Efficiency measures

In a profession with decision-making at its heart, determining how to use AI tools touches on delicate questions about which skills and tasks need to remain human.

While that ‘augment, not replace’ mindset towards the use of AI tools in admissions seems to still be prevalent, there are some concerns to be addressed. And, perhaps, some myths to be dispelled.

Rick Clark, Executive Director, Strategic Student Access at Georgia Institute of Technology, says that, in his experience, students and families are concerned and usually think that AI is used far more than it actually is. The scary narrative, he says, is that institutions are going to let algorithms make their admissions decisions with no human checks.

“Of course, I think that that would not be appropriate,” he explains.

“[But] that's not happening.”

What is most commonly happening at the moment is that institutions are starting to use AI to help with time-consuming tasks and exploit its data analysis power.

Institutions with an admissions process requiring essays and letters of recommendation, Clark explains, are using AI to pull out summaries and produce bullet points, while other institutions with a more formulaic type of process use AI to analyse the numbers, with staff members checking the results. “That’s obviously an efficiency measure,” he says.

Some parts of the process lend themselves better than others to the use of AI tools. For holistic admissions, Blessing explains, AI tools can be useful for data processing but less so for other tasks.

“If there are systems that use an admissions officer’s perspective or judgement of the context, if they put a lot more emphasis on letters of recommendations and support, or they are measuring things like engagement, then it’s really hard to integrate AI,” she explains.

At ESCP Business School in France, AI helps with logistics, the school’s European Associate Director for Admissions and Business Development Muriel Grandjean explains. During the institution’s recruitment examination process, AI tools are used to put together jury panels by taking into account the availability of faculty, staff and alumni and providing a balanced group of representatives.

Grandjean explains that her team spends a long time on the organisation of the jury panel, with one staff member dedicated to it. “She could be looking at the big Excel file and trying to come up with jury panels from it, but the AI can do it in 10 seconds, and then we review the output. This means she can spend more time on quality tasks – such as liaising with jury panel members,” she explains.

The institution, Grandjean adds, is exploring a collaboration with OpenAI to simplify tedious tasks such as verifying documents, checking test scores and detecting AI-generated content.

Predicting success

Blessing’s colleague Katie Burns, a College Admissions Counsellor with IvyWise, says she has observed that more companies supporting the admissions and enrolment process are launching tools to help institutions track the student journey from application to graduation.

“Using AI tools to understand a student's profile, finding correlations between what their application file looked like and how they performed at the school, can help admissions officers inform decisions,” she says.

This system, Burns explains, could identify qualities that are correlated to student success in applicants who did not fit the preferred student profile, helping institutions find more of what she calls “diamonds in the rough”.

This is something Clark also thinks is going to become more common, as institutions use the data analysis power of AI to build student profiles to make more informed admissions decisions and provide targeted support to students.

“Let’s say we went to the same high school, and I am two years older than you,” he explains.

“I am now studying at Georgia Tech. What my academic preparation and profile looked like, and how I'm performing, are some of the best possible predictors of how you will also perform.”

When asked whether there could be potential risk for profiling to be misused and schools recruiting the same type of student with "successful characteristics", Clark says that it is possible.

“There could be misuse or abuse of any number that is already occurring with the data we currently have. But I also see some real benefits for those institutions trying to have a more balanced class,” he adds.

“I see this helping us to say, ‘All right, here's a student who does fall outside of our highest profile, but we also have great confidence in their ability to make it if we put the right things in place for them.”

Insights

At IÉSEG School of Management in France, AI features in the asynchronous video interview international applicants are required to undertake.

Doing the interview on camera, students have approximately five to six questions tailored to the programme, one minute to read each question, and about one and a half minutes to reply, the institution’s Head of International Recruitment, Promotion and Admissions Emilie Largosse tells QS Insights Magazine.

“We are not looking for standardised or well-prepared questions. We tell candidates that we want a natural conversation. We want to see the candidate’s personality,” Lagorsse explains.

The system flags up when candidates are speaking too fast, as if they were reciting a text or reading from the screen. But this is not the most important role AI plays in the interview.

“The system is equipped with what we call ‘insights’,” Lagorsse says.

“This means that if an applicant is speaking for more than five minutes, the system is able to identify the five OCEAN traits according to the vocabulary they use.”

“The candidates don’t know about this personality test,” she adds.

OCEAN stands for openness, conscientiousness, extraversion, agreeableness and neuroticism, commonly known as the Big Five personality traits. The model has been widely researched, and, while it has received some criticism, such as oversimplifying personality, the potential for cultural bias is the basis of personality tests commonly used in a range of sectors, including research and human resources.

The video interviews, Lagorsse explains, are reviewed by human eyes. Asked if staff members ever disagreed with the AI’s perspective on a candidate’s personality, Lagorsse says that it hasn’t happened yet.

Applicants, she adds, value the flexibility of being able to record the interview at their own convenience, while the members of the admissions team now have more time for other tasks, including dedicated slots for students to book meetings and ask questions.

No time for experiments

Not every institution uses AI tools in admissions, and definitely not to the same extent.

Privacy, discrimination, bias and losing the personal touch are usually the main concerns around using AI in admissions, according to Dr Tamim Elbasha, Associate Dean – Learning and Quality Development at Audencia Business School in France.

Dr Elbasha, who explains that his institution has not experimented with AI in admissions yet, also adds that, in the sector, sometimes pressure works against innovation.

“I think people under pressure try to do their best, exploiting what they have to get better results, and have less time for exploration and experimenting with something new,” he says.

He explains that AI could be used more to spot missing translations, summarise large documents, and help candidates fill out forms, keeping admissions decisions to humans. This could take away some of the ethical concerns, he says, as AI tools would only summarise factual documents with no judgment involved.

Other challenges to implementing AI tools, according to the interviewees, include costs, the availability of technology, and the fact that the higher education sector is notoriously slow to move. In some instances, though, limiting AI use is also a conscious decision to ensure communication remains human and students receive quality responses.

“It’s easy to ask ChatGPT to help answer an email – but then I am thinking: is it really me answering?” Grandjean says.

The automation of certain tasks may also make the process more impersonal and harder to navigate for students.

A lot of colleges, Blessing explains, may have students enter their grades or classes in the system. A small mistake – such as putting a poetry class under performing arts instead of English – could go unnoticed and be harder to fix.

“That’s the only place where I may just say to students: ‘slow down, because a human would catch poetry may not be a performing arts class, but that first pass may be done by non-human eyes’,” she says.

“Many things feel automated – think about the bots answering questions on websites. Sometimes, it’s tougher to find someone to help you troubleshoot in case you make a mistake.”