HR AI Bias AUDIT
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NYC Local Law 144
Fairly accelerates safe AI adoption by streamlining compliance processes for HR AI Bias Audits
Trusted by:
Key aspects of this law include:
- Bias Audits: Employers must conduct annual audits on their AI systems to check for bias, ensuring that the technology doesn’t discriminate based on race, gender, or other protected characteristics.
- Transparency: Employers must notify job applicants when AI is being used in the decision-making process and provide information on how the system works.
- Accountability: The AI system must comply with anti-discrimination laws, and companies must demonstrate that their AI tools are unbiased and fair.
New York City Local Law 144 refers to a law in New York City that governs the use of automated employment decision tools (AEDTs), such as AI systems, in hiring and promotion processes. The law mandates that any AI system used to make decisions about job applicants or employees must meet specific criteria to ensure fairness and transparency. In essence, the law seeks to prevent bias and discrimination in AI systems, ensuring that employment decisions are made in a just and equitable manner.
Under New York Local Law 144, HR professionals need to be mindful of how AI and automation can be used in recruitment and employment processes.
Companies in violations can be fined upto $10,000 a week.
Under New York Local Law 144, HR professionals need to be mindful of how AI and automation can be used in recruitment and employment processes.
Companies in violations can be fined upto $10,000 a week.
Contact us to find out how our award-winning AI-Compliance-in-a-Box with white-glove service can help you with your HR AI Bias Audit in the most secured data environments without IT overheads:
Additional Automated Employment Decision Tools (AEDTs) we audit :
Here are top HR use cases where AI or automation tools could be applied, and companies need to make sure they comply with NYC LL 144:
Resume Screening: AI-driven tools can automatically scan and filter resumes based on pre-set criteria such as skills, qualifications, and experience. This helps HR teams quickly identify the most relevant candidates without manual sorting.
Applicant Ranking and Matching: AI algorithms can rank candidates based on how well their profiles match the job description and requirements. This can save time by highlighting the best-fit candidates.
Video Interview Analysis: Some AI systems analyze video interviews, assessing verbal and non-verbal cues such as tone, facial expressions, and word choice to provide insights into candidates' emotional intelligence or other personality traits.
Performance Appraisals: AI tools can gather and analyze performance data over time, identifying trends in employee performance and providing insights into areas where improvement or recognition is needed.
Training and Development Recommendations: AI can analyze employee performance and skills gaps, recommending personalized training or development programs to help employees grow in their roles.
Retention and Turnover Prediction: AI-powered predictive analytics can analyze employee data to forecast potential turnover risks and suggest interventions to improve retention.
Resume Screening: AI-driven tools can automatically scan and filter resumes based on pre-set criteria such as skills, qualifications, and experience. This helps HR teams quickly identify the most relevant candidates without manual sorting.
Applicant Ranking and Matching: AI algorithms can rank candidates based on how well their profiles match the job description and requirements. This can save time by highlighting the best-fit candidates.
Video Interview Analysis: Some AI systems analyze video interviews, assessing verbal and non-verbal cues such as tone, facial expressions, and word choice to provide insights into candidates' emotional intelligence or other personality traits.
Performance Appraisals: AI tools can gather and analyze performance data over time, identifying trends in employee performance and providing insights into areas where improvement or recognition is needed.
Training and Development Recommendations: AI can analyze employee performance and skills gaps, recommending personalized training or development programs to help employees grow in their roles.
Retention and Turnover Prediction: AI-powered predictive analytics can analyze employee data to forecast potential turnover risks and suggest interventions to improve retention.
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