As used in this subchapter, the following terms have the following meanings:
Automated Employment Decision Tool. "Automated employment decision tool" or "AEDT" means "Automated employment decision tool" as defined by § 20-870 of the Code where the phrase "to substantially assist or replace discretionary decision making" means:
i. to rely solely on a simplified output (score, tag, classification, ranking, etc.), with no other factors considered; or
ii. to use a simplified output as one of a set of criteria where the simplified output is weighted more than any other criterion in the set; or
iii. to use a simplified output to overrule conclusions derived from other factors including human decision-making.
Bias Audit. "Bias audit" means "Bias audit" as defined by § 20-870 of the Code.
Candidate for Employment. "Candidate for employment" means a person who has applied for a specific employment position by submitting the necessary information or items in the format required by the employer or employment agency.
Category. "Category" means any component 1 category required to be reported by employers pursuant to subsection (c) of section 2000e-8 of title 42 of the United States Code as specified in part 1602.7 of title 29 of the Code of Federal Regulations, as designated on the Equal Employment Opportunity Commission Employer Information Report EEO-1.
Code. "Code" means the Administrative Code of the City of New York.
Distribution Date. "Distribution date" means the date the employer or employment agency began using a specific AEDT.
Employment Decision. "Employment decision" means "Employment decision" as defined by § 20-870
of the Code.
Historical data. "Historical data" means data collected during an employer or employment agency's use of an AEDT to assess candidates for employment or employees for promotion.
i. is or was involved in using, developing, or distributing the AEDT;
ii. at any point during the bias audit, has an employment relationship with an employer or employment agency that seeks to use or continue to use the AEDT or with a vendor that developed or distributes the AEDT; or
iii. at any point during the bias audit, has a direct financial interest or a material indirect financial interest in an employer or employment agency that seeks to use or continue to use the AEDT or in a vendor that developed or distributed the AEDT.
Impact Ratio. "Impact ratio" means either (1) the selection rate for a category divided by the selection rate of the most selected category or (2) the scoring rate for a category divided by the scoring rate for the highest scoring category.
Impact Ratio = | selection rate for a category |
selection rate of the most selected category | |
OR | |
Impact Ratio = | scoring rate for a category |
scoring rate of the highest scoring category | |
i. that generate a prediction, meaning an expected outcome for an observation, such as an assessment of a candidate's fit or likelihood of success, or that generate a classification, meaning an assignment of an observation to a group, such as categorizations based on skill sets or aptitude; and
ii. for which a computer at least in part identifies the inputs, the relative importance placed on those inputs, and, if applicable, other parameters for the models in order to improve the accuracy of the prediction or classification.
Scoring Rate. "Scoring Rate" means the rate at which individuals in a category receive a score above the sample's median score, where the score has been calculated by an AEDT.
Selection Rate. "Selection rate" means the rate at which individuals in a category are either selected to move forward in the hiring process or assigned a classification by an AEDT. Such rate may be calculated by dividing the number of individuals in the category moving forward or assigned a classification by the total number of individuals in the category who applied for a position or were considered for promotion.
Example: If 100 Hispanic women apply for a position and 40 are selected for an interview after use of an AEDT, the selection rate for Hispanic women is 40/100 or 40%.
Simplified output. "Simplified output" means a prediction or classification as specified in the definition for "machine learning, statistical modelling, data analytics, or artificial intelligence." A simplified output may take the form of a score (e.g., rating a candidate's estimated technical skills), tag or categorization (e.g., categorizing a candidate's resume based on key words, assigning a skill or trait to a candidate), recommendation (e.g., whether a candidate should be given an interview), or ranking (e.g., arranging a list of candidates based on how well their cover letters match the job description). It does not refer to the output from analytical tools that translate or transcribe existing text, e.g., convert a resume from a PDF or transcribe a video or audio interview.
Test data. "Test data" means data used to conduct a bias audit that is not historical data.
(Added City Record 4/6/2023, eff. 5/6/2023)