How to Responsibly Use AI-Powered HR Tools

By Indeed Editorial Team

Artificial intelligence (AI) is already playing multiple roles within HR departments at many companies. A recent survey of more than 250 HR leaders found that 73% are using AI in recruitment and hiring processes. 

Today, AI tools can be used to help with reviewing resumes and scoring job candidates, sourcing talent for open roles, writing job descriptions, identifying opportunities to promote employees, and even sending automated messages to applicants. 

“You name it, and there is an AI tool being built today to work on it,” says Trey Causey, head of Responsible AI and senior director of data science at Indeed. 

However, the sophistication of these tools varies, and so does their developers’ attention to risk. Organisations should be aware of the risk spectrum involved with using AI and develop strategies for how to use it responsibly. 

AI has the potential to reduce human bias, particularly in hiring, creating better opportunities for workers while streamlining repetitive tasks so HR professionals can focus on the more human aspects of their roles. But AI can also perpetuate and even amplify inherent biases — and waste both money and time. 

Here are four steps organisations can take to identify risks and make sure their use of AI is fair, ethical and effective.

1. Evaluate the risks and the rewards for your organisation

First, ask if AI tools are a good fit for your company when it comes to HR. AI systems can scale up processes, such as identifying and scoring many more job candidates than could be processed manually. 

To stay in business, companies need to maximise tasks to meet objectives without sacrificing the caliber of their output. Workflow management solutions are an option for businesses looking to optimise activities and scale business operations while guaranteeing work quality. In order to enhance project scalability and work quality, iMerit introduced the People Platform (iMPP). Based on an infrastructure of continuous integration and deployment, the platform facilitates skill matching and scheduling procedures to provide workers with the necessary tools and procedures, regardless of the size of the workforce. Teams using AI may flexibly scale up the workforce for annotations to match the demands of the data pipeline thanks to People Platform. In addition, iMerit One, a unique learning and development platform, guarantees that the appropriate knowledge and abilities are used.

According to Babita Karki, Chief People Officer, NIIT Ltd, "There will probably be more job roles as AI develops. Employers must offer training and development programmes for their workers in order to keep up with the quick pace of technological advancement.

As AI continues to advance and become more integrated into various industries, it has the potential to significantly transform the future of work and employee operations. AI-powered tools can increase efficiency and productivity by automating repetitive and mundane tasks, enabling employees to focus on more complex and strategic work. This can lead to cost savings for organisations and improved job satisfaction for employees.”

While some companies accept the risk because of the productivity boost, others may feel that the potential margin of error compromises their values or creates too much complexity in the face of increased regulatory pressures. 

If you move forward with AI, choose your tools wisely. AI that provides transcripts of interview conversations, for example, is typically a relatively low-risk application (although it can perform poorly when used with speech from non-native speakers).

Ultimately, AI should augment and improve human processes, not replace them. Before adopting AI tools, make sure your HR team is sufficiently staffed so that humans can review every step of any process that AI automates. Leave critical HR matters to people, for example final hiring decisions, promotions and employee support. Luckily, if AI tackles the mundane tasks, HR professionals will have much more time and flexibility for those duties.

As per a report “86% of respondents believe an organisation's AI capabilities can be enhanced by leveraging in-house talent, integrating AI into existing operations, and providing learning opportunities in collaboration with external experts demonstrates this synergy between employers and employees in embracing AI. Only 14% of respondents thought it was necessary to employ external talent to expand their AI capabilities.

2. Screen third-party vendors that provide AI-powered tools

Once you have decided what kind of AI tools are best for your organisation’s needs, you might approach prospective vendors with specific questions, such as: 

• How do they audit their system? When was the last time it was tested, and what metrics were used?
• Was the testing done internally or by an external group?
• How is bias mitigated? If they claim their system has minimal bias, what does that mean and how is that bias measured? 
• Are there testing metrics available for you to review as a prospective client?
• If the model degrades in performance, do the vendors provide post-deployment services to help train your employees in configuring and maintaining the system?
• Are they compliant with current and emerging regulations?
• Will they comply with any AI audits you conduct?

