Move over Siri and Alexa…C.L.Ai.R.A . has arrived!
Meet C.L.Ai.R.A. - the first Afro-Latina artificial intelligence (AI).
“…C.L.Ai.R.A. is considered to have the sharpest brain in the artificial intelligence world…[and]is an autoregressive language model that uses deep learning to produce human-like text,” (Black Enterprise). C.L.Ai.R.A was created by Create Lab Ventures, a tech company that provides underserved communities with the skills, resources, and networks needed to thrive in tech and media.
The hope is that with C.L.Ai.R.A.’s debut in classrooms across the United States, young people of color will be inspired and uplifted.
It is important to note that Artificial Intelligence (AI) is a core theme in any STEM (Science, Technology, Engineering and Math) curriculum.
According to Pew Research Center, “Black and Hispanic adults [which C.L.Ai.R.A. is supposedly modeled after] are less likely to earn degrees in STEM than other degree fields, and they continue to make up a lower share of STEM graduates relative to their share of the adult population,” and women only account for a small share of degree earners in fields like engineering and computer science “areas where they are significantly underrepresented in the work force.”
So is C.L.Ai.R.A. enough to counter the “histories and ongoing forms of deeply embedded discrimination, bias, racism,” and white insecurity, that infect U.S. institutions and systems, including technology?
In her interview with Counterspin, Ruha Benjamin, the author of Race After Technology: Abolitionist Tools for the New Jim Code, makes it clear that technology “is not, in fact, objective in the way we are being socialized to believe.”
Counterspin Interviewer, Janine Jackson, offered this example to better illustrate the lack of objectivity, or rather how the implicit biases of the larger society can affect technological outputs, including AI:
“If police are deployed disproportionately to poor communities of color [because of discrimination and racism], then that’s where they make the most arrests. So if you fill a database with that, and then you say, you know, ‘Alexa, where is the most crime, based on the number of arrests?’ Well, it’s going to circle you right back to the data that you fed it, and it’s only predictive because you make it so.”
The Pew Research Center maintains that “the long-term outlook for diversity in the STEM workforce is closely tied to representation in the STEM educational system,” of which C.L.Ai.R.A. of course would be seen as an asset for representation.
However, according to Massive Science’s report on data from the National Science Foundation:
“The share of STEM-field bachelor’s degrees awarded to Black students peaked in the early 2000s and has been falling ever since — despite increasing federal spending on STEM diversity initiatives….
Precisely what is driving the decline is a matter of some debate. Some experts pointed to persistent income inequality and the disproportionate lack of access to quality schools among Black and other minority communities. Others argued that outreach efforts, peer mentoring, and other programs aimed at fostering interest in the sciences among Black students have dwindled, causing enrollments to plummet. But several education and legal professionals also pointed to a more straightforward and sobering correlation: The steady downturn in STEM degrees among Black students, they say, comes in the wake of a large-scale retreat from specific programs and policies that consider race in admissions, recruitment, and retention in higher education — policies commonly known as affirmative action.”
From a Development standpoint, it is suffice to say that likely all of those factors contribute to the current state of bias that can be found in the U.S. tech world.
It remains to be seen if C.L.Ai.R.A.’s introduction to the STEM educational system will have the positive impact her creators are hoping for, and can help to reverse the downward trend of Black and Hispanic/Latinx people in STEM.
While we can hope it is a step in the right direction, there are still several other factors (e.g. lack of quality schools, etc.) that need to be addressed in order for there to be significant and long-lasting change.