Education Week - August 28, 2019 - 6

Early Access to Advanced Courses
Needed for English-Learners
"A Matter of Time: Variations in High School Coursetaking by
Years-as-EL Subgroup"

Helping English-learners access challenging courses
may prevent them from developing long-term language
difficulties, according to a new study in the journal
Educational Evaluation and Policy Analysis.
Prior studies on English-learner coursetaking identified
three subgroups within the English-learner population:
newcomers; reclassified English-learners; and long-term
English-learners. The study-a longitudinal analysis of urban
California students by the Center for School and Student
Progress at NWEA, formerly the Northwest Evaluation
Association-found newly arrived English-learners and those
recently reclassified as proficient take just as many, if not
more, advanced academic courses than their native Englishspeaking peers. Conversely, longer-term English-language
learners take fewer advanced academic courses,
The study identified a fourth group of ELLs, dubbed
"midterm" English-learners-students who are not
newcomers, but may be on the path toward long-term
English-learner status. The authors suggest schools must
do more to support students who struggle with English
proficiency and academics by prioritizing exposure to math,
science, and social studies in the English-learner curriculum
well before they reach high school, the final stage of their K-12
education. For that work, educators must avoid "watering
down" the material, the study says.
"ELLs are very diverse," said author, Angela Johnson,
a research scientist at the NWEA center. "Educators and
researchers have to appreciate the differences in their
strengths and differences in their needs."
-Corey Mitchell

Support and Accountability for
Public and Private Principals
New data from the National Center for Education
Statistics find that principals at private schools tend to have
more experience, 9.7 years on average leading schools
versus 6.8 years for public school principals. Yet leaders of
traditional district and charter schools were more likely
to have participated in recent evaluations and professional
development activities. The data come from a nationally
representative sample of 10,600 traditional and charter
public school principals and 4,000 private school principals
surveyed in 2017-18.
-Sarah D. Sparks

Principals who
have been evaluated
in the last year

51.3

Principals who have
participated in
professional
development

78.9%
68.0

85.5
82.6
77.1
52.1
53.0
43.3

Had
mentoring/coaching

77.0
70.5
69.6

Took part in a
principal network
Took university courses
on principalship
Traditional

Charter

19.5
21.9
22.8
Private

SOURCE: National Teacher and Principal Survey, 2017-18, First Look

6 | EDUCATION WEEK | August 28, 2019 | www.edweek.org

This Is Not Your Average
Summer Computer Camp
AI4ALL seeks to end bias in artificial intelligence
By Alyson Klein
Princeton, N.J.

Anaya Bussey didn't know much about "artificial
intelligence" when she arrived at a camp at Princeton
University earlier this summer other than that "it was
definitely blowing up." But after just three weeks here
she and other students-all incoming high school juniors-teamed up to use the technology to help diagnose melanoma by looking at skin lesions.
Bussey, 15, who is from the Bronx borough in New
York City, has been interested in computer science
since she was in elementary school. But there have
been times when she's been one of only a handful
of girls-or black students-in a computer class or
program.
That wasn't the case at the Princeton summer
camp, run by AI4ALL, a two-year-old nonprofit that
seeks to increase diversity and inclusion in AI education, research, and policy.
AI4ALL believes that getting students like
Bussey in on the ground floor of AI is about more
than just opening the doors to a hot and potentially lucrative corner of computer science to underrepresented groups.
It's also about making sure the technology works
better.

