Discrimination

The -isms and the -phobias refer to designations of discrimination. Common well-known examples include racism, sexism, anti-semitism, homophobia, xenophobia and islamophobia. In addition to these aforementioned options, discrimination can occur for many other reasons including socioeconomic status, ethnicity, accent, gender, religion, age, or even a specific combination of identities. 

However, where does discrimination come from?
Answer: Unconscious Bias

Every human on the planet has unconscious biases that have been learned through interaction with society. Making a quick categorization of people and situations was important in human evolutionary history and has informed how our brains function (Source).

• Our reflective mind is our conscious thought, made up of beliefs, values and opinions.

• Our automatic mind is the part of the brain that categorizes and formulates associations without the need for active piloting. Automatic associations are: 

  • Learnt through practice 

  • The result from experience 

  • Absorbed with minimal (if any) awareness

Societal messages about people and groups that are untrue embed themselves in our automatic mind. Internalization happens even when we disagree with them in our reflective minds; our conscious minds may reject stereotypes, yet the associations that we reject are nonetheless part of our unconscious thought.

Unconscious Bias Case Study (source and source):

In a landmark 2018 study, “Gender Shades”, MIT Media Lab researcher Joy Buolamwini and co-author Timnit Gebru tested gender classification algorithms developed by Microsoft, IBM, and Face++ (Megvii) to see how well each of their face-scanning systems did at figuring out whether a person in a picture was a man or a woman—a task all three are supposed to be able to accurately perform. If the person in the photo was a white person, their study found, the systems accurately classified the image more than 99 percent of the time. For Black women, though, the systems miscalculated between 20 and 34 percent of the time—which, if you consider that assuming gender (in this case, a heteronormative binary of man or woman) at random would have a 50 percent probability of accuracy, means the algorithm performed worse than just arbitrary guessing or assumptions.

How could that be? Buolamwini says the problem lies out of sight, buried deep in the code that runs this technology. Face-analysis programs, she says, are trained and tested using databases of hundreds (or thousands, even millions) of pictures, which research has found are overwhelmingly white and male. So, a developer might not notice that their software doesn’t work for someone who isn’t white or male, if their dataset isn’t diverse.

This creates a bias in the way artificial intelligence and systems work. Given that some of the brightest minds in technology are tinkering with machines designed to decide what kinds of advertisements we see, whether we get flagged by the police, whether we get a job, or even how long we spend in jail, the implications of human bias coded into the development of these intelligences poses many risks that are/could become barriers for racialized and marginalized peoples. Examples include automatic soap dispensers that don’t recognize black hands, Google and Flickr automatically tagging black people as gorillas in photos, and voice recognition software not being as accurate with female dictation.

For further learning on this case study, check out the Algorithmic Justice League, co-created by Joy Buolamwini, or watch the documentary Coded Bias to dig deeper.

Our unconscious biases are informed by many different sources, one of which is unconscious culture.

Reflection Questions:

• Where is unconscious culture defined and reinforced? 

• Who has the ability to influence unconscious culture?

Unconscious bias when left unchecked can manifest into acts of overt discrimination or racism, intended or not. This can inform how you not only perceive oppression, but also how you understand your privilege and responsibility to resolve conditions of oppression.

The Roots of Racism As We Know It

Despite the widely held belief that racism has existed for all of human history, the concept of race is actually relatively new. The term “race” and its equivalents are not found in ancient texts, nor even in the 14th century travel writings of Marco Polo. Its first known use in French dates from 1684 when François Bernier, a physician from Montpellier, returning from long trips to India, uses it in an article in the Journal des sçavans, the oldest literary and scientific periodical in Europe. This article represents the first theoretical attempt to divide humanity into "races", which coincides with the birth of modern colonialism and the transatlantic slave trade. This is not a coincidence.

Age of Enlightenment and Slavery

• When the scientific and intellectual ideals of the Enlightenment came to dominate the thinking of most Europeans in the 1700s, they exposed a basic contradiction between principle and practice: the enslavement of human beings.

• Despite the fact that Enlightenment ideals of human freedom and equality inspired revolutions in the United States and France, the practice of slavery persisted throughout the United States and European empires. 

• In the late 1700s and early 1800s, American and European scientists tried to explain this contradiction through the study of “race science,” which advanced the idea that humankind is divided into separate and unequal races.

• If it could be scientifically proven that Europeans were biologically superior to those from other places, especially Africa, then Europeans could justify slavery and other imperialistic practices. 

(Adapted from “Teaching Holocaust and Human Behaviour: The Concept of Race, Facing History and Ourselves,” and Phrenology and “‘Scientific Racism’ in the 19th Century,” Real Archeology, 2017)