Currently the rules for the EU AI Act are not finalized and no organization can obtain a Conformity Assessment. However, many of the required elements of a these Conformity Assessments are publicly available and BABL AI can help organizations prepare for a Conformity Assessment by preforming an EU AI Act Conformity Assessment Preparation Audit.

The EU Artificial Intelligence Act proposes a comprehensive framework for categorizing and overseeing artificial intelligence applications according to their potential for harm. This framework predominantly comprises three key classifications: prohibited practices, high-risk AI systems, and other AI applications. High-risk AI systems, as defined by the Act, encompass those presenting substantial risks to public health, safety, or fundamental human rights. Prior to market release, they necessitate a mandatory compliance evaluation, which the provider must perform through self-assessment.

The process of conformity assessment demonstrates to the public that an AI System meets the relevant requirements of the EU AI Act. 

At the moment the final rules for a Conformity Assessment have not been finalized. This audit process is to help your organization be fully prepared for a Conformity Assessment when the rules have been finalized.

As defined in the EU AI Act, high-risk systems are those that present substantial risks to public health, safety, or fundamental human rights. These systems include but not limited to:

• Biometric identification and categorization of natural persons
• Management and operation of critical infrastructure
• Education and vocational training
• Employment, workers management, and access to self-employment
• Access to and enjoyment of essential private service, and public services and benefits
• Law enforcement
• Migration, asylum, and border control management
• Administration of justice and democratic processes

This regulation is applicable to AI system stakeholders whose products are available in the EU market or impact individuals within the EU, irrespective of their organizational type, whether public or private, and whether they operate within or outside the EU. The regulation outlines specific obligations for these stakeholders:

• Providers: These are the ones who create an AI system or have someone make it for them. They sell it with their own name or brand.
• Importers: These are the ones who bring AI systems from outside the EU and sell them in the EU using the original name or brand.
• Distributors: These are the ones who sell AI systems in the EU market without changing them in any way. They are not the creators or importers.
• Users: These are the people or organizations that use AI systems, but not for personal, non-professional use.

Each role has its own responsibilities under the regulation.
Note: Providers, such as the developer of a candidate screening tool, bear different obligations from users, such as a bank procuring this screening tool.

Legals requirements pertaining to providers include areas such as:

• Quality management system
• Risk management system
• Data governance
• Technical documentation and transparency
• Human oversight
• Post-market monitoring system, among others

The New York City Bias Audit Law (Local Law 144) governs the use of automated hiring tools (AEDT) in New York City. It mandates that algorithm-based recruiting, hiring, or  promotion technologies must undergo an annual bias audit from an independent third-party auditor before they can be used for candidates and employees.

AEDT stands for "Automated Employment Decision Tool." It refers to software or systems that use algorithms and automation to assist in various aspects of the employment process, such as recruiting, hiring, or promoting employees. AEDTs can be used for tasks like screening resumes, conducting initial candidate assessments, or identifying potential candidates for job openings.

New York City Local Law 144, also known as the Bias Audit Law, affects employers of all sizes within New York City that use automated employment decision tools (AEDTs) for recruiting, hiring, or promoting candidates and employees.

The NYC Bias Law states that an AEDT is “any computational process, derived from machine learning, statistical modeling, data analytics, or artificial intelligence, that issues simplified output, including a score, classification, or recommendation, that is used to substantially assist or replace discretionary decision making for making employment decisions that impact natural persons.”

This includes but is not limited to: Applicant Tracking Systems (ATS), Pre-employment Assessment Software, Chatbots for Initial Screening, Resume Screening Algorithm, Video Interview Platforms.

We transparently provide all legally required information, along with essential context to comprehend the audit opinion and summary of results. Furthermore, we openly disclose our audit criteria and methodology, offering maximal transparency while safeguarding the intellectual property of the audited organization.

On average our audits take between 2-3 weeks to complete after all relevant documentation has been submitted. This timeframe can vary depending on many circumstances like readiness and resubmission of unsatisfactory documentation, but BABL AI will help you at every stage to ensure an easy process.

In addition to ensuring compliance with emerging regulations such as New York City Local Law 144, an algorithmic audit serves as a powerful tool for reassuring your stakeholders that your algorithms undergo vigilant bias monitoring and testing. This proactive approach helps mitigate potential risks posed by your systems while significantly enhancing transparency, ultimately fostering greater trust in your AI systems.

