Ethics in Action: Ensuring Your Staffing Agency Practices Responsible AI 

Ethics in Action: Ensuring Your Staffing Agency Practices Responsible AI 

Table of Contents

  • Hannah
  • June 28, 2023

Everyone’s getting into Artificial Intelligence (AI), but you haven’t yet. It could be that you don’t have the people or resources to start with, or you fear the repercussions that may come along with the use of it.

AI has transformed many aspects of various industries for good, and it can do the same for yours, too. Here’s how you can start your journey with responsible AI in the staffing industry.

What is Responsible Artificial Intelligence? 

Artificial Intelligence is rapidly advancing, from voice assistants to self-driving cars. It has revolutionized industries and improved people’s efficiency. It is important for us to be aware of our responsibilities in using AI.

Responsible AI refers to the accountable and ethical use of AI systems. It is our job to make sure that the use of this technology benefits us and doesn’t cause anyone any harm.

A survey by Boston Consulting Group (BCG) discovered that 84 percent of the surveyed organizations trust that responsible AI should be a top management priority. However, only 16 percent of them have an effective program in place.¹

Currently, the top 5 highest-growing skills in responsible AI are as follows, according to LinkedIn Collective:

  • AutoML (Automated Machine Learning) is the process of automating the design and optimization of machine learning models.
  • Soft Robotics focuses on designing and developing robots with soft, flexible structures.
  • Deep Neural Networks (DNN) is a type of multi-layered artificial neural network that can learn complex patterns and representations.
  • Natural Language Processing (NLP) involves the use of algorithms and techniques to let computers understand, interpret, and generate human language.
  • Data Science refers to the extraction of insights, knowledge, and value from data through machine learning, statistical analysis, and other processes.


Qualities of Responsible AI in the Staffing Processes 

To build up your processes with the help of responsible AI, you have to understand its beneficial qualities. Here are some of them:



Insights are easy to explain and can be interpreted easily and correctly. Responsible AI can provide you with results and recommendations so that your next steps are clear to you.

In staffing, this can be applied to the clarity of your updates to candidates. AI-generated messages can guide them in the next steps for their application.



Responsible AI complies with data protection laws so that it can support your audits, risk assessments, and mitigation when needed. It makes sure that individuals and organizations are responsible for the results produced by AI and that the consequences that arise from its use can be managed by people.



Responsible AI needs high-quality data to power it. This means that it can then minimize errors and uncertainty to carry out its intended functions. It can screen candidates for you and can match you with the best candidates out of the many applications you’ve received.



Responsible AI was built for fairness. It identifies biases and discrimination and avoids or rectifies them. This AI ensures that equality can be found by diverse groups through its use.

Ethical AI can help promote equal opportunities for all candidates. By using responsible AI systems in the hiring process, staffing and recruitment experts can ensure that there won’t be any discrimination against their candidates based on protected traits such as race, gender, age, or disability.


Privacy and Protection

Ethical AI prioritizes privacy and the protection of personal data. It makes sure that your system adheres to legal and ethical standards when collecting, storing, and using data. Responsible AI systems use robust measures in protecting and adhering to relevant regulations. It provides transparency and control over your use of candidates’ personal information and that of others.


Human Collaboration

Human decision-making is part of the responsible AI process. Ai should only augment human intelligence instead of fully replacing it. Human involvement brings empathy and moral judgment to AI processes, making sure that AI contributes only to well-being and societal progress.


Steps Staffing Experts Can Take Towards Positive AI Principles 

To ensure that your team knows how to use AI ethically, you need a team of experts who will be accountable for your systems. Before fully harnessing AI in the office, here are the steps you can take.


1. Form a Responsible AI Team

This team can help oversee your organization’s AI tools. Your team members don’t have to be limited to IT and AI experts. Include staffing experts as well. Your members may include your HRIT, recruiting, HR, and DEI leaders.

Assigning members that can bring feedback from various perspectives can help thoroughly manage your organization’s AI processes. Based on AI regulatory laws, the characteristics and expertise of your members should include:

  • Diversity in members
  • Technical understanding or expertise in how AI services and systems should work
  • Regulatory and legal features of data and AI
  • Educational issues and human resources related to Artificial Intelligence
  • Representation of stakeholders for AI, including business partners, researchers, business leaders, and customers
  • Communication of your AI ethics and policies with the public, including customers, competitors, and regulators
  • Ethics fundamentals
  • Administrative skill sets


2. Educate the whole recruiting team on the consequences of not using AI responsibly

Failing to implement responsible AI processes can lead to an overall lack of diversity. Bias against underrepresented groups may emerge due to how the algorithm of your AI is faultily designed. All of these can be affected by how data was collected, selected, coded, or used in the training of your AI system. Coding fairness into the system must be done with intention so that your staffing firm can meet your diversity goals.

If AI is adopted irresponsibly, the following implications may possibly occur:

  • Violation of compliance and regulations
  • Penalties
  • Negatively impacting your reputation or employer brand
  • Missed opportunities to hire diversely


3. Audit your current technology to make sure it meets the responsible AI requirements

Auditing your current AI system will depend on the qualities you want it to have. Set the standards and start auditing with these things in mind:

  • Review your data collection and handling by examining your data resources, security measures, storage, and management. Make sure that you are following compliance and regulations regarding data protection.
  • Evaluate your transparency. Ethical AI must be explainable to everyone who manages and views it to understand how decisions were made. Assess its level of interpretability like in the cases of finance and candidate screening.
  • Examine for biases. If undiscovered biases are included in your system’s programming, it may result in unfair outcomes in hiring. You may want to analyze how it affects various demographic groups. Make sure that your system was designed to understand fairness. Implement your own fairness evaluation to filter out any potential biases.


4. Educate your leaders on responsible AI to get their support and feedback

Your leaders should be among the people to be trained first when it comes to responsible AI. Working toward AI hiring practices will require your leadership’s support. Share your work and findings with them and let them help you take charge of any adjustments you may need to make.

Related Reading: Automation 102: Steps for a Successful Implementation 


Develop and Deploy AI Ethically 

Be empowered by harnessing responsible AI while also safeguarding against its unforeseen consequences. Use it in alignment with human values. Contribute positively to society by understanding how to maximize AI responsibly.



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1 “While 84% of Organizations View Responsible AI (RAI) As a Top Management Issue, Only a Quarter Have Fully Mature RAI Programs.” Boston Consulting Group, 20 Sept. 2022, Accessed 10 Jun. 2023.


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