Policy
Your AI Exercise Became a Test the Day It Moved a Decision
An informal AI exercise becomes a selection procedure the first time it changes who advances, whatever it is called and whether or not anyone scores it. The Uniform Guidelines define a selection procedure as any measure, combination of measures, or procedure used as a basis for an employment decision, and the definition reaches informal or casual interviews by name [1]. Validation is the narrower duty. It attaches where the exercise produces adverse impact [1].
The takeThe instinct to keep the exercise informal runs exactly backwards. Formality is not what creates the obligation. Use is. An undocumented half hour carries every duty a written one carries, with none of the record that would answer for it. Writing down the task, the bar and what each finalist did is a short job for a manager, and it is the only version of the round anyone can defend, repeat or correct. Keep the exercise. Lose the informality.
Where Olive fits
Open a role and see what the work shows
Olive produces no composite, and no decision about a candidate is made by a machine alone: a person writes or edits each of the six findings, every finding carries the timestamped excerpt it rests on, and a released report exports with its rubric, scorer and bank versions attached. The candidate is granted the same report the employer reads.
Assess your shortlistWhen does an informal exercise become a selection procedure?
The first time it changes who advances. Federal selection law draws the line at use rather than at form. The Uniform Guidelines define a selection procedure as any measure, combination of measures, or procedure used as a basis for any employment decision, and name informal or casual interviews and unscored application forms inside the same definition 1.
Nothing in that sentence turns on a score, a vendor, an invoice or a name.
The Guidelines date to 1978, and the text cited here is the 2023 annual edition of the Code of Federal Regulations, revised as of July 1, 2023 1. They name no software and anticipated no chatbot. What the definition carries instead is a reach wide enough that a manager reading a finalist's prompt log over coffee sits inside it, on the same footing as a proctored aptitude test.
The belief that a test needs a vendor is not irrational. In many hiring stacks the word describes exactly that: an instrument somebody bought, with a score, a cut mark and an invoice. But the regulation predates all of it, and its category is wider than the market's.
So the question is not whether the exercise is formal enough to count. Ask instead whether a finalist has ever moved, or failed to move, because of how the half hour went.
One yes settles it, and the yes may be two rounds old by the time anybody asks.
What attaches the day it moves a decision?
The exercise should be job related. It should reach everyone at the same stage on the same terms. And it should leave enough of a record that somebody can say afterwards what was asked and what was seen. The definition cited here spells out none of those three, and none of them waits on a number. Validation is the fourth, and it is the one that does.
The number is adverse impact, and the Guidelines treat a selection procedure that produces it as discriminatory unless it has been validated 1.
Adverse impact is measured on rates, not on impressions. One paragraph of the Guidelines says a selection rate for any race, sex or ethnic group below four-fifths of the rate for the highest group will generally be regarded by federal enforcement agencies as evidence of it 2.
The same paragraph says smaller differences can still be adverse impact where they are significant in statistical and practical terms, and that larger ones may not be where the numbers are small and not statistically significant 2.
Reading four-fifths as a pass mark inverts the rule. The agencies that wrote the rule said in a 1979 interpretive document that the figure is not intended as a legal definition, but a practical means of keeping enforcement attention on serious discrepancies 3. Asked directly whether the Guidelines therefore tolerate up to 20 percent discrimination, they answered no.
One duty attaches with no arithmetic at all.
An applicant needs no legal vocabulary to request a reasonable accommodation. The EEOC's 2022 technical assistance on algorithms in assessment is guidance rather than law, and the agency took it off its site in January 2025, so it is read here from an Internet Archive capture. Under it, somebody who says a medical condition may make a test difficult to take has already requested one. Saying the phrase, or naming the statute, is not required 4.
An exercise nobody described in advance gives a candidate nothing to say that sentence about. The gap gets expensive when the tool the round bans is how someone manages a disability.
Does New York's tool rule reach a manager with a whiteboard?
No, and the mismatch is why the federal definition surprises people. New York City's Local Law 144 governs automated employment decision tools used on candidates in the city. Using one is barred unless a bias audit was run within the previous year, a summary of the results is posted publicly, and the candidate got notice at least 10 business days ahead 5.
The law took effect on January 1, 2023, and enforcement began that July 5 5.
A person running an exercise by hand triggers none of those duties. There is no tool, so there is nothing to audit and nothing to post.