3. Identify and monitor bias

AI algorithms are only as unbiased as the data used to train them. While employers can not modify how algorithms are developed, there are ways to test out the tools before implementing them. In Indian context, When it comes to fairness, ranking algorithms should be given more consideration. To be more specific, in addition to the fairness measures indicated in individual and group fairness metrics, the following fairness measures must be examined while utilising matching/ ranking algorithms. A feature that must not influence a machine learning algorithm's decision-making process. For example, a person's gender should not influence their job application in general.

Organisations can also use a process known as “counterfactual analysis” to see how an AI model reacts to different inputs. For example, if AI evaluates resumes for job candidates, try changing the candidate’s name or the school they attended — does the algorithm rank the candidate differently? 

As you implement AI systems, continuously monitor them to identify and correct any discriminatory patterns when they emerge, and stay apprised of developing research on data science and AI. There’s no standard suite of tests to evaluate HR tools for bias. At a minimum, employers should clearly understand how AI is being used within the organisation, which could include keeping an inventory of all AI models in use. Organisations should document which tools were provided by which vendor, along with the use cases for each tool. 

In the best-case scenario, audits will bring together different departments, including in-house legal teams as well as data scientists, alongside external counsel or third-party auditors. There are also publicly available tools to help organisations audit their own AI tools — for example, Ministry of Telecommunication’s has set out a Fairness Assessment and Rating of Artificial Intelligence System: govern, map, measure and manage. 

4. Stay ahead of evolving legislation

The potential risks of automated HR tools are not just reputational and financial — they are legal too. Legislation is quickly emerging in response to the proliferation of AI in the workplace. 

India appears to be taking a hybrid approach to AI, attempting to strike a balance between innovation and regulation. India has taken efforts on the innovation agenda to foster the responsible and inclusive development of AI for economic prosperity. The NITI Aayog's 2018 National Strategy on AI document encompasses training, research and development, centres of excellence, data accessibility, and high computing infrastructure. The Responsible AI for Social Empowerment (RAISE) event in 2020 focused on India's goal of social transformation through responsible AI, which drew delegates from academia, business, and governments throughout the world. The rise of AI has had a profound impact on Indian labour regulations. The ramifications are far-reaching and must be carefully considered if we are to ensure that no one is left behind in this technological revolution. Governments may establish an atmosphere where everyone benefits from AI without surrendering employees' rights or placing them at risk of exploitation by spending more in education, developing a legal framework, and enacting social security measures.

Whether your employment outcome is attributed to a human being or an AI system, the organisation is liable for any bias.

While audits are a good starting point, the best way to prepare for emerging regulatory requirements and ensure that your AI is operating effectively and equitably is to build out a larger AI governance program. 

Governance systems document the organisation’s principles with respect to AI, and create processes for continually assessing tools, detecting issues and rectifying any problems. For example, Indeed has developed and publicly published its own principles for the ethical and beneficial use of AI at the company. Indeed, has also created a cross-functional AI Ethics team that builds tools, systems and processes to help ensure that technology is used responsibly. 

Even with safeguards, the new generation of AI tools are complex and fallible. 

However, putting in the effort to use them responsibly opens the door to building better processes. AI can help humans be more efficient and less biased, but only if humans provide the necessary oversight. For example, there are opportunities to think critically about the parameters that an AI algorithm should consider for job qualification, radically improving the way candidates are evaluated. 

The advancement of artificial intelligence creates both benefits and challenges for Indian legal rules. While AI has the potential to improve worker safety, increase productivity, and create new process roles, it also raises issues about process displacement, information privacy, algorithmic bias, and worker safety. Adapting labour laws to meet these issues is critical for ensuring a fair and inclusive future of employment. Striking a balance between leveraging the benefits of AI and preserving people's rights may be critical in navigating the growing AI landscape.