which are holding back women and minorities from entering the workforce, either as data scientists or as computer engineers and software engineers.

And we’ve seen a lot of research in this area that’s shown that there can be some implicit biases in how we judge people once we know their name, their gender or their race.

And what we do when we assess the people who are going to be working for us is we are completely blind to these things.

We actually strip away the name when we consider people’s applications. We just look at how they perform on a series of challenges that we give them that really try to test their ability to be data scientists and test their understanding of these kind of core fundamental mathematical programming concepts.

And when we do that I think it actually becomes a much more fair process and it actually can help increase the number of women and underrepresented minorities who sort of make it through the screening process.

Just to give you one sort of quick anecdote about this there’s a famous story about music auditions in the 1970s where orchestras had a very, very tiny percentage of their members or their players there – the people who were playing in the orchestra as women.

And what happened is at some point they decided to try to break free from this and they would put down a curtain between the performer, that is the auditioner, and the judging panel that was trying to determine whether she or he should be allowed to play in the orchestra. And when they did the results were night and day.

There’s a famous study that’s up on the National Bureau of Economic Research’s website published by two famous researchers from Harvard talking about this.

It’s called “orchestrating diversity” and it talks about how the results were a night and day difference: the fraction for women who made it past the screening round shot up something like sevenfold between not having the curtain down and having the curtain down.

And it just goes to sort of show that at this time there was an implicit bias that women weren’t really the kind of caliber of musician that you needed to be able to perform at Carnegie Hall, right? At these kind of top level symphonic performance.

And when you put down a curtain and you just listened to them as opposed to being able to see whether they were a man or a woman, you then—without that kind of knowledge you suddenly were forced to make judgments just based on the music, just based on their ability and you saw that you were much more willing to let in women than before.

How much does cognitive bias change people's perception? Well, the history of computing would be a lot different. And so would many major orchestras, who had to implement a curtain during auditions so that judges and orchestral directors could only judge musicians on their skills... and not their gender. Michael Li, PhD, is the founder of The Data Incubator, an education startup training STEM PhDs to be data scientists and quants.

COVID-19 amplified America’s devastating health gap. Can we bridge it?

The COVID-19 pandemic is making health disparities in the United States crystal clear. It is a clarion call for health care systems to double their efforts in vulnerable communities.

Credit: Joe Raedle/Getty Images
Sponsored by Northwell Health
  • The COVID-19 pandemic has exacerbated America's health disparities, widening the divide between the haves and have nots.
  • Studies show disparities in wealth, race, and online access have disproportionately harmed underserved U.S. communities during the pandemic.
  • To begin curing this social aliment, health systems like Northwell Health are establishing relationships of trust in these communities so that the post-COVID world looks different than the pre-COVID one.
Keep reading Show less

Lonely? Hungry? The same part of the brain worries about both

MRI scans show that hunger and loneliness cause cravings in the same area, which suggests socialization is a need.

Credit: Dương Nhân from Pexels
Mind & Brain
  • A new study demonstrates that our brains crave social interaction with the same areas used to crave food.
  • Hungry test subjects also reported a lack of desire to socialize, proving the existence of "hanger."
  • Other studies have suggested that failure to socialize can lead to stress eating in rodents.
Keep reading Show less

A Chinese plant has evolved to hide from humans

Researchers document the first example of evolutionary changes in a plant in response to humans.

Credit: MEDIAIMAG/Adobe Stock
Surprising Science
  • A plant coveted in China for its medicinal properties has developed camouflage that makes it less likely to be spotted and pulled up from the ground.
  • In areas where the plant isn't often picked, it's bright green. In harvested areas, it's now a gray that blends into its rocky surroundings.
  • Herbalists in China have been picking the Fritillaria dealvayi plant for 2,000 years.
Keep reading Show less

Who is the highest selling artist from your state?

What’s Eminem doing in Missouri? Kanye West in Georgia? And Wiz Khalifa in, of all places, North Dakota?

Eminem may be 'from' Detroit, but he was born in Missouri
Culture & Religion

This is a mysterious map. Obviously about music, or more precisely musicians. But what’s Eminem doing in Missouri? Kanye West in Georgia? And Wiz Khalifa in, of all places, North Dakota? None of these musicians are from those states! Everyone knows that! Is this map that stupid, or just looking for a fight? Let’s pause a moment and consider our attention spans, shrinking faster than polar ice caps.

Keep reading Show less

MIT breakthrough in deep learning could help reduce errors

Researchers make the case for "deep evidential regression."

Credit: sdeocoret / Adobe Stock
Technology & Innovation
  • MIT researchers claim that deep learning neural networks need better uncertainty analysis to reduce errors.
  • "Deep evidential regression" reduces uncertainty after only one pass on a network, greatly reducing time and memory.
  • This could help mitigate problems in medical diagnoses, autonomous driving, and much more.
Keep reading Show less
Quantcast