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By:

Rajendra Joshi

3 December 2024 at 9:20:26 am

Centre pushes for early sugarcane crushing

Mills seek special subsidy Kolhapur: Despite an estimated 30-40 lakh tonnes of sugar being available in excess of domestic demand, the Centre is stepping up efforts to keep sugar prices under control. The Union Food Ministry has urged Maharashtra, Uttar Pradesh and Karnataka to advance the 2026-27 sugarcane crushing season so that fresh sugar reaches the market before the existing stock is exhausted. Sugar mills, however, say an early start will come at a cost. They are seeking special...

Centre pushes for early sugarcane crushing

Mills seek special subsidy Kolhapur: Despite an estimated 30-40 lakh tonnes of sugar being available in excess of domestic demand, the Centre is stepping up efforts to keep sugar prices under control. The Union Food Ministry has urged Maharashtra, Uttar Pradesh and Karnataka to advance the 2026-27 sugarcane crushing season so that fresh sugar reaches the market before the existing stock is exhausted. Sugar mills, however, say an early start will come at a cost. They are seeking special financial assistance to compensate for the likely fall in sugar recovery and the reduction in cane weight that could result from crushing in October. India produced around 280 lakh tonnes of sugar last season. The season began with stocks of nearly 50 lakh tonnes, while annual domestic consumption is estimated at around 280 lakh tonnes. With about 35 lakh tonnes expected to remain in stock by September 30, the Centre wants the new season’s production to start flowing into the market without waiting for the traditional crushing cycle. Maharashtra, Uttar Pradesh and Karnataka account for nearly 80 per cent of India’s sugar production. The Union Food Ministry has therefore written to the chief ministers of the three states, asking them to bring forward the start of the 2026-27 crushing season. The push comes against the backdrop of a sharp movement in sugar prices. Ex-mill prices had earlier climbed to around Rs 68 per kg, pushing retail prices close to Rs 80 per kg. Following a series of measures by the Centre, ex-mill prices have since declined to around Rs 41 per kg. Yet, the government is looking at further measures to bring prices down and ensure that stocks move into the market. One such measure has been the approval of imports of one million tonnes of raw sugar. Since initial applications covered only around eight lakh tonnes, the Centre has invited applications for the remaining quota. It has also reduced the permissible stockholding limit for traders from 400 tonnes to 200 tonnes. The next major point of discussion will be the meeting convened by Union Food and Public Distribution Secretary Sanjeev Chopra with the sugar industry in New Delhi on September 8. The secretaries of Maharashtra, Uttar Pradesh and Karnataka have also been invited. West Indian Sugar Mills Association (WISMA) president B. B. Thombre said the Centre was pushing for crushing to begin around the middle of October. Traditionally, most mills in Maharashtra begin operations around November 15, largely because sugarcane harvesting labour becomes available only after Diwali. The industry is, however, willing to explore an early start between October 20 and 25. But early crushing could have significant implications. According to Thombre, sugar recovery could fall by around 1.5 percentage points, while the weight of sugarcane supplied by farmers could decline by 10-15 per cent. The industry will therefore seek special assistance for cane crushed between October 15 and November 15. At the September 8 meeting, it plans to demand a subsidy of Rs 500 per tonne for sugar mills and Rs 300 per tonne directly for sugarcane farmers.

Careers in the Age of Artificial Intelligence: What Is Safe and What Is Not?

Understanding how different professions may respond to AI can help students, parents, educators, and policymakers make wiser choices for the future.

AI generated image
AI generated image

A quiet anxiety is spreading across classrooms, workplaces, and households across the world. As artificial intelligence becomes increasingly capable in writing reports, analysing data, generating images, and even producing computer code, many people are beginning to ask a simple but unsettling question: Which jobs will survive the age of AI?


For students planning their careers, parents advising their children, and educators designing the next generation of curricula, this question is no longer theoretical. The choices made today may determine how well individuals adapt to a rapidly changing technological landscape.


To better understand this emerging reality, a broad classification of occupations was attempted by grouping jobs into three categories: highly immune to AI, moderately immune to AI, and vulnerable to AI. The purpose of this exercise is not to predict the future with certainty, but to identify patterns in how technology interacts with different kinds of work.


Several international studies have attempted to understand how automation and artificial intelligence may reshape employment. Research from institutions such as Oxford University, the OECD, and the World Economic Forum suggests that while many work activities may be automated, only a relatively small proportion of occupations are likely to disappear entirely.


Most professions consist of multiple tasks. Some of these tasks can be automated, while others continue to require human judgment, creativity, or interaction. In many cases, the future of work will therefore involve humans and machines working together, rather than machines simply replacing humans.


Understanding which human capabilities remain difficult to automate is therefore key to thinking about future careers.


Immune to AI

The first category includes professions that are highly resistant to AI replacement. These occupations typically require human interaction, emotional intelligence, physical dexterity, or complex judgment in unpredictable environments.


Healthcare professions provide clear examples. Doctors, nurses, physiotherapists, and mental health counsellors rely not only on knowledge but also on empathy and trust. Caregivers for children, the elderly, and persons with disabilities similarly perform roles that machines cannot easily replicate.


Skilled trades such as electricians, plumbers, carpenters, masons, and appliance technicians also fall into this category. Their work requires manual skill, situational awareness, and real-world problem solving in constantly changing environments.


Many occupations rooted in community life are equally resilient. Farmers, gardeners, chefs, artisans, musicians, sports coaches, and hospitality workers rely heavily on creativity and human connection. Even traditional roles such as priests, funeral service providers, and cultural performers remain difficult to automate because they are deeply embedded in social and cultural relationships.


Moderately Immune to AI

The second category includes professions that are moderately immune to AI. In these fields, artificial intelligence can serve as a powerful tool, but it cannot replace human expertise entirely.


Scientists, engineers, lawyers, chartered accountants, civil servants, and university professors belong to this group. Software developers and AI engineers themselves also fall into this category. Artificial intelligence can assist them by analysing data, generating code, or identifying patterns, but human reasoning, accountability, and creativity remain essential.


Similarly, many analytical and planning professions rely on interpretation and decision-making. Environmental auditors, energy auditors, policy analysts, and logistics managers must evaluate complex situations and make judgments that carry social and economic consequences. AI can assist their analysis, but the final responsibility for decisions