A.I. is only human

#artificialintelligence

If you applied for a mortgage, would you be comfortable with a computer using a collection of data about you to assess how likely you are to default on the loan? If you applied for a job, would you be comfortable with the company's human-resources department running your information through software that will determine how likely it is that you will, say, steal from the company, or leave the job within two years? If you were arrested for a crime, would you be comfortable with the court plugging your personal data into an algorithm-based tool, which will then advise your judge on whether you should await trial in jail or at home? If you were convicted, would you be comfortable with the same tool weighing in on your sentencing? Much of the hand-wringing about advances in artificial intelligence has been concerned with AI's effects on the labor market.


Who will decide which students get into college – a committee or a computer?

USATODAY

In this March 7, 2017 file photo, rowers paddle along the Charles River past the Harvard College campus in Cambridge, Mass. It's crunch time for college applications, and hopeful high school seniors are working hard to impress admissions committees to land a spot at the school of their choice. What if, instead, you had to impress a robot – or win over an artificial intelligence-driven algorithm? You did everything you could to package your application to highlight just the right combination of grades, extracurriculars and eye-catching essays the counselor at your high school said the admissions committees at your target schools were looking for. Was it all a big waste of time?


GRADE: Machine-Learning Support for Graduate Admissions

AI Magazine

In recent years, the number of applications to the UTCS Ph.D. program has become too large to manage with a traditional review process. GRADE uses historical admissions data to predict how likely the committee is to admit each new applicant. It reports each prediction as a score similar to those used by human reviewers, and accompanies each by an explanation of what applicant features most influenced its prediction. GRADE makes the review process more efficient by enabling reviewers to spend most of their time on applicants near the decision boundary and by focusing their attention on parts of each applicant's file that matter the most. An evaluation over two seasons of Ph.D. admissions indicates that the system leads to dramatic time savings, reducing the total time spent on reviews by at least 74 percent.


GRADE: Machine Learning Support for Graduate Admissions

AI Magazine

This article describes GRADE, a statistical machine learning system developed to support the work of the graduate admissions committee at the University of Texas at Austin Department of Computer Science (UTCS). In recent years, the number of applications to the UTCS PhD program has become too large to manage with a traditional review process. GRADE uses historical admissions data to predict how likely the committee is to admit each new applicant. It reports each prediction as a score similar to those used by human reviewers, and accompanies each by an explanation of what applicant features most influenced its prediction. GRADE makes the review process more efficient by enabling reviewers to spend most of their time on applicants near the decision boundary and by focusing their attention on parts of each applicant’s file that matter the most. An evaluation over two seasons of PhD admissions indicates that the system leads to dramatic time savings, reducing the total time spent on reviews by at least 74 percent.


Killing Affirmative Action Won't Fix Harvard's Prejudiced Admissions

Slate

My 9-year-old brother is a happy, healthy, wide-eyed third-grader. He sneaks a flashlight under the covers at night to read Harry Potter and goes on and on about Minecraft and Legos. He's also brilliant and full of creative energy, excels at math and science, and plays piano and guitar. And the other day, perhaps a bit precociously, he asked me why the news was telling him it would be harder for him and his Asian friends "to get into college someday." What he was referring to is, of course, the recent class-action lawsuit against Harvard, which has produced headlines like "Harvard Rated Asian-American Applicants Lower on Personality Traits" and revealed prejudiced comments made by admissions officers such as "would she relax and have any fun?"