Diversifying Talent Pools in the Wake of New York City’s AI Bias Law
Published Date, 2023

Diversifying Talent Pools In The Wake Of New York City’s AI Bias Law

Created By: Jessica Shatzel and Rebecca Voulgarakis
August 23, 2023

The New York City AI Bias Law (Local Law 144) took effect in early July, ushering in what is sure to be further regulation of the use of AI in recruiting and hiring. This law regulates the use of automated employment decision tools (AEDT) by employers and employment agencies by requiring the use of such tools to be disclosed to employees and candidates. AEDTs are also subject to bias audits, the results of which would be made public. Local Law 144 is the response to an increased understanding of the biases that exist in AI and the limitations of AI tools in human resources functions.

AI’s Bias Tendency in Recruitment and Hiring

Bias can creep in at every stage of the recruiting and hiring process. 68% of hiring managers believe that AI can remove unconscious bias, and many are turning to AI tools to diversify their candidate pools and talent pipelines. However, relying on AI to identify key qualifications in a stack of resumes is likely producing the opposite effect. If the AI is set up to filter talent against a particular job description, there is a high probability that it is filtering out quality candidates and diverse talent who do not meet traditional benchmarks of success for a particular role.

Let’s consider the following qualifications:

  • Years of Experience. It is common for job descriptions to list desired years of experience. However, filtering on this factor may expose an ageism bias and result in candidates who have fewer years of relevant and high-quality experience being eliminated, or candidates who exceed the high end of the threshold being removed from consideration.
  • Higher Education and Advanced Degrees. Attending college and obtaining a degree is a privilege and not accessible to all. Inequities in our educational system and access to financial means are just a few barriers that low-income individuals and communities of color face in securing higher education opportunities. Furthermore, of working-age military veterans, only 42% have a college degree. Setting AI up to filter for degrees or even specific institutions of higher education will limit the diversity of your pool.
  • Title Keywords. Scanning resumes for keywords in titles that match the level you are hiring for will limit your ability to see and consider emerging leaders in your applicant pool. Systemic barriers to advancement for people of color have limited leadership opportunities and access to higher-level jobs. Urban Institute’s Nonprofit Trends and Impacts 2021 report revealed that just 21% of nonprofit executive positions are held by people of color. Considering candidates who have not yet held executive leadership roles but have the skills and expertise to advance to this level of their career will allow for increased diverse representation. 

Utilizing AI to filter for protected classes (race, color, religion, sexual orientation, gender identity, national origin, age and/or disability) – even with the best of intentions to increase diversity – is still discriminatory. These practices, too, are fueling the call for increased regulation and transparency of how AI is used in hiring and recruiting processes. It is important for employers to be aware that they must take ownership of and responsibility for the ways in which AI is used throughout their recruitment and hiring processes to ensure continued compliance with Equal Opportunity Employment laws.

Ultimately, the human relying on AI, not the robot, will be held responsible for the results and possible repercussions of automating these processes.

AI’s Value in Enhancing Recruitment and Hiring

At least for now, humans are still the best choice to lead the initial screening process due to their capacity for evaluating applicants holistically. This naturally raises the question, “Is there room for AI anywhere in the hiring process?” In short, yes. 40% of talent tech solutions include some sort of AI component. This figure encompasses a wide array of products, and when used judiciously, some of them can bring an unprecedented depth and breadth of information to hiring. Think of them as new tools to add to your toolkit rather than replacements for all of your existing tools.

Outside of screening, AI can prove valuable in other stages of hiring:

  • Job Description Development. Without realizing it, you may be introducing bias into your hiring process before the first application even reaches your inbox. Subtle language choices in job postings can discourage diverse talent from applying. Enter AI tools like Textio and Clovers, which are trained to identify and correct linguistic bias in job descriptions to attract more—and more diverse—applicants.
  • Sourcing. Unsatisfied with the size of your candidate pool? You can leverage AI sourcing in conjunction with your regular sourcing methods to cast a wider net. Consider Juicebox AI’s PeopleGPT or the Workable ATS AI tool; both products comb public information for prospects who may be qualified for your open roles. Again, proceed with caution. While the use of AI in sourcing new prospective candidates is distinct from using it to evaluate the applications of those who have already expressed interest, these tools are not infallible in either case and may exclude exceptional talent whose resumes do not match the exact keywords of your posting. However, AI may also introduce diverse talent you otherwise would not have found.
  • Interviews and Reference Checks. You are likely already familiar with AI products that boast transcription or note-taking capabilities, such as Otter.AI. However, you may not have considered the ways these tools of convenience can also help to mitigate bias. Real-time note-taking often shows its value after interviews have concluded. When forced to compare the content of candidates’ answers—as opposed to vague impressions and unreliable memories—you may be surprised by the ways the written record supports or challenges your perception of an interviewee’s performance. Reference calls can benefit from the same objectivity. 

