The U.S. Department of Defense has requested $30.3 million over five years to develop an upgraded lie detection system, according to budget documents. The initiative, known as «Polygraph+» or «Polygraph Next,» aims to modernize federal polygraph and credibility assessment technologies through artificial intelligence, machine learning scoring algorithms, and «standoff sensing»—a technique that captures physiological readings without physical contact with the subject.
The program would be managed by the Defense Counterintelligence and Security Agency (DCSA), which handles background checks for the federal government. According to the budget proposal, which Congress has not yet approved, the technology would be deployed for vetting job applicants and «insider threat detection.» Specific technologies remain unspecified, and the DCSA did not respond to requests for additional details.
This effort arrives amid heightened internal tensions at the Pentagon. Under Defense Secretary Pete Hegseth, the department has increasingly relied on polygraph examinations to identify sources of alleged media leaks. In September, the New York Times reported that staff members on the Joint Staff underwent polygraph tests following news coverage about depleted U.S. weapons stockpiles during the conflict with Iran.
Previous Pentagon initiatives may offer insight into the program’s direction. In 2023, the Defense Innovation Unit (DIU) launched an open solicitation for companies developing deception detection products. Two firms were selected: Presage Technologies, which claims its standard cameras can measure heart rate and breathing rate, and Altec Research, a medical sensor company expanding into non-contact sensing. A DIU-released video of Altec’s prototype shows it monitoring head movement, facial skin temperature, and pore activity. Neither company responded to comment requests, and the DIU declined to comment.
Polygraph technology has remained largely unchanged since its invention in the 1920s. Examiners measure blood pressure, pulse, respiration, and perspiration to assess truthfulness, comparing physiological responses between baseline questions («Is the sky blue?») and target questions («Have you ever committed a crime?»).
The federal government administers tens of thousands of polygraph tests annually for employee screening, yet the technology’s reliability has faced repeated scrutiny, and results are seldom admissible in court. In 1983, Congress’s Office of Technology Assessment found minimal evidence supporting polygraph use for employee screening. A 2003 National Research Council (NRC) report characterized the evidence for its effectiveness as «weak at best.»
Research suggests humans detect lies correctly just over 50% of the time without technical aids. The American Polygraph Association claims 80% to 94% accuracy, but the 2003 NRC report noted that even at this accuracy level, screening tests would generate substantial errors. With the Department of Defense employing 2.8 million people, an imperfect system at that scale could falsely accuse tens of thousands.
Additional concerns exist. Polygraph interpretations are frequently subjective, and racial minorities face higher likelihood of being judged deceptive. Furthermore, trained individuals can employ countermeasures to defeat the test—for instance, artificially increasing physiological responses to baseline questions by stepping on a hidden pin.
«If you know how it works, you can beat it,» says Sophie van der Zee, an associate professor studying deception at Erasmus University in Rotterdam. She notes the machine’s primary effect is deterrence—subjects often confess before testing begins. «But that only works if people think a polygraph works,» she adds.
Various alternative lie detection methods have been attempted over the years, including thermal cameras, pupil trackers, and brain scans. None have produced reliable results outside laboratory settings. The fundamental challenge persists: no single physiological indicator reliably signals deception across all individuals at all times. «There is still no Pinocchio’s nose,» van der Zee observes.
AI might theoretically improve detection by identifying patterns examiners cannot perceive. AI algorithms could also enable «multi-modal» deception detection, combining multiple measurements into an overall deception score that is harder to manipulate. According to van der Zee, three underlying processes occur during lying that detection attempts to capture: physiological stress, cognitive load, and conscious efforts to conceal deception. Current polygraph technology addresses only one of these.
«The more you can have combined methods that approach it from these three different angles, the more successful you will be,» van der Zee says. This concept isn’t new—in the 2000s, researchers at Manchester Metropolitan University in the UK created a system called Silent Talker that generated deception scores from video footage, later incorporated into iBorderCtrl, an EU-funded pilot program. In the U.S., a project called AVATAR combined eye tracking, voice analysis, and body movement detection for border crossing applications. All these initiatives quietly disappeared.
Kyri Kotsoglou, a legal scholar at Northumbria University in the UK who studies polygraph use in justice systems, calls combining AI with polygraphs «the worst of both worlds» because it introduces uncertainty atop invalidity. Even if AI or machine learning identifies previously unseen patterns in physiological data, reliably linking them to deception remains impossible without genuine ground truth.
«Even if you have all the records in the world from polygraph tests, you don’t know whether those polygraph tests are right or not,» says Marion Oswald, a law professor who has co-authored work with Kotsoglou on polygraph use in justice systems. She worries that new lie detection forms will, like the polygraph, serve more as psychological props than scientific instruments.
«It seems very much a response to the concern of the current administration to leaks and perceived lack of loyalty,» Oswald says. «[Lie detection is] being used as a threat, to intimidate and force people to confess to things, as opposed to anything that’s actually getting valid information.