AI in the Workplace

  7 min 11 sec to read
AI in the Workplace

BY Rajendra Prasad Koirala

Although the term artificial intelligence (AI) was first coined in the 1950s, the idea has always fascinated people. AI was once limited to science fiction and futuristic dreams, but recent technological advances have made it a commonplace concept. Every day, we rely on these systems to receive directions, check the weather, read the news, and manage voicemail. Additionally, these technologies are gradually taking the place of or guiding human decision-making in crucial areas like banking, employment, criminal justice enforcement, and medical care. Concerns regarding the proper place of algorithmic decision-making in our society have been addressed by a number of academics in response to these advancements, which provide a variety of societal difficulties. 

AI tools are being used by an increasing number of companies for labour management, recruitment, and selection. Concerns have been raised by these advancements that these systems might treat employees unfairly, discriminatorily, or in an invasive way. 

It is difficult to describe artificial intelligence precisely, and the word is frequently used synonymously with other concepts like machine learning, algorithmic decision-making, and automated decision-making. There are particular concerns about the application of AI in the workplace. The question of whether artificial intelligence (AI) or other emerging technologies, such as automation and robotics, will replace workers has received a lot of attention lately.

Artificial intelligence technologies have been implemented by employers to support a range of human resources and administrative tasks. AI techniques are deployed for tasks ranging from screening job applicants to assessing suitable candidates for openings. AI has also been used by employers to identify workers who may be more inclined to depart the organisation. 

AI has revolutionised a number of industries in recent years by bringing efficiency and creativity. This quick development has, however, also sparked worries about possible job threats. AI is both generating new employment opportunities and displacing existing ones, especially in sectors of the economy that mostly depend on repetitive and regular work. A World Economic Forum analysis projects that artificial intelligence by 2025 will have generated 133 million new employment while dislodging 75 million existing ones worldwide. Certain responsibilities and functions that were previously completed by humans can now be automated. This necessitates reconsidering how we view employment and work in the age of automation. 

Obstacles that Workforce Faces

1. Job displacement: The main issue at hand is the possible loss of jobs as machines take over repetitive duties, which could result in a sizable percentage of the labour population becoming unemployed.

2. Skills Mismatch: As AI develops quickly, there is a constant need to improve skills. This could result in a skills gap as many workers could not be prepared for the jobs of the future.

3. Unequal Impact: Not all industry or demographic groups are equally affected by AI. There is a possibility that some industries could be more severely affected, and that disadvantaged groups would have additional difficulties. 

4. Unequal Impact: Not all industry or demographic groups are affected equally by AI. There is a possibility that some industries could be more severely affected, and that disadvantaged groups would have additional difficulties. 

AI and Employment Discrimination

Access to work possibilities may be significantly impacted when a company employs AI technologies in recruiting, hiring, and promotion choices. These technological advancements hold the potential to improve the fairness and reduce discrimination in HR procedures. 

Human decision-makers frequently have implicit or explicit biases that unfairly penalise women, people of colour, and other marginalised groups. Technology may be able to assist mitigate these biases. Though AI technologies seem unbiased and objective, depending on how they are designed and trained, they may also bring new types of prejudice or replicate human biases. Numerous instances of algorithmic bias have been reported in studies. If AI is educated on biassed data, it may also generate biassed findings. Future job performance will be predictably skewed by an algorithm that was trained on the subjective assessments of a biassed supervisor. In a similar vein, discrimination may occur from a hiring algorithm that matches applicants with present workers if the employer has historically excluded particular groups from consideration. When the system tries to anticipate the most promising candidates, it will probably replicate the employer's very low percentage of female computer programmers. Likewise, a system designed to optimise "cultural fit" by suggesting candidates who resemble existing staff members may function to ostracise members of underrepresented racial or ethnic groups. 

Biassed results may also arise from other data issues. AI's ability to select the most promising applicants from a group will be hampered by incomplete or inaccurate training data, and it may even consistently underestimate the prospects for success. It is also possible for the algorithm to systematically disadvantage protected groups if the training data is not representative of the population to which it will be applied, even if neither the algorithm's developer nor the employer utilising it intended to discriminate. 

Even the diversity of the applicant pool may be impacted by the dangers of biassed AI before the employer has an opportunity to assess job seekers. Employers now primarily use online job boards to post job openings and find qualified candidates. But those platforms do more than just publish job openings everywhere. Rather, they rely on AI to forecast the individuals most likely to seize a given opportunity, and such forecasts frequently mirror historical trends in occupational segregation. 

AI and the privacy and autonomy of employees 

AI solutions are being incorporated into work responsibilities increasingly, in addition to helping with traditional HR duties. These tools can help employees work more productively which can have a huge positive impact. Simultaneously, extensive AI integration in the workplace usually necessitates the gathering and processing of copious amounts of data, a significant portion of which is obtained from workers. 

Employers now have more authority to oversee and manage employees as a result of this extensive data collecting. Consequently, privacy and autonomy problems are raised by the growing usage of AI in the workplace. AI requires the collecting and processing of massive volumes of employee data, which puts employee privacy at risk. Furthermore, workers may feel helpless and alienated when AI systems make judgments that have significant effects on employment without providing transparency or responsibility. These problems are not new, but the increasing application of AI techniques increases their scope significantly, and the law, globally, rather in our country too, now offers very little direct remedy mechanisms. 

Getting Used to the AI Age

1. Reskilling and Upskilling: Proactive education and training are essential to reducing the threat. Programmes aimed at upskilling and reskilling workers can enable them to adopt new technologies.

2. Embracing Collaborative Intelligence: AI may augment human workers' capabilities rather than replace them. Increased creativity and productivity are possible with collaborative intelligence, where people and robots collaborate in a positive way.

3. Ethical AI Practices: It is critical to put ethical AI practices into effect. Concerns about employment displacement can be allayed and bias can be prevented by ensuring that AI technologies are developed and applied ethically. 


Even American law at this point is inadequate to handle the problems brought about by the growing use of AI in the workplace, let alone the rest of the globe. Although several laws now in place provide protection against discrimination as well as employee autonomy and privacy, there is no complete framework in place to handle the unique risks of damage that arise when workers are managed by machine learning techniques. The law will need to change as artificial intelligence (AI) becomes more widely used and crucial to business in order to effectively prevent discrimination, safeguard privacy, and address worries about worker alienation and loss of personal security. 

The complexity of the AI threat to the workplace necessitates a thoughtful and proactive response. Even while there will inevitably be difficulties, we can traverse this revolutionary time in the history of work by seizing the potential AI offers for creativity and teamwork. Through education, ethical AI practices, and inclusivity, we can create a future where human labour and AI coexist together, resulting in a workforce that is more flexible and resilient. 

(Koirala is the CEO of Gyanda Academy)

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