Proctoring software like Honorlock that track students' movements during online exams to prevent cheating are criticized for allegedly flagging normal behavior
An unsettling glimpse at the digitization of education. — Give this article- - - Read in app Tweets: @zeynep , @random_walker , @hypervisible , @nytimestech , @_aloisi , @pt , @evanselinger , @autumm , @dealbook , @nytimesbusiness , and @nytimestech Tweets: @zeynep : Always read @kashhill. Many institutions use automated surveillance to decide if a student is cheating on tests as part of remote learning. Often, this means a clunky, unaccountable algorithm barely overseen by low-paid workers abroad has great power. https://www.nytimes.com/... Arvind Narayanan / @random_walker : A recurring pattern in AI that judges people: -The vendor markets it as a one-stop solution to win clients. -But the fine print puts responsibility for oversight on the client (company/school/gov't). -When the tool inevitably makes mistakes, both parties say it's not their fault. https://twitter.com/... https://twitter.com/... @hypervisible : So many important elements in this NYT story, but two I want to highlight: Students not only have this system used against them, they are also used as data to “improve” the tech. Not a new thing, but it's always invasive and gross. https://www.nytimes.com/... https://twitter.com/... @nytimestech : Despite widespread criticism, online proctoring software is still used at many schools around the country. When this student in Florida was accused of cheating by an A.I. monitoring tool and a professor she had never met, her experience was Kafkaesque. https://www.nytimes.com/... Antonio Aloisi / @_aloisi : The pandemic was a boom time for companies that remotely monitor test takers bringing #surveillance into academic settings. Some have been frustrated by the invasiveness, glitches, false allegations of cheating & failure to work equally well for all people https://www.nytimes.com/... Parker / @pt : I, for one, an outraged that software to detect cheating would be improved by using example data in which humans determine students are cheating. https://twitter.com/... Evan Selinger / @evanselinger : “Normal behaviors are punished by this software.” Except that what counts as abnormal appears to be basic human stuff, the embodied cognition of moving your head + hands to think & remember. Great reporting from @kashhill. https://www.nytimes.com/... @autumm : “I try to become like a mannequin during tests now,” Hey #edtech, what exactly are you teaching? https://www.nytimes.com/... @dealbook : “Schools seem to be treating it as the word of God,” Cooper Quintin of the @EFF said about anti-cheating software. “If the computer says you're cheating, you must be cheating.” https://www.nytimes.com/... @nytimesbusiness : The software said she might have cheated during her biology exam. The professor she'd never met agreed. The video showed her looking down. She said she was just thinking. How does someone prove they are innocent when the video is ambiguous? https://www.nytimes.com/... @nytimestech : The software said she might have cheated during her biology exam. The professor she'd never met agreed. The video showed her looking down. She said she was just thinking. @kashhill reports on how sideways anti-cheating software can go. https://www.nytimes.com/...
Context & Ripple Effects
Remote-exam monitoring had already spread during the pandemic, bringing privacy and security complaints over services such as Examity's online proctoring tools. The category's methods included facial detection, eye tracking, mouse clicks and room scans, turning routine test-taking into a stream of potential risk signals for exam-monitoring systems.
The allegations against Honorlock arrive after Proctorio's client list grew despite complaints, lawsuits, bias accusations and pushback from top universities against its proctoring practices. They sharpen the core problem for providers and schools: flags intended to verify exam integrity can also make ordinary student conduct consequential.
First-order effects
- Students using Honorlock and similar services face the immediate risk that normal movements are treated as suspicious during online exams.
- Honorlock and peer providers face renewed criticism over how their systems distinguish cheating indicators from ordinary behavior.
Second-order effects
- Universities relying on remote proctoring face greater pressure to examine whether flagged behavior is reviewed fairly, adding to the complaints and institutional pushback already documented around Proctorio.
- Vendors using broad behavioral monitoring must compete not only on cheating detection but on the credibility of the review process behind their flags.
Third-order effects
- If such allegations persist, education technology will face a durable verification bottleneck: institutions will need to reconcile scalable remote assessment with systems that can justify consequential flags to students.
- The pattern points to student surveillance becoming embedded beyond single exams, as later coverage of a California college connected e-proctoring with broader student data-collection tools.
The trend: Remote education is shifting from simple online testing toward behavioral surveillance systems whose legitimacy depends on accountable verification, not merely more data collection.