While there are many uses for AI, human resources remains a human function and requires careful consideration before the implementation of AI. Leverage AI’s capacity for good by monitoring and evaluating outcomes to ensure appropriate and equitable utilization – and compliance with all existing and emerging laws.

Orr Group’s talent team leverages technology and human expertise to support your organization’s recruitment, retention, and DEI goals. Get in touch with us to learn more.


Jessica Shatzel is a Senior Director and Head of Talent Management at Orr Group, specializing in executive search, recruitment, and a variety of human resources support for our clients.

Rebecca Voulgarakis is an Associate Director on the Talent team at Orr Group. She supports Orr Group’s outsourced recruitment efforts, delivering peace of mind and identifying top talent for our nonprofit clients.

Related Resources

AI for Nonprofits: 10 Tools and Best Practices to Know

Published Date 2025
AI for Nonprofits: 10 Tools and Best Practices to Know

Created by: CJ Orr May 19, 2025 In today’s technologically driven world, artificial intelligence (AI) has transformed various industries, including fundraising for nonprofit organizations. AI tools have proven to be significant game-changers, enhancing efficiency, creativity, and personalization in donor engagement. To capitalize on these opportunities, over 60% of nonprofits have started embracing AI in their operations. However, despite these high adoption rates, 92% of nonprofits feel unprepared for AI implementation. To prepare your team to fully leverage AI, let’s understand the landscape and discuss the benefits and challenges of using popular AI-powered tools in nonprofit work. Overview of AI for Nonprofits Leveraging AI: Best Practices for Nonprofits Top AI Tools for Nonprofits Overview of AI for Nonprofits What is AI? AI is any technology that can perform intricate tasks and mimic human intelligence. While AI has become a hot topic in recent years, it’s been around for a while, performing simpler duties like sorting emails or scheduling appointments. However, recent advancements in AI have allowed machines to better understand language, process more complex tasks, and generate original content. In the nonprofit world, organizations typically use AI to enhance and streamline: Prospecting and fundraising by analyzing existing donor data for trends, and identifying new prospects with high potential to give Donor communication by analyzing donors based on shared characteristics and tailoring outreach to them for increased engagement Grant writing by quickly reading applications and generating drafts responses, based on previous applications and organizational materials Human resources by automating interview scheduling, onboarding, training, performance management, and more Graphic design by creating visually appealing infographics or mockups Administrative functions by automating repetitive tasks like data entry, timekeeping,  and record maintenance Data insights and reporting by analyzing large datasets to forecast trends and enable better decision-making Types of AI Tools for Nonprofits The library of AI tools is vast and ever-growing. While each organization may have its own needs and goals that AI can support, below are several common types of AI tools you may encounter: Generative AI: consists of machines that create new content based on user prompts and training data. Nonprofit applications: Content creation for grant proposals, social media posts, and impact reports. Large Language Models (LLMs): systems designed to understand and generate human language by learning from vast datasets. LLMs are a subset of generative AI focused primarily on creating and understanding text. Nonprofit applications: Automatically answering routine questions via chatbots or summarizing content. Predictive AI uses statistical models and machine learning to identify patterns in large datasets to forecast future outcomes.  Nonprofit applications: Prospecting for fundraising and future financial growth. Advantages and Challenges of Using AI Advantages Increased efficiency. With AI handling mundane tasks, nonprofits can focus on more pressing mission-critical work. Easy data reporting. Humans are more prone to making errors when reporting on and analyzing data. AI can easily—and accurately—report on important data. Better decision-making. AI can provide context and information that allows nonprofits to make more informed choices faster. Scalability. Advanced AI solutions can easily adapt to a growing nonprofit’s needs, enabling organizations to handle increased workloads without overburdening staff.  Proactive growth. Most nonprofits have adopted AI, and it’s only getting more prevalent. Your nonprofit should leverage similar technology to keep up with others in the field. Challenges Data privacy/security. Nonprofits must confirm that their chosen solution complies with relevant data privacy laws, like GDPR and CCPA, to keep supporter data safe and maintain their trust. Research which regulations apply to your constituents based on their location, and ensure that AI usage is transparently communicated when necessary. Requires human oversight. AI can make mistakes in researching and synthesizing information, so nonprofit teams need to actively maintain their solutions (more on that later).  Initial and ongoing costs. Like any other software solution, AI solutions have costs associated with them, both financial and in time to implement and onboard staff.  