ai is taking over the job market.
That is the thesis of the new book. The Algorithm: How ai Decides Who Gets Hired, Monitored, Promoted, and Fired—and Why We Should Fight Back by Hilke Schellmann, Emmy Award-winning investigative reporter and contributor to The Wall Street Journal and The Guardian, as well as an assistant professor of journalism at New York University.
In the book, Schellmann tells how large companies are increasingly turning to ai to scan resumes, evaluate video interviews and predict the success of candidates or employees through games that do not always have a clear connection to work.
This is all a problem, Schellmann tells tech & Learning, because the decisions made by ai systems can be arbitrary, unfair, and sometimes blatantly biased against certain types of applicants. And students preparing to enter the job market need to know how to navigate the changing hiring landscape.
Schellmann offers tips and techniques you can use to help prepare your students to stand out to ai recruiters and overcome some of the problems associated with the growing ai job market.
“Job platforms like LinkedIn, Monster, ZipRecruiter, and Indeed have really tried to democratize hiring and have done so; many of us can apply for many jobs,” Schellmann says. “That has led to many companies getting “There are many applications for a position. “We see large companies like Google receiving around 3 million requests a year.”
And it's not just a tech giant like Google that faces this challenge. Anyone who has ever served on a hiring committee knows that any semi-desirable position will receive at least dozens of applications, many of them from candidates who apparently meet none of the requirements for the position.
“Many companies are simply overwhelmed by the number of applications,” says Schellmann. “So they're looking for a technology solution and vendors come in and say, 'These tools will make hiring more efficient.' We're going to save a lot of money, they're not going to be biased, and they're going to choose the most qualified candidates.”
These ai detection tools increase efficiency and save money, but the vendors' other claims may be more dubious, Schellmann says. “Are they impartial? That is certainly not true. And do they choose the most qualified candidates? “We don't have much evidence that it's true.”
<h2 id="problems-with-ai-bias-xa0″>Problems with ai bias
Bias can be built into ai algorithms in subtle and unintentional ways which can have devastating consequences. An employment lawyer Schellmann interviewed for the book found a resume filter that gave more points to people who mentioned baseball on their resume and fewer points to those who mentioned softball.
“That's probably a case of gender discrimination,” Schellmann says, since more men would be expected to include baseball on their resume and more women would be expected to include softball. What likely happened in that case is that the ai tool was trained on the resumes of former company employees.
“There may have been a historical bias at the company, they may have hired more men than women in the past,” he says. Therefore, it is possible that the ai saw more mentions of baseball and inferred, wrongly, that those who had baseball on their resume were better employees.
As bad as bias is in individuals, ai bias has the potential to be much worse. “The problem with resume screeners, or with many ai tools, is that their reach is unprecedented,” Schellmann says. “A human hiring manager can only discriminate against a certain number of people, and I feel very sorry for them, but an artificial intelligence tool can discriminate against millions of people.”
<h2 id="overcoming-ai-hiring-algorithms”>Overcome ai hiring algorithms
To differentiate yourself from ai algorithms when you or your students apply for jobs, Schellmann suggests:
- Keep your resume simple. Forget the old advice about making your resume stand out; Now the opposite is true: you want it to be in a format that the ai already understands. “Use short, crisp, clear sentences,” says Schellmann. Images, multiple columns, or other design embellishments should be avoided.
- List skills separately. Many ai tools scan resumes for specific skills, so applicants should create a separate section that lists their skills clearly with bullet points. This helps ensure that the algorithm “ingests its skills correctly,” Schellmann says.
- Quantify whenever possible. “Anything you can quantify, quantify, rather than just describe, is really useful to machines,” Schellmann says.
- Use technology to evaluate your resume before you submit it. Schellmann recommends using a tool like Jobscan, which allows job seekers to enter their resume and the job description they are seeking and compare similarities. “You always try to use the keywords that are in the job description, but make sure they are not 100%,” says Schellmann. Instead, he wants an overlap of between 60 and 80%. “Because if it's 100% the same words, some resume evaluators will infer that it's just a copy of the job description,” she says.
- Get close to a person. If you can know the name of the person in charge of recruiting for that position, it may be worth sending them a short message on LinkedIn. This guarantees that a human will see her resume. This is important for the reasons laid out in this article and described in more detail in Schellmann's book. “It's hard to understand how machines will treat your resume,” he says.
The Algorithm: How ai Decides Who Gets Hired, Monitored, Promoted, and Fired—and Why We Should Fight Back It is available on Amazon.
