8 Ways AI Outperforms Human Raters for Reliable Language Certification

AI seems to be on everyone’s minds these days. As more and more organizations adopt AI solutions for their processes and teams, the question on all of our minds is “What does artificial intelligence really mean? What can it really do, and will it replace human contribution?” 

While I can’t speak for every use case of AI, I can tell you that in Emmersion’s eyes, AI’s purpose is to enhance human contribution and help people do their jobs better. There are some things that humans should always do themselves—things like making complex decisions based on multiple factors, and developing personal connections with others.

 AI, on the other hand, can really help with repetitive, black-and-white, data-gathering roles. And when the two support each other, we know that you can experience much greater outcomes.

So when we talk about the language certification space, what advantages does AI contribute to the process? Here are seven things AI can do that humans can’t that make it a much better language screening solution:

1. AI can do the same thing over and over again, in the same way, indefinitely

Especially in large organizations hiring bilingual candidates, the constant need to evaluate language ability is so draining on internal teams. Language evaluation is difficult, time-consuming, and repetitive. It’s very challenging to create a system that can evaluate candidates’ skills in a consistent, regular cadence that large organizations need to get accurate, dependable results. 

Humans have a difficult time with repetitive tasks that need exacting, consistent attention because our performance depends on a lot of factors—our sleep, when we last ate, how tired we are, unconscious biases we carry toward other people, and other outside influences. We’re not really built to do the same thing over and over again the same way. It’s a strength in some ways, but not in language certification.

AI is good at performing repetitive tasks because that’s what it’s built to do, and it’s so needed in language ability testing. Any successful volume hiring initiative requires a lot of repetitive questioning and analysis to deliver dependable results. 

2. AI delivers bias-free results

As we mentioned before, one of the factors that contributes to inaccurate scores from human language evaluators is that humans carry unconscious biases. The Kirwin Institute at Ohio State University describes unconscious or “implicit” biases as pervasive attitudes that don’t necessarily align with our declared belief. Even people with “avowed commitments to impartiality” have unconscious biases—everyone does.

Even AI can be vulnerable to bias because it’s still created by humans. But taking the right measures to make sure it’s getting enough input and scoring the same way for every test no matter who it’s gives you essentially bias-free scoring—something that is so much harder for a human to achieve.

3. AI assessments are shorter than human interviews

Another thing AI can do that human interviewers can’t is make fast decisions about language ability. Like we said before, typical language interviews are usually around 30 minutes long. Our AI assessment is just 15 minutes—half as long. 

The reason AI is so successful at quickly assessing language ability is because it can do the elicitation (gathering information) and evaluation (scoring) work at the same time. 

To do language assessment best, humans should do those parts separately and after they’ve gotten some time and space from the language interview—that way, they can make a truly sound judgment with fewer outside influences. 

4. AI can multitask 

The best human-led language assessment interview will be focused on one candidate at a time to get the most accurate results possible. The length of human interviews vary, but they’re usually around 30 minutes long. So, in each 30-minute interview, one person is evaluated at a time by one other person. If you have a lot of candidates to assess and want to interview multiple people at a time, you’ll need to hire more humans to evaluate. 

As you hire, you’ll also need to keep in mind that your interviews can only go on during your employees’ work time and can’t happen during breaks, on days off, or when they’re unable to work. In short, you’re very limited by your interviewers’ schedules, and it’s tough to scale.

AI has no limits on the number of assessments it can administer at the same time. (When it’s built right, of course.) If you don’t factor in the time it takes to send assessments to test-takers (and many companies don’t have to when they’ve integrated assessment sends into their other processes), the impact that AI-driven assessments have on an organization’s time is essentially zero. 

5. AI is made to test remotely

Another thing AI can do that humans can’t is test language ability remotely, without any human involvement. AI doesn’t sleep or need to take any breaks—it works constantly, any time, and for an infinite number of people. 

Testers can take assessments on their own devices, too, since AI allows language assessments to be automated. It eliminates any scheduling difficulties interviewers have while trying to set up one-on-one meetings with a large number of applicants.

6. It can deliver instant scores

Another advantage of using AI is that it can score responses instantly. Some of our clients have used language testing with third-party sources that take days or weeks to interpret applicants’ input and score it. 

If AI is built well and made to interpret scores fast, it can deliver instant, actionable feedback that decision-makers can immediately access and take into account.

7. AI scales and improves calibration

Remember when we said humans aren’t great at doing the same thing, over and over again, in the same way? If you want to help your human language evaluators to score as consistently and accurately as possible, you’ll need to invest significant resources into calibration efforts.

Each individual person will need to “reset” their assessment methods and scoring criteria to stay in line with best practices and score as consistently as possible.

Calibration efforts start to multiply, though, if you’re hiring at scale and using many different people to evaluate language ability. Each person that needs individualized calibration will also need to be calibrated with everyone else on the scoring team. If consistency is your goal, you have to make sure everyone is aligned.

But once AI is calibrated, you don’t have to worry about it anymore. In fact, it can continue to learn and incorporate input into the algorithms it uses to score raw data. It continues to perform at its best while getting better and better at what it does all the time.

8. AI does a great job at keeping track of data 

Another thing AI is made to do better than humans is keep track of test-taker data. And, because AI allows you to know your results are accurate and objective, that data is so much more useful to you in making decisions and improving your performance. 

One of the things you can do with more and better data is hone in on your thresholds and language ability cut-off points for hiring and advancement. It also lets you communicate your employees’ language ability to your clients clearly and from a reliable, third-party perspective. 

Conclusion

If you can’t tell already, we really believe that AI is best at language testing, especially for volume hiring. When it comes to humans and AI, there are definitely strengths and weaknesses of both. But when you can use humans for what they’re best at and AI for what it’s best at, you can really get the best results. 

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