Absolutely! Our audit process is highly adaptable to cater to your unique compliance and assurance requirements. Feel free to get in touch with us and have a conversation with one of our expert auditors to discover the full spectrum of solutions BABL AI can offer.

The AI Risk Management Framework (AI RMF) is a comprehensive guide designed to enhance trustworthiness in AI product design, development, and application. This voluntary framework is meant to integrate trust factors into your AI services and systems, ensuring they meet the highest standards of evaluation and performance.

The AI Risk Management Framework offers a versatile solution for businesses and organizations across all industries and sizes to initiate or improve their strategies for managing AI risks. It provides an innovative method for embedding responsible AI practices within their operations.

BABL AI’s NIST AI Risk Management Framework Audit is an easy way to implement this framework into your organization.

BABL AI can help your organization apply the NIST AI Risk Management Framework with our experienced Audit experts.

The AI Risk Management Framework (AI RMF) is a comprehensive guide designed to enhance trustworthiness in AI product design, development, and application. This voluntary framework is meant to integrate trust factors into your AI services and systems, ensuring they meet the highest standards of evaluation and performance.

The AI Risk Management Framework offers a versatile solution for businesses and organizations across all industries and sizes to initiate or improve their strategies for managing AI risks. It provides an innovative method for embedding responsible AI practices within their operations.

BABL AI’s NIST AI Risk Management Framework Audit is an easy way to implement this framework into your organization.

BABL AI can help your organization apply the NIST AI Risk Management Framework with our experienced Audit experts.

In addition to ensuring compliance with emerging regulations such as New York City Local Law 144 or the EU AI Act, an algorithmic audit serves as a powerful tool for reassuring your stakeholders that your algorithms undergo vigilant bias monitoring and testing. This proactive approach helps mitigate potential risks posed by your systems while significantly enhancing transparency, ultimately fostering greater trust in your AI systems.

We transparently provide all legally required information, along with essential context to comprehend the audit opinion and summary of results. Furthermore, we openly disclose our audit criteria and methodology, offering maximal transparency while safeguarding the intellectual property of the audited organization.

The Digital Services Act (DSA) governs the responsibilities of digital service providers that serve as intermediaries, facilitating connections between consumers and goods, services, and content, encompassing platforms like online marketplaces. It establishes a robust framework for transparency and accountability among online platforms, creating a unified regulatory structure across the European Union.

Under the Digital Services Act, the European Union classifies online platforms and search engines as entities with 45 million or more monthly users that operate within the EU.

Absolutely! Our audit process is highly adaptable to cater to your unique compliance and assurance requirements. Feel free to get in touch with us and have a conversation with one of our expert auditors to discover the full spectrum of solutions BABL AI can offer.

In addition to ensuring compliance with emerging regulations such as New York City Local Law 144, an algorithmic audit serves as a powerful tool for reassuring your stakeholders that your algorithms undergo vigilant bias monitoring and testing. This proactive approach helps mitigate potential risks posed by your systems while significantly enhancing transparency, ultimately fostering greater trust in your AI systems.

We transparently provide all legally required information, along with essential context to comprehend the audit opinion and summary of results. Furthermore, we openly disclose our audit criteria and methodology, offering maximal transparency while safeguarding the intellectual property of the audited organization.

On average our audits take between 2-3 weeks to complete after all relevant documentation has been submitted. This timeframe can vary depending on many circumstances like readiness and resubmission of unsatisfactory documentation, but BABL AI will help you at every stage to ensure an easy process.

Absolutely! Our audit process is highly adaptable to cater to your unique compliance and assurance requirements. Feel free to get in touch with us and have a conversation with one of our expert auditors to discover the full spectrum of solutions BABL AI can offer.

In addition to ensuring compliance with emerging regulations such as New York City Local Law 144, an algorithmic audit serves as a powerful tool for reassuring your stakeholders that your algorithms undergo vigilant bias monitoring and testing. This proactive approach helps mitigate potential risks posed by your systems while significantly enhancing transparency, ultimately fostering greater trust in your AI systems.

We transparently provide all legally required information, along with essential context to comprehend the audit opinion and summary of results. Furthermore, we openly disclose our audit criteria and methodology, offering maximal transparency while safeguarding the intellectual property of the audited organization.

Absolutely! Our audit process is highly adaptable to cater to your unique compliance and assurance requirements. Feel free to get in touch with us and have a conversation with one of our expert auditors to discover the full spectrum of solutions BABL AI can offer.