If you have ever taken a personality test as part of a job application, you have probably wondered: what are they actually looking for? And if you knew what they were looking for, could you just answer accordingly?
The honest answer to the first question is: yes, there are patterns employers tend to prefer — higher Conscientiousness, moderate to high Extraversion for many roles, lower Neuroticism. The honest answer to the second is more complicated.
This article reviews what the scientific literature actually says about faking on personality tests, how much it happens, whether it matters for predictive validity, and what it tells us about the appropriate use of personality assessment.
Can People Fake Personality Tests? Yes — When Instructed
The fakeability research is unambiguous on one point: when people are explicitly instructed to present themselves as ideal candidates, they can and do shift their scores substantially. Studies using "fake good" instructions — where participants are told to imagine they are applying for a desirable job and answer accordingly — consistently show that mean scores on Conscientiousness, Emotional Stability (low Neuroticism), and Extraversion increase by around half a standard deviation or more.
This is not surprising. The social desirability bias — the tendency to answer questions in ways that present a favourable social image — is one of the best-documented phenomena in survey research. Personality tests are not immune to it. For a broader treatment of how assessment context shapes scores, see anonymity in personality assessment: why it matters.
"Motivated faking on personality inventories can result in mean-score elevations of approximately one-half to one standard deviation on most Big Five scales."
— Viswesvaran & Ones (1999), Human Performance
How Much Faking Actually Happens in Real Hiring Contexts
Here is where the picture becomes more nuanced. The laboratory evidence for faking under instruction is robust. The evidence for spontaneous, uninstructed faking in actual hiring contexts is weaker.
Several studies have compared personality scores collected in applicant contexts (where people have reason to fake) with scores collected in research contexts (where they do not). The differences are real but smaller than the instructed-faking studies suggest — typically around one-quarter to one-third of a standard deviation on the most fakeable scales.
Some researchers argue this remaining gap is mostly attributable to self-deception rather than deliberate distortion: applicants genuinely believe they possess the traits they claim, because motivated reasoning leads them to inflate their self-assessments in positive directions. This is a different phenomenon from cynical faking, and it has different implications for what to do about it. It also connects to the broader evidence on why self-assessment alone produces an incomplete picture — we are systematically unreliable narrators of our own personalities.
Does Faking Actually Damage Predictive Validity?
This is the key empirical question, and the answer is genuinely contested. There are three main positions in the literature:
Position 1: Faking doesn't matter much. Some meta-analyses have found that personality tests show similar predictive validity for job performance regardless of whether the assessment context was applicant or research. If fakers end up performing just as well on the job, the faking hasn't corrupted the predictive signal.
Position 2: Faking reduces validity. Other research argues that when high scorers are a mixture of genuinely high-trait individuals and skilled fakers, the predictive relationship with performance is attenuated. The fakers inflate the distribution without having the underlying trait.
Position 3: Faking selects for impression management. A third perspective notes that the ability to fake a personality test successfully may itself be a meaningful signal — specifically, it correlates with social intelligence and the motivation to impress. People who fake effectively may actually perform well in roles where impression management matters. This does not make faking unproblematic, but it complicates the simple validity-corruption story.
The current scientific consensus leans toward Position 1 for low-stakes, non-selection uses, and toward Position 2 for high-stakes selection contexts where the incentive to fake is highest. For what "valid" actually means in personality measurement, see what is reliability and validity in personality testing?.
Forced-Choice Formats: A Partial Solution to Test Faking
One technical response to faking is the forced-choice format, in which respondents choose between two or more equally socially desirable options (e.g., "I tend to be very organised" vs. "I tend to be very sociable"). By removing the easy option of endorsing all positive descriptors, forced-choice formats reduce the opportunity for response inflation.