Working out whether a tool counts as an automated employment decision tool is a live question for the software in the stack and a dead one for a manager with a document and an hour.
But the older rule never had a technology test in it. Teams that read the two together can take the wrong lesson: the city rule reaches a narrow class of software, and the 1978 definition reaches the conversation. An exercise can sit outside one and inside the other on the same afternoon.
An unwritten half hour carries every duty and no evidence
Every duty above already applies, and the record is the part of this a team controls most directly. An unwritten exercise is not outside the Guidelines. It sits inside them with no evidence of what was asked, what was observed, or whether the same thing happened twice, which is the position hardest to answer from.
Documentation does not create the obligation. It answers one.
Written anchors have also been associated with a better instrument, which is the part nobody expects.
Levashina and colleagues, reviewing the structured interview literature, report a meta-analysis by Taylor and Small covering 19 past-behavior interview studies 6. Interviews using anchored rating scales showed criterion-related validity of .35, against .26 for interviews without them. Agreement between raters moved less, .77 against .73.
The .35 and the .26 come from different studies rather than from one that ran both, so anchored scales travel with whatever else careful teams already do. The 19 studies covered past-behavior questions only, not work samples or take-homes.
California has made the testing record evidence in claims about automated decisions. The Civil Rights Council's final text on automated-decision systems makes evidence of anti-bias testing, or the lack of it, relevant to a claim that such a system discriminated and to any defense, down to the quality, recency and scope of the effort and the response to its results 7.
The same text stretches employment-records retention from two years to four 7.
The sharp edge points at inaction rather than at inquiry. Having looked, found a gap and done nothing counts against an employer under that language, and holding no record at all is no safe harbor either. Confirm current status and dates with employment counsel, because none of this is legal advice.
What can a manager say when a rejected finalist asks?
Only what was written down at the time. Writing it is a short job. Name the task and what it is supposed to show about the job. Name what a strong answer looks like and what a weak one looks like. Say who gets the exercise and at which stage. Say what gets written down afterwards, in every case, including the rounds that go well.
Consistency is the part that fails first. An exercise given to the two finalists a manager is unsure about, and skipped for the one they already liked, is a different test given to different people. The difference shows in the record whether or not anyone meant it that way.
Adding the exercise partway through a live pipeline raises the same question. Bringing back candidates who finished before the round existed is worth deciding before the next requisition opens rather than after.
Nothing in the four-fifths rule forces any of this. A finalist round holds too few people for a selection rate to mean much, and the Guidelines' own paragraph says larger gaps may not be adverse impact where the numbers are small and not statistically significant 2. On numbers that small a validation duty may never technically bite.
What shows up instead is a rejected finalist asking what the exercise was, and a manager who cannot say. Written down, the same half hour becomes a defensible assessment rather than a memory.
The half hour was always a test. What it leaves behind is decided this week, by the person who runs it next.
Common questions
Does an unscored exercise count as a test under federal law?
Yes. The Uniform Guidelines define a selection procedure as any measure, combination of measures, or procedure used as a basis for an employment decision, and the definition explicitly reaches informal or casual interviews and unscored application forms. Nothing in it turns on a score, a vendor or a name. A half-hour AI exercise run on finalists is inside that definition the first time it changes who advances. What is not automatic is the duty to validate, which the Guidelines attach where the procedure produces adverse impact.
When does the duty to validate actually apply?
Where the exercise produces adverse impact. The Uniform Guidelines treat a selection procedure with adverse impact as discriminatory unless it has been validated, and adverse impact is measured on selection rates rather than on impressions. A rate for any race, sex or ethnic group below four-fifths of the highest group's rate is what federal enforcement agencies generally regard as evidence of it. The same paragraph adds that smaller differences can still count, and larger ones may not, where the numbers are small and not statistically significant. At finalist stage the numbers usually are small, which is why the record matters more than the arithmetic.
Does New York City's Local Law 144 cover a manager-run exercise?
No. The city rule governs automated employment decision tools. It requires a bias audit within the prior year, a posted summary of the results, and notice to the candidate at least 10 business days before the tool is used. It took effect on January 1, 2023, with enforcement from July 5 that year. A person reading a finalist's work by hand is not a tool, so none of those duties attach. The federal definition of a selection procedure carries no technology test at all, which is how an exercise sits outside the city rule and inside the older one at the same time.
