Prove Your AI Is Free from Algorithm Bias

An AI bias audit is a structured evaluation of an AI system that is designed to detect and measure unfair or discriminatory outcomes.

AI bias occurs when an algorithm produces systematically prejudiced results often due to biases in the data, modeling choices, or assumptions made during development.

Bias audits are a critical part of responsible AI governance practices and a regulatory requirement from laws like NYC LL144, Colorado SB205, and more.

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As regulations and standards around AI fairness tighten, ensuring your AI applications comply with these standards is business-critical. Additionally, bias mitigation is becoming table-stakes expectations for customers and stakeholders.

FairNow not only helps detect and mitigate bias but also aligns with the latest regulatory guidelines, providing documentation and audit trails that support compliance efforts.

This proactive approach can save your business from costly fines and legal challenges while also boosting your credibility in the market.

Bias audits help organizations to avoid causing harm from biased AI. This helps society at large but also prevents the organization from reputational, financial and legal risks.

Additionally, bias audits provide a level of assurance and trust that the AI can be used safely. This lets an organization build the confidence to reap the benefits of AI knowing that the risks of bias have been managed. And it also builds trust with customers and stakeholders. This is especially the case for organizations that build and sell AI to customers, where bias audits and responsible AI practices are a key differentiator in sales cycles.

This can lead to unfair outcomes, such as discrimination against certain groups or misinformed business decisions, harming your reputation and potentially leading to legal consequences

There are many reasons.

First, bias audits can help detect and prevent harms before they happen. Because AI is trained on data that can carry patterns of historical discrimination (e.g., in hiring or lending), there’s a risk of these patterns getting learned or even amplified if unchecked.

Second, bias evaluations are a requirement under many laws and AI governance standards (like ISO 42001), so it is a matter of compliance.

Third, bias audits are a way to build trust with stakeholders and demonstrate responsible AI practices. Bias audits show that your organization is doing the right thing to detect and mitigate problems, and that you’re transparent about sharing this process broadly.

Bias audits typically involve reviewing AI outcomes for different demographic groups. This is done using historical data where the model was used previously, or synthetic data that is specifically designed to test for bias. 

For example, to test an AI that makes hiring decisions, you could evaluate the average pass rate by group (e.g. men vs women) to detect differences that are worth investigating.

It’s important to note that large group differences are not always a sign of bias. For example, the candidates in one group may meet the requirements for a job posting at a much higher rate than another group. Additional deep dive analyses can help paint a fuller picture of what’s going on.

Additionally, bias audits might also involve reviewing input data, assessing the guardrails and oversight placed on the system, and conversations with stakeholders to identify potential issues.

We use state-of-the-art technology to analyze your AI models and the data they process. Our software scrutinizes various elements such as model behavior and decision patterns to identify biases that might not be evident at first glance.

If detected, our tool provides detailed reports and recommendations on how to address these biases, ensuring your AI operates fairly.

Unlike a one-time bias audit, FairNow offers ongoing detection capabilities and continuous learning to adapt to new biases and regulations over time.

Our user-friendly dashboard allows you to monitor your AI applications in real-time.

Evaluating your AI for the first time? Our expert technical team is available to guide you through the bias mitigation process.

With FairNow, you’re not just purchasing software; you’re investing in a partnership that grows with your business and ensures you maintain ethical AI practices.

FairNow offers AI Regulatory Compliance Software embedded into its AI governance platform. All clients on the platform have access to AI bias audit and reporting tools to ensure and demonstrate that their AI is compliant.

While New York City LL144 is most commonly associated with bias assessments, a growing number of laws and regulations require bias assessments.

Some of the most notable regulations include the EU AI Act, Colorado SB 24-205, Colorado SB21-169, and more.

We are happy to simplify this process for our clients so they can focus on innovation and growth while we track the requirements.

In addition to laws and regulations, FairNow’s bias assessments can support voluntary standards such as ISO/IEC 42001 and the US NIST AI RMF.

The cost of implementing AI regulatory compliance software varies based on the organization’s size, the complexity of the AI applications, and the specific compliance needs. FairNow offers scalable solutions to fit different business sizes and requirements.

Request a demo for an instant quote.