Ethical concerns. AI can reinforce biases based on the datasets it's trained on. There are also concerns about Generative AI solutions trained on user data, which can plagiarize information from other sources. Loss of human touch. Nonprofit outreach relies on forging deep personal connections with supporters. While AI can emulate human thought, it lacks the emotional depth needed to reinforce relationships, so it still requires staff to ensure the final product aligns with an organization’s values. Leveraging AI: Best Practices for Nonprofits Establish parameters for AI privacy and ethics. Your entire team should be aligned on ethical best practices while using AI. Adopt an AI usage policy and supporting AI governance infrastructure to ensure you’re fulfilling promises to stakeholders and protecting their sensitive information. Identify areas for AI application. While AI has many different uses, your nonprofit doesn’t have to rely on it for everything. To start, identify a few pressing areas where AI could help your operations, like content creation, data analysis, or task automation.  Work with an expert to implement AI effectively. The stakes are high when implementing AI, so it’s worth consulting with a professional to cover all of your bases. Double-check AI’s work. While AI can generate human-like text, it’s not flawless. You must review and edit the generated content to ensure it aligns with your organization’s voice, mission, and fundraising goals. Properly train your team. AI can present a learning curve for teams, especially those less technologically advanced. Align everyone with comprehensive AI training and educational resources. Don’t completely replace human interaction with AI. As previously mentioned, AI can’t perfectly emulate your connections with supporters. Use AI to brainstorm ideas for communication (like an outline) and fill in the details yourself. Choosing the right AI systems, developing policies, and training your team are essential, but they take time and expert knowledge to get right. By working with a professional team like Orr Group, you can get up and running with new insights and ideal tools by your side.  Top AI Tools for Nonprofits General Use/LLM: ChatGPT Use: ChatGPT is an advanced language model that has significantly influenced the nonprofit sector’s fundraising strategies. It utilizes machine learning algorithms to generate human-like text based on the input it receives.  Best features: Live web search, DALL-E image generation, and access to a growing dataset. Cost:  Limited free tier $20 Plus tier $200 Pro tier $25/user Team tier Pro-tip: Eligible nonprofits can receive a 20% discount on ChatGPT Team and a 50% discount on ChatGPT Enterprise through OpenAI for Nonprofits.  AI Chatbot: Cody Use: Cody is a chatbot that uses organizational content to answer HR-related queries for employees based on defined knowledge sources. Best features: Easy user interface, customizable knowledge base, task automation, and specific features for IT support, business consulting, marketing, HR, and more. Cost: $29/month for the Basic tier, $249/month for the Advanced tier Writing: Grammarly Use: Grammarly is a browser extension that enhances grammar and generates written content. Best features: Tone suggestions, auto-completion of writing, and extensive user-supplemented knowledge base. Cost: Free tier, $12/month, $15/month Prospecting: Apollo Use: Apollo is a sourcing tool that collects contact information for prospective supporters. Best features: Automated outreach, meeting scheduler, and CRM enrichment tools. Cost: Free-$119/month Grantwriting: Grantable Use: Grantable is an LLM that automates aspects of the grantwriting and submission processes. Best features: Ability to train the system from writing samples, reference user-uploaded materials from a library, and include educational resources. Cost: Free-$89/month Graphic Design: Gamma Use: Gamma is a graphic design platform that facilitates the creation of presentations, documents, webpages, infographics, and more. Best features: AI-generated designs, customization options, and user-friendly interface. Cost: Free-$15/seat/month Administrative: Zapier Use: Zapier automates repetitive administrative tasks while connecting various apps and services. Best features: Configurable workflows, app integrations, and a large integration ecosystem. Cost: Free-$69/month Data Management: Microsoft Power BI Use: Microsoft Power BI is a Microsoft add-on tool that allows users to create reports, visualize data, and share insights. Can be combined with Microsoft Copilot 365 for AI data insights. Best features: User-friendly integrations with Microsoft Suite, interactive dashboards, and customizable reports. Cost: Free-$10/user/month Meeting Management: Zoom AI Companion Use: Zoom AI Companion simplifies meeting management by automatically completing tasks during the meeting. Best features: Real-time meeting transcriptions, agenda generation, and ability to assign next actions with a meeting summary. Cost: Free with paid Zoom account Now that you have a solid understanding of AI in the nonprofit world, it’s time to create and execute your own strategy! Developing policies, training your team, and staying updated on the newest best practices can be draining—but it doesn’t have to be. Having an expert team by your side allows you to play around with these tools, test them out, and see what works for you without compromising mission-critical activities. We suggest working with a team with a business-oriented mindset, embedded partnership approach, and AI-specific expertise, like Orr Group. Our well-rounded nonprofit experience and hands-on strategy can help your nonprofit become more comfortable with AI and develop a sustainable use policy in the long term. That way, you can adapt to the rapidly-changing world of AI with ease! CJ Orr is President and Partner of Orr Group. As an expert project and relationship manager with 10+ years of experience in the sector, CJ utilizes data and technology to execute on the development of strategies and tactics to drive effective fundraising plans that meet or exceed targets.