As the adoption of artificial intelligence (AI) continues to expand, many individuals and corporate bodies are currently looking for ways to integrate AI to amplify efficiency and productivity across various industries.
Recently, an AI-powered platform was launched that allows recruiters to search for experts in different fields using search prompts. This platform is definitely just one amongst a host of others trying to make good impact on recruitment, human resource management and business operations.
While the advantages of platforms like this are clear, there are concerns about the legal implications of such platforms. When the launch of this platform was announced, we observed that someone raised a personal concern as to whether or not the developers of the launched platform trained the AI-powered tool on the data of individuals without their consent. According to the individual, if this is the case, it could be a breach of privacy and could lead to legal action.
The founder of the platform responded to this concern by stating that they did not train an AI model using any individual’s data and that all AI models used are developed and trained by OpenAI. According to the founder, they used the models by providing them with contextual information obtained via compliant sources.
Another individual raised a personal concern and opined that the launched platform and other similar platforms with the same models or system of operations could be used by hackers during the research and reconnaissance phase to identify people working at the target company. This raises concerns about the platform's data privacy and security, as well as intellectual property rights.
Some other possible legal issues other individuals highlighted include the potential for the platform to perpetuate biases and discrimination. These legal issues are not farfetched since AI models are trained on historical data, and if the data is biased, the AI model may perpetuate the bias. This raises concerns about discrimination in the hiring process, which is illegal under many employment laws and regulations.
Despite these and many other concerns, the adoption of AI in recruitment, human resource management, and business operations has numerous benefits which include:
Improved Candidate Selection:
AI can improve candidate selection by using machine learning algorithms to analyze resumes and identify the most qualified candidates based on job requirements. These algorithms can detect relevant skills, experience, and education, while also considering factors such as location and language proficiency. This approach ensures that recruiters can easily identify the best candidates from a large pool of applicants.
If well developed, the concerns of biases that may affect candidate selection can be eliminated. This can be done by removing subjective factors such as name, gender, and age. AI can help ensure that selection is based solely on job-relevant factors. This can help organizations create a more diverse and inclusive workforce while ensuring that they hire the best candidates for the job.
AI can also improve candidate selection through the use of predictive analytics. By analyzing data on past hires, performance and turnover rates, AI can identify patterns and trends that can help recruiters make more informed decisions when selecting candidates. profiles, assess their skills, and provide an objective assessment of their qualifications, making the selection process more efficient and unbiased.
Time and Cost Savings:
With the improved candidate selection processes with AI, recruiters can screen resumes, schedule interviews, and conduct background checks in a fraction of the time it would take manually. In this same vein, recruitment can be an expensive process, from advertising job openings to paying recruiters and conducting the background checks. AI can significantly reduce these costs by automating many of the recruitment tasks that previously required manual labour.
Improved Employee Engagement:
AI can also be used to improve employee engagement and satisfaction which can lead to higher retention rates. AI-powered tools can be used to monitor employee engagement and provide insight into areas where improvements can be made. They can also analyze employee data, such as performance reviews and feedback, to identify areas where employees need additional support or training. The information can be used to create personalized development plans for each employee, which can help to improve their skills and job satisfaction.
To address these issues, there are possible solutions for companies developing AI-powered tools for recruitment and human resource management to consider.
Firstly, it is important that these companies develop transparent algorithms that can be easily explained to the users; particularly the candidates in a recruitment process. By making the selection process clear, candidates can trust that they are being evaluated based on their qualifications and experience. Transparency is also important for ensuring that algorithms used are compliant with relevant regulations.
Secondly, these companies should be aware of potential biases in data sets, such as underrepresentation of certain demographics or the overrepresentation of certain qualifications because AI algorithms can only be as unbiased as the data sets used to train them. This can lead to AI models that are biased against certain candidates. The companies should ensure that their data sets are diverse and representative of the candidate pool.
Thirdly, these companies should continuously evaluate and refine their products algorithms to ensure that they are performing as intended. This should be accompanied by a regular review of the data used to train their algorithms and adjust them as necessary to avoid biases and improve accuracy.
Flowing from the above, recruiters should use multiple data sources to evaluate candidates, rather than relying solely on AI algorithms. It is also important that they maintain open communication with candidates throughout the recruitment process. This includes informing them of the use of AI algorithms and how they are being used to evaluate their candidacy. Candidates should also have the ability to provide feedback and ask questions about the selection process.
