Some dark-skin students getting ‘Unable to Identify Your Face’ messages while attempting to take online bar exam

Congrats soon-to-be graduates! Not even a once-in-a-century pandemic could stop you from finishing law school this year and move on to taking the all-important bar. However, there is one thing that may stand in your way of successfully taking the exam, and it has nothing to do with your study habits. 

It could be your skin color.

Some students with dark complexions are getting an error message when attempting to login to online bar exams that many states have adopted in the wake of COVID-19. One of the ways it is administered is by facial recognition. That prevents cheating. Your buddy can’t take it for you, unless he’s got one of those “Mission Impossible” masks … 

But a number are complaining that the technology is messing with their ability to take the test smoothly.  

Take Areeb Khan for example. The 27-year-old law student couldn’t login to his online portal to take a practice New York bar exam, he told the Thomas Reuters Foundation. Instead, he got a message that said, “Due to poor lighting we are unable to identify your face.”

Khan even went to his bathroom – it’s the brightest room in his apartment—but that didn’t help. Khan then wondered if it was his dark skin that was causing the issue with the test-proctoring platform.

“There are so many systematic barriers preventing people like me from obtaining these degrees — and this is just another example of that,” Khan told the new agency. 

He’s not alone. A number of test-takers went to Twitter to complain about the same thing when taking the test, which was held in a number of states in October. 

“The @ExamSoft software can't ‘recognize’ me due to ‘poor lighting’ even though I'm sitting in a well lit room. Starting to think it has nothing to do with lighting. Pretty sure we all predicted their facial recognition software wouldn't work for people of color,” tweeted Alivardi Khan.

Kiana Caton, a Black student, told the website Venturebeat that she planned to shine a light on her face while taking the bar — a tactic she learned from other dark-skinned students. She wasn’t thrilled with the idea, though.

“If someone has to shine a light in their face, they’re probably going to get a headache, or if they have sensitivity to light or are susceptible to migraines or anything like that it’s going to affect their performance, and that’s something I’m really concerned about,” Caton told the website. 

The ACLU of California had asked the Supreme Court of California not to allow the software because of the issue. It wrote: “Test-takers of color may be more likely to experience technical difficulties during the examination if facial recognition algorithms are unable to verify their identity.' 

The problem will likely continue. After all, the pandemic is surging and many states have already decided to continue with the online version come February. 

ExamSoft has strongly defended its system. “ExamSoft maintains a non-biased identification and exam delivery process to ensure that individuals of color are not disproportionately affected,” Nici Sandberg, a spokesperson, told Thomas Reuters Foundation. 

Facial recognition errors, or algorithmic bias, is nothing new. Wired.com has two reports—one from September 2017and another from July 2019—that both address the difficulty for facial recognition technology to identify Black people. 

The articles assert that robots, Google Photos, iPhones and other facial recognition technology have not been successful for years. 

It reported: “Facial-recognition software works by training algorithms with thousands, or preferably millions, of examples, and then testing the results. Researchers say the problematic facial-recognition systems likely were given too few Black faces and can only identify them under ideal lighting conditions.”

“There’s a big gulf between what this technology promises, and what it actually does on the ground,” Audrey Watters, a researcher on the edtech industry who runs the website Hack Education told the Thomas Reuters Foundation. “(They) assume everyone looks the same, takes tests the same way and responds to stressful situations in the same way.”