Is artificial intelligence a friend or foe? Various scholars from different sectors of life and work have answered this question. Let us examine this through some facts. According to the Future of Jobs report, 2020, It is estimated that by 2025, 85 million jobs may be displayed by a shift in the division of labour between humans and machines. However, 97 million new jobs will also be generated because of this shift, which will help humans find new areas of jobs. In the same report, it was stated that there is an increase in the shift from adopting humanoid robots to non-humanoid robots in firms, especially socially aligned firms such as public restaurants. As per the study by the RIS Policy Brief, June 2021, the question of whether analogous processes occur in the perception of non-social entities like robots is brought up by the significance of categorization processes in social cognition. Evidence suggests that they do so. Certain humanoid robots appear to be automatically classified according to national, racial, and gender classifications. Additionally, people evaluate robots whose physical characteristics suggest that they are male or female, based on gender norms. Stereotyping has also been linked to the assessment of other types of human-like robots (such as computers with male or female voices). Thus, there is proof that some machines and robots can be viewed from a social perspective. This can be another challenge for a multidiverse country like India. This points out that the amendments in the laws and policies of the nation as per the change in lifestyles with the robots will prevent all the consequences of this kind of stereotypes.
If we refer to the historical facts, we can see that lack of the efficient and practical policy research for balancing the life of human existence and the advancing of AI as the “future factor of production” alongside by displacing capital and labor. This can be proved by the studies of famous economists, Purdy and Daugherty, who show that in recent decades, the capital efficiency rate has declined, but the GDP of most developed countries has increased. However, this was not the case for developing nations. Nations like India, which rely heavily on labor-intensive products and production methods, must seek alternative strategies to address the anticipated rise in unemployment resulting from the increasing prevalence of artificial intelligence. The potential impact of AI on employment and economic structures necessitates a comprehensive approach to policy-making, particularly in labor-intensive economies. Governments and industries must collaborate to develop strategies that balance technological advancement with job creation and skill development. This may involve investing in education and training programs to prepare the workforce for AI-driven industries, as well as exploring new economic models that can accommodate both human and artificial labor. As for India, the lack of focus and investment in research and development will cause it to be lacking. A well-defined formulated policy for developing nations such as India can change this fact.
To address such issues, India should emphasize the need for a comprehensive AI skilling framework that integrates industry, academia, and various sectors of society. This underscores the importance of not only coding skills, but also a deep understanding of algorithms and domain-specific applications. This holistic approach is necessary to produce skilled professionals who can effectively use AI in diverse fields such as healthcare, agriculture, and urban planning. The loopholes in the Indian educational system and lack of access to basic resources such as digitization indicate that many individuals lack clarity on where to start their AI learning journey, reflecting a broader issue of accessibility to quality educational resources. There is consensus that while numerous courses exist, the quality and relevance of these courses often fall short of industry needs, leading to a significant gap in employability. Government programs like Skill India and Digital India provide a frame work for integrating AI into vocational training and higher education. For instance, it is necessary to include underprivileged groups, such as tribes, particularly those that are unknown to the outside world. Consultation with the tribes and a shared understanding of their culture and AI environment are important when it comes to the formulation of AI policies. These programs concentrate on bridging the digital divide, guaranteeing inclusivity, and developing a workforce with AI capabilities. To develop specific AI courses and certifications, partnerships with academic institutions, IT firms, NGOs and startups are encouraged.
As the government provides funds to create AI research institutes and innovation laboratories, funding and support for research and development are equally essential. This improves academic programs and fosters corporate collaborations, allowing for practical training and the practical use of AI skills.
Moreover, the need for ethical considerations in the development of AI is a recurring issue. The importance of addressing biases and ethical implications in AI systems, advocating for a curriculum that incorporates ethical training alongside technical skills. This is crucial, particularly as AI becomes increasingly integrated into the decision-making processes that affect various aspects of life. While ethical considerations in AI are important, an overemphasis on ethics in the curriculum could potentially slow down technological progress and innovation. Focusing too heavily on ethical training might divert resources and time from developing crucial technical skills, potentially putting Indian AI professionals at a competitive disadvantage in the global market. Moreover, ethical standards can vary across cultures and contexts, making it challenging to implement a universally applicable ethical framework in AI education and potentially leading to inconsistencies in AI development and application.
Capgemini (2017), in their report AI has produced new job opportunities, according to 83% of executives from large organizations surveyed, with 67% of these new jobs being at the manager or higher level including India. What about the upskilling and reskilling of the jobs below the managerial level? This question states that a critical discourse on AI skilling and reskilling in India, highlighting the urgent need for structured initiatives that bridge the gap between formal and informal job sectors. This calls for collaborative efforts among stakeholders to create a workforce that is not only technically proficient but also aware of the implications of informal sector in AI technology. Therefore, the future of AI in India hinges on a well-rounded, inclusive skilling strategy that prepares individuals to thrive in an AI-driven world. India’s lack of data ecosystems and poor research capacity are cited as obstacles to achieving AI’s full potential. Two-tiered research institutes should be established in India (for both basic and applied research). For the present workforce, learning platforms must be established. Additionally, the nation ought to establish focused data sets and startup incubation centers. Lastly, it ought to provide a legal framework for cyber security and data protection.