Robotic
Robotic
Nurses:
Nurses:
The Problematic Future of Healthcare
Ivy Evans
ENG 1021
Pikes Peak State College
The Article
The
Article
“Here Come the Robot Nurses”
Authored by Anna Romina Guevarra
Published: The Boston Review
nd
2 August 2021
Author
Author
PhD in Sociology.
Involved in major ethnic studies, such as the racialization
and gendering of certain skills in the workforce.
Founded and manages programs that contribute to these
issues.
Her claim in the article that healthcare “relies heavily on
the labor of poor women of color, often immigrants...” is
given context and credibility by her background.
Biased toward the better treatment of these groups, but
very knowledgeable.
Source: https://glas.uic.edu/profiles/guevarra-anna/
Occasion
Occasion
Written as a response to a robotics company’s
“hopes to be able to mass-produce a robot [named
Grace] for the global market.”
Grace was created during the pandemic, the first
human-like medical robot.
Widspread integration raises questions about what it
means for human workers.
The author penned the article to voice concerns that
Grace will become “another excuse to ignore the
inequities faced by human workers by simply
replacing them.”
Purpose
Purpose
The primary purpose is to persuade.
Firm statements intended to convince
the reader that robots should not be
integrated into healthcare until they
are free of biases and workers can
labor justly.
“Designing a care robot that looks like a white woman
broadcasts a racialized and gendered understanding
of human expertise.”
Care work is seen as “feminine,” and “white.”
This representation exacerbates harmful stereotypes.
Detriments the backbone of poor women of color in the
line of work.
“Outsourcing care may have grave consequences if
racist and gendered biases in the code go
unaddressed.”
Robotic nurses will do more harm than good if the issues
are not fixed.
Algorithms may not evaluate patients equitably.
Even subtle bias will have severe health risks.
Primary Appeal
Primary
Appeal
The primary appeal is Logos.
The author consistently uses objective evidence from peers to support her argument, forcing
readers to make logical connections.
1. “In recent years this has been documented by critics of artificial intelligence...who have noted how
algorithmic biases are reflected in everything from facial recognition systems’ failure to identify
people of color to the technological redlining in search engines of results related to Black subjects.”
→ Other critics have observed a bias beyond just the author. There is greater value in the consensus
of a group, so if multiple people believe algorithms have biased coding, then it must be true.
2. “Sociologist Ruha Benjamin found that one of the most popular tools used by health insurers to
assess health risks defined a theoretical Black patient as having less risk than a white patient with
the same health markers because of racial bias in the tool’s algorithms.”
→ The example of the racial bias can’t be explained in any other way. The algorithm defined a black
patient as having less risk than a white patient despite being identical otherwise, so there must be
some sort of fundamental flaw in how the tool is coded.
Literary Device
Literary
Device
The author uses a metaphor to reinforce her ideas.
“Will the racist assumptions that are
likely baked into Grace’s algorithms
define the type of therapeutic
interventions that patients will receive?”
The bias is not literally baked into the
algorithms.
The metaphor tells the reader that the bias is
fundamentally inseparable.
Like an ingredient in a cake, you can’t remove
it without redoing everything.
The code must be completely rebuilt.
The metaphor sets up the author’s mention of
the Algorithmic Justice League.
AJL is a collective dedicated to coding “more
equitable and accountable artificial
intelligence.”
“The Algorithmic Justice League
reminds us that “we can code a better
future.””
Effectiveness
Effectiveness
I believe the author was successful in her argument.
Skillful use of evidence and examples
forms a compelling, supported
contention.
Main points were clear and stated
consistently throughout.
“A similar bias can be seen in the
case of a telepresence robot called
EngKey…”
“…labor justice must be a precondition
for the adoption of automation.”