Can you give the exercise to some finalists and not others?
You can, and it is the fastest way to turn a useful exercise into a problem. An exercise given to the two finalists a manager is unsure about, and skipped for the one they already liked, is a different test given to different people. The difference is legible in the record whether or not anyone meant it. Pick the stage, give the exercise to everyone who reaches it, and write that rule down before the next round opens. Adding it partway through a live pipeline raises the same question about the candidates who finished before it existed.
What is the minimum record to keep on an informal AI exercise?
Five fields, and every one of them fits in a note in the system the team already runs. Record the task as given, what it is meant to show about the job, what a strong and a weak answer look like, who received it and at which stage, and what the reviewer observed each time. Keep the rounds that went well as fully as the ones that did not, since a file holding only rejections describes a decision nobody can re-read. California's automated-decision regulations stretch employment-records retention from two years to four, which is a reasonable floor to design against anywhere.
Does writing the criteria down increase legal exposure?
Ask employment counsel, and expect the answer to turn on where the employer sits. California's Civil Rights Council put in its final text on automated-decision systems that evidence of anti-bias testing, or the lack of it, bears on a claim that an automated-decision system discriminated and on any defense. The clause reaches the quality, recency and scope of the effort and the response to its results. The instinct runs backwards here: holding no record is no safe harbor, and having looked, found a gap and done nothing about it counts against the employer too.
References
- 1. 29 CFR Part 1607 - Uniform Guidelines on Employee Selection Procedures (1978), sections 1607.16(Q) and 1607.3(A) ✓ govinfo.gov Supports the definition of a selection procedure as any measure, combination of measures, or procedure used as a basis for any employment decision, its explicit reach to informal or casual interviews and unscored application forms, and the rule in 1607.3(A) that a procedure with adverse impact is considered discriminatory unless validated.
- 2. 29 CFR 1607.4 - Information on impact (Uniform Guidelines on Employee Selection Procedures, 1978) ✓ law.cornell.edu Supports the four-fifths selection-rate figure that federal enforcement agencies generally regard as evidence of adverse impact, and the same paragraph's caveats that smaller differences may still be adverse impact and larger ones may not be where the numbers are small and not statistically significant.
- 3. Questions and Answers to Clarify and Provide a Common Interpretation of the Uniform Guidelines on Employee Selection Procedures (Q.11, Q.19) ✓ eeoc.gov Supports the 1979 statement that the four-fifths figure is a rule of thumb not intended as a legal definition but a practical means of keeping enforcement attention on serious discrepancies, and the agencies' answer that the rule does not mean the Guidelines tolerate up to 20 percent discrimination.
- 4. The Americans with Disabilities Act and the Use of Software, Algorithms, and Artificial Intelligence to Assess Job Applicants and Employees ✓ web.archive.org Supports the claim that an applicant who says a medical condition may make a test difficult to take has thereby requested a reasonable accommodation, without needing to mention the ADA or use the phrase reasonable accommodation.
- 5. Automated Employment Decision Tools: Frequently Asked Questions ✓ nyc.gov Supports the Local Law 144 duties (a bias audit within the prior year, a publicly posted summary of results, and notice at least 10 business days before the tool is used), the January 1, 2023 effective date and the July 5, 2023 start of enforcement.
- 6. The Structured Employment Interview: Narrative and Quantitative Review of the Research Literature ✓ doi.org Supports the Taylor and Small meta-analysis of 19 past-behavior interview studies, in which interviews using anchored rating scales showed criterion-related validity of .35 against .26 and interrater reliability of .77 against .73.
- 7. Final Unmodified Text of Proposed Employment Regulations Regarding Automated-Decision Systems (Attachment B), 2 CCR sections 11009, 11013 ✓ calcivilrights.ca.gov Supports the clause making evidence, or the lack of evidence, of anti-bias testing relevant to a discrimination claim and to any defense, including the quality, recency and scope of the effort and the response to the results, and the extension of employment-records retention from two years to four.
7 sources, numbered by first appearance. Every one was opened and checked against the claim it carries. How Olive sources claims
General guidance, not legal advice. Hiring rules differ by state and country and change often; check anything here against your own counsel before you act on it.
Olive assesses how a person works with AI. It does not detect AI-written documents, and it never produces a score, a ranking, or a match percentage for a person. Candidates read the same report the employer reads.