Exploring the Effects of GenAI on Labor Market Stability in India

Experts from various fields discussed the impact of Generative AI (GenAI) on India’s workforce during the Digital Futures Lab discussion on June 21 and 22, 2024. Speakers discussed the impact of GenAI on various work sectors including writing, research, work unorganized and agriculture. Throughout the discussion, participants also spoke about the need to consider the implications of GenAI on productivity, efficiency and job displacement by demanding more accountability from AI companies on the possibility of their products being used for illegal purposes.

Use GenAI for productivity:

Speakers talked about the impact of GenAI on editing and curation jobs, especially in the field of data management. One speaker talked about how interns had to do small tasks which, although useful for practice, did not utilize human potential to the fullest. Now, AI models like Chat-GPT have demonstrated the ability to perform such tasks more efficiently, eliminating human error and reducing training requirements. This shift is encouraging companies to use AI for tasks such as coding, data collection, and other decision-making processes.

However, in doing so GenAI also raises the minimum barrier for entry-level intellectual work, the speaker said. Companies are increasingly emphasizing AI skills in their hiring processes, although there is uncertainty about what might constitute sufficient AI training. The impact on employment is unclear, as the number of apprenticeships has not changed significantly. However, there is a growing skills gap, evident with companies like TCS saying it will train people how to use GenAI.

Another speaker claimed that a focus on AI-generated content has resulted in a 30% increase in productivity. The speaker also mentioned how some countries like the Republic of Korea are working on a robot tax to prevent the replacement of humans in favor of generative AI. The discussion also highlighted the need for clearer definitions of AI skills to prevent misleading claims of expertise based only on basic trigger skills.

Increased productivity will affect working hours:

Regarding the discussion of delegating small tasks to GenAI, one speaker said that reducing work should also consider its impact on time.

“If we are not reducing time while reducing work, this will lead to unemployment,” the speaker said, stressing that the global south must strengthen demands for less working time and how that time will be invested. Speakers suggested that AI should work with union leaders, who are not as tech-savvy.

GenAI redirects the workforce to core work:

Another speaker said in rural areas, AI is enabling economic activities for women working in their mother tongue and creating new opportunities. Partnerships with universities are emerging, matching student loans with public sector job opportunities, indicating a growing interest in AI among students and consumers.

Another observation was that students who could not boast of AI skills on their CVs were turning to NGOs, redirecting a significant number of students from sophisticated universities to 3-4 salary NGO jobs lakhs. This trend suggests that AI is reshaping the job market, creating new jobs for educated workers in the nonprofit sector, while potentially replacing traditional roles in larger corporations.

One speaker spoke about how GenAI is showing potential to positively impact employment and job prospects in India. The person gave the example of how AI tools can help ease women’s re-entry into the workforce after childbirth. Another example given was in the beauty industry, where workers typically earn between INR 60-150. By using GenAI, women can increase their productivity by better understanding skin tones, hair types and product suitability. Similarly, AI can improve their ability to personalize services, potentially leading to improved profits and work performance.

GenAI can help bridge training and skills gaps:

One speaker talked about how GenAI can help training and skills development and overcome barriers such as language gaps. They gave the example of the artificial intelligence tool Whisper, which helps individuals with no typing experience or technologies like Google Translate and voice-to-text overcome language and literacy issues.

The speaker went on to talk about GenAI’s potential to break down silos in training systems, suggesting the need for policymakers to consider and budget for these technologies in educational planning. However, the use of AI in training raises important considerations regarding human development, pay structures, productivity metrics, and efficiency. During the discussion there were also concerns about how over-reliance on AI could be problematic in developing countries like India, potentially hindering competition or exacerbating existing inequalities.

Moreover, the pressure on women to increase productivity through AI-supported work-from-home arrangements may reinforce patriarchal structures rather than alleviate them.

How will GenAI affect women?

While several speakers talked about how GenAI could lighten the workload for some women, another speaker pointed out that jobs in sectors such as textiles, apparel and food (packaging) are those that are currently in the process of being automated. Most of these jobs are owned by women. As such, the speaker urged others to consider the impact of technological advances on women, especially given that most women in India do not have electronic devices of their own and must share them with their children.

“Are we equipped to have this discussion of the impact of AI on women? How will AI be adopted by women? How do you give them access to this discussion?” asked the speaker.

Why farmers reject Agritech?

During the discussion, the speakers talked about the use of the latest technologies in sectors such as agriculture. One speaker said that farmers are actively refusing to use the technology because historically they have been burned many times. The speaker said that while Agritech tells farmers what they already know, it fails to provide farmers with the assurance of mitigating uncertainties. Farmers remain apprehensive about digitization measures due to lack of transparency, unfair prices, etc., and inability of technology to increase overall income. As such, the speaker said there is a need to look at GenAI in this context.

Speakers demand accountability from AI companies:

Drawing parallels with ride-sharing platforms like Uber, which initially argued they were mere aggregators, one speaker said AI companies could face similar scrutiny and legal challenges. Just as Uber was ultimately held accountable for driver insurance and safety, there is a growing sense that AI companies should be held accountable for the content their technologies enable or produce. The speaker gave the example of how a novice working on an AI tool had predicted that the tool was likely to be used for illegal purposes for pornography, but could not be held responsible for it.

The speaker argued that currently, social media platforms are facing increased regulation and that a similar trend could emerge for AI companies. The main principle being proposed is that these companies should implement powerful discriminators or filters to prevent the spread of problematic content.

Algorithm should be considered together with AI:

Another speaker noted that the navigation algorithm plays a bigger role in the distribution of work than AI ever did. Therefore, there is a need to audit these algorithms even if AI is not there in the system because the algorithm is used as a control lever.

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