We are excited to announce the launch of FairNow. We simplify and automate fairness compliance. But we go much further and help your business by intelligently auditing and monitoring your AI algorithms, automated decision making, and human processes to ensure that your methods are fair and effective. FairNow also helps vendors demonstrate that their AI-based technology is fair and effective. This will be table-stakes in the near future and we can help you get there.
How it works:
Our platform will play a crucial role in your hiring governance strategy. It has the following three components.
- Onboarding & discovery
- Automated reports
- Continuous monitoring and insights
Onboarding & discovery –
The onboarding & discovery phase has multiple steps to help understand where in your organization AI and automated decision making is taking place. The first part is connecting to your various HRIS/ATS systems and ingesting your data into the FairNow platform. We can also run our code in your data ecosystem, if you prefer. The second step is for you to discover and register your processes and analytical tools. The third step is to set your access rights, define your metrics and thresholds. We can work closely with you and advise during this onboarding and discovery phase.
Automated reports –
Based on what we learn about you during the onboarding process and our knowledge of laws and regulations, we will automatically know which laws apply to you. We will be able to create automated compliance reports and audit prep and will also be able to identify issues with your data – data quality, bias, etc. – and suggest recommendations to improve your data.
Continuous monitoring and insights dashboard –
We ingest data automatically from your HRIS/ATS at regular intervals, including data points about your applicants, their outcome data through your hiring funnel, and any AI model scores used. We then run our models and analyses on these inputs continuously.
Our Insights reports provide you with findings about your hiring practices and AI tools, evaluating them for fairness, explainability and effectiveness. We can help you measure the ROI of your practices, the effectiveness of your tools and interviewers, and the factors behind the decisions of your AI algorithms. These insights will give you comfort in the robustness of your process and/or identify areas for remedy.
We provide continuous monitoring to help you proactively identify issues as they arise. Understanding the ongoing status of your AI tools is crucial. Even though an AI algorithm might be fair and effective when it is deployed, it can still lose performance and fall out of compliance over time due to model drift and changes in the applicant population.
We take privacy and security seriously:
- We anonymize your data.
- We do not persist your data.
- We follow SOC 2 compliance for cybersecurity.
- We can deploy our software to your cloud or our secure cloud environment.
In addition to our core technology platform, we will provide an extensive body of resources to help you on your automation and AI journey.
- Responsible AI laws and regulations. In 2022 alone, Colorado, Illinois, Vermont and Washington passed laws related to the fair usage of AI, and many other states are considering similar legislation. The European Union is also considering a broad AI regulatory scheme. We will go deeper on AI laws and regulations in the hiring and HR domain. Most importantly for hiring, NYC Local Law 144 will require companies using AI tools in their hiring process to prove fair use via an independent audit. Click here to learn more about NYC LL 144. New Jersey is planning a similar regulation with NJ A4909. We expect other jurisdictions will follow suit, and we can help you stay informed on the latest developments.
- Best practices in AI governance. More to come about our framework, which includes leadership, policy/governance, stakeholders, and standards, for both building and buying AI tools. We will also have links to our partner organizations that offer additional resources, frameworks, and support.
- Our framework for responsibility:
- Fairness – Your applicants should be treated without bias or discrimination. There are many ways to define fairness, but we narrow down to the 4 most common and relevant definitions and talk about trade-offs to help you figure out what matters to you.
- Explainability – You should be able to understand what factors drive the decisions made by your AI tools. This is critical to mitigating bias and building trust.
- Effectiveness – You should be able to evaluate the performance of your AI tools. AI tools can drift and perform worse over time. You should constantly monitor them to ensure you are getting the best ROI.
FairNow helps build trust in AI-enabled decisions. We simplify and automate fairness compliance. FairNow helps your business by intelligently monitoring the outcomes of your AI algorithms and human processes to ensure that your methods are fair, effective, and explainable. Contact us to talk!