The evidence on forced-choice formats is generally positive: they produce less faking and, in some studies, slightly better predictive validity. But they are harder to take, more cognitively demanding, and less well-validated in cross-cultural contexts. They also introduce ipsative scoring problems (the scores are relative to each other, not absolute) that complicate interpretation. For a detailed treatment of the tradeoffs, see forced-choice personality assessment: more honest data.
| Test format | Susceptibility to faking | What to do |
|---|---|---|
| Standard Likert-scale Big Five | High — easy to endorse positive items | Use for development; monitor if used in selection |
| Forced-choice (e.g., Thurstonian IRT) | Moderate — harder to fake but not immune | Better for selection contexts; validate locally |
| Situational judgement tests (SJTs) | Moderate — less transparent but still fakeable | Combine with personality data for better coverage |
| Peer/multi-rater assessment (e.g., Cèrcol Witnesses) | Low — others are harder to game | Most resistant to intentional faking |
| Anonymous self-report (no high-stakes context) | Low — reduced motivation to distort | Best for development; the ideal context for honest data |
See also: social desirability bias in personality tests.
Why the Real Problem Is Using Personality Tests for Selection
Most of the faking debate is actually a proxy debate about whether personality tests should be used for hiring selection at all. If you use personality data for development — to help people understand themselves and work better with others — faking is largely self-defeating. If you fake your way to a development report that doesn't reflect how you actually behave, you will simply get feedback that is less useful to you. The cost falls on the person who faked, not on the organisation.
If you use personality data as a selection hurdle — as a gate that determines whether you proceed in a hiring process — the incentive to fake becomes significant, and the consequences of faking fall on the organisation (in the form of mis-selected hires) and on honest candidates who are disadvantaged relative to skilled fakers. The ethical and legal dimensions of this are examined in personality testing in hiring: what is legal and what is ethical.
This is the most important practical insight from the faking literature: the fakeability problem is downstream of the misuse problem. Personality assessment was designed for development and self-understanding. When it is repurposed as a selection screen, it develops fakeability vulnerabilities that it was never designed to resist.
Why Anonymous, Developmental Assessment Resists Faking
One practical response to faking concerns is to collect personality data anonymously — that is, in contexts where the data will not be seen by hiring managers, and where no individual's scores are linked to employment decisions. This is exactly the context in which personality assessment generates its most valid and useful signal.
Anonymous assessments eliminate the primary motivation for faking. They produce data that is more accurate and more useful for development. They also eliminate the legal and ethical risks associated with using personality data in selection.
Cèrcol uses a multi-rater design in which Witnesses provide an external view of a person's behaviour. This adds a layer of information that is substantially harder to fake than self-report: while you can inflate your own scores on Conscientiousness, you cannot easily manipulate how five colleagues who work with you every day describe your typical behaviour. The science behind the IPIP — International Personality Item Pool that underpins the Witness instrument gives it validated, open-source foundations that commercial tools frequently lack.
The faking literature ultimately teaches us less about how to make personality tests more tamper-resistant and more about where they genuinely belong: in development, in team dialogue, in self-understanding. That is where they deliver their most honest and most useful signal.
How Cèrcol addresses faking
Cèrcol's design responds directly to the faking problem at every level. The Witness peer assessment means that your personality profile is not constructed from your own self-presentation — it is built from how the people who work with you actually describe your behaviour. Witnesses answer forced-choice adjective pairs anonymously, which removes both the ability to fake (no obviously "correct" answer) and the incentive (no stakes attached to their individual responses). The self-report component is taken in a low-stakes, individually owned context — you own your data and decide who sees it — which research shows substantially reduces impression management. You can explore the full instrument at /instruments and read about the underlying science at /science. The assessment is free at cercol.team.
Further reading
- Social desirability bias in personality tests
- Forced-choice personality assessment: getting more honest data
- Why self-assessment alone isn't enough: the case for peer personality feedback
- Anonymity in personality assessment: why it matters
- Personality testing in hiring: what is legal and what is ethical?
- What is reliability and validity in personality testing?