Bias Problems
AI has indeed "blown up" over the last decade.
The technology trains a machine to do tasks that
come close to some of the things a human brain can
do. That means, by using data, AI can learn to recognize faces and voices, understand natural language,
and even make recommendations. It's used in everything from Snapchat filters to self-driving cars.
And demand for AI jobs has more than doubled over
the past three years, according to research from the
job-placement website Indeed.com.
The problem? There's a major potential for bias
with the use of AI.
For instance, studies have shown that the AIdriven risk-assessment algorithms used to figure
out criminal sentences tend to make harsher predictions about black defendants than white defendants. Amazon's AI-powered hiring system appears to screen out female applicants, which led the
company to ditch it. Facial recognition technology
has been a lot less accurate in identifying people of
color, and women, than white men.
"It's easy to portray the danger [of AI] as killer robots," said Tess Posner, AI4ALL's chief executive
officer. But the real danger behind the new technology "might be stopping someone from getting a job
because of a biased algorithm that we don't even
know is a biased algorithm."
Programs like the Princeton summer camp can
help counteract that because, "at the end of the day
it's like who's in the room, who's asking the questions, who gets to shape this from the beginning,"
Posner said. That means making sure that a diverse
workforce is helping to develop the technology as it
begins to have a bigger and bigger impact on society.
The message isn't lost on the Princeton students.
"I definitely think that having different people
in the room will help, because if you're just taking
one segment of the population, they are going to be
thinking about things relatively the same way," said
Daphne Liu, who goes to West High School in Salt
Lake City. "Different people will all think different
and have different ideas and the collaboration of
everyone working together will definitely be much
better than if it's just one type of person."

But right now, there just aren't a lot of people of
color-or women-helping to develop the technology.
The applicant pool for jobs in AI is 71 percent
male, according to a report released last year by
the AI Index, which tracks data on the technology.
And in 2018, women made up just under a quarter of computer and information scientists in the
United States. Black men and women comprised
just 5.4 percent, and Hispanic men and women
only 5.1 percent.

Solving Big Problems
The camps, which last one to three weeks, kick off
with some technical work. Students are exposed to
Python, a coding language that helps them program
in AI applications. They may do some work in math
concepts related to AI, like statistics and probability.
They'll also learn about some of the broader data
issues that inform AI systems, including how data
are collected and cleaned, and how to mitigate bias.
Then, the students break up into smaller teams
for projects, typically centered around how AI can
be used to solve big societal problems. Past projects have focused on cyberbullying, increasing
mobility for aging populations, and sending aid
after a natural disaster.
At Princeton, students divided into four groups.
One looked at DNA sequencing to help figure out an
individual's ancestry, information that can be used
to help figure out how suspectible they are to certain
diseases or find the best course of treatment.
Another group used AI's image-recognition powers to sort through pictures of skin lesions, determining which were cancerous. A third also relied on
image recognition, but used it this time to figure out
which sections of the Amazon were hit by deforestation. And the fourth used natural language processing to figure out which news stories didn't match
their headlines, a possible sign of "fake news."
On the last day of camp, students presented on
how they used advanced machine-learning algorithms-and a lot of trial-and-error-to help tackle
these problems.
And they talked about the broader ethical and
policy implications of the topics they covered. The
fake news group said that the term is tough to define-for some people, any article they don't agree
with is fake news, which would mean there are no
true news stories. Both the DNA sequencing and
the melanoma groups cited Henrietta Lax, a woman
whose cancer cells were used in research without
permission as a cautionary ethical tale.
The chance to use AI to deal with big challenges
is part of what makes this such an attractive potential career to Kai Lockwood, a 16-year-old
from Durham, N.H.
"I've always really wanted to do something that
will help people," Lockwood said. "I've definitely
learned that AI is less [about] people sitting in Silicon Valley in office buildings, disconnected from
the rest of the world. There's people out there in
AI who are definitely trying to be connected to the
problems that they are solving." Lockwood wants
to explore merging AI with another big interest: biomedical research.
Each camp also has a particular theme. At Princeton, it's the intersection of AI and policy. The campers took an overnight trip to Washington where they
met with people working in AI at the Federal Trade
Commission and the National League of Cities.
Another goal of the projects: to give every kind of
student an entrée into AI, even if they aren't wannabe coding wizards. More-advanced students may

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Education Week - August 28, 2019

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