I, For One, Welcome our New Admissions Overlords

*To paraphrase Kent Brockman

Once upon a time, there was a yellow brick road that led to college. You would submit your SAT scores, your GPA, your activities, you would write your essay – and you would submit all of this on paper! And all was good and just in the land, and all of the right students gained admission.

Utter nonsense of course! The college admissions process was a mess then, it’s more of a mess now, and it’s about to get hit by one neutron bomb everyone’s talking about (SCOTUS case which likely ends affirmative action), and another that may be even bigger.

But first, a blast from the past – I was among the last classes of students to apply on paper (Dec 1994) – perhaps one good thing about that era was that students applied to fewer colleges, since they couldn’t shotgun their application to 20 schools via the Common App or the internet. I applied to 6 schools, and had the good fortune to get into all but one. My safety school at the time even had programmatic admissions – if you had a GPA above X and an SAT above Y, you were essentially guaranteed admission, not just to the university but to the honors program!

Admissions have gotten harder since then, although the numbers are a bit of a lie, as elite schools try to lower their acceptance rates as part of the college rankings game – they use the ease of the internet to lure unsuspecting students to submit applications that have no chance of success. Admissions have also become less structured, as more and more schools have eliminated or de-emphasized testing requirements – with the occasional retrench, as my alma mater reinstated the SAT as a requirement (going to great lengths to explain that it IS actually correlated to success at an engineering school). But all of these changes pale in comparison to 2023…

College admissions will be impacted by the end of affirmative action. But they will also be deeply impacted by the rise of generative AI! I’m willing to bet that numerous high school students used ChatGPT to help write their essays this past December. And even with the new paywall, ChatGPT and its competitors are far cheaper than the pricey consultants that wealthy families use for essay ghostwriting (let’s just acknowledge that this happens). While colleges will attempt to deploy tools to stop the practice, students aren’t that dumb – they’ll add their own touch to the essays, making it hard to tell where the robot dropped the pen and where the student picked it up. So what happens to college admissions in an environment where affirmative action is dead, standardized testing is diminished, and essays are written by ML bots?

In the spirit of my days at HiddenLevers, here are a few potential scenario outcomes:

Back to Basics: Schools (in collaboration with SAT/ACT) will reemphasize controlled measures like standardized tests, GPA, class rank, and similar, since they can’t trust much else. This will dismay some and delight others, but it’s easy ground to tread since this was the norm not so long ago.

Human Interviews: Zoom eliminates a lot of the costs of the traditional college interview – but instead of using it as a “positive” tool, schools may begin to use it as employers do – as a primary filter mechanism. This approach will lead to a wide variance in outcomes just as it does with corporations (some are good at using interview-based recruitment to acquire talent, and some simply suck at it).

Welcome Robot Overlords? Here’s a guess for a post-affirmative action AI-enhanced world: admissions decisions will themselves will be handed over to machine learning. By placing a black-box trained algorithm as an intermediary between themselves and admissions decisions, colleges will achieve several goals:

1) Algorithms will likely achieve a higher fit toward whatever class composition the administration wants than human admissions officers. Simply feed in past classes or “idealized” classes and let the algorithm build such a class from the applicants. Colleges will take this approach because…

2) This decreases perceptions of bias by offloading human biases into the algorithm’s training (which leaves a lot more plausible deniability, regardless of the goals!)

3) The overall cost of running admissions, even with human oversight, will be substantially lower. And since we all know elite universities are just hedge funds with educational arms anyway…!

It’s an unsettled time for colleges and prospective students, and this post hasn’t even touched on issues like falling birth rates or the rise of alternative career pathways! But post-secondary institutions are going to have to wrestle with the impacts of ML just like the rest of us. In some situations there are clear right or wrong answers, but that’s not the case here. Would it hurt to put a robot in charge?

Schools-Over.com – Find High Value College Programs and Escape the Debt Traps

I last posted about a business idea for an automated college counselor, one which would guide students to make better college and career choices. I can now announce that Schools-Over.com has launched in beta, and attempts to deliver on that goal!

School’s Over currently provides two core features: a search feature for high-value degree programs, and a comparison tool enabling students to enter their current admissions offers to see which offers the best lifetime value*.

Much of the data for School’s Over comes from the Department of Education’s College Scorecard program, which has built a solid application for exploring the DOE’s newly released data on graduate salaries by college program. School’s Over uses this data and extends it by projecting salaries for the 70% of programs lacking salary data. School’s Over also projects total Lifetime Value for each degree, so that students know at a glance whether a college program is worthwhile, or whether it’s a debt trap.

With the beta launch we’ve taken an initial step toward providing automated guidance counseling – please try it out and give us your feedback (use the green feedback button onsite).

*Lifetime value for a college degree is defined as the NPV over a 45 year career, taking into account the cost of tuition, the opportunity cost of lost wages during college, and the net after-tax difference in wages realized by graduating from a particular college program versus simply going to work after high school. The discount rate used in the NPV calculations is the average federal student loan rate, currently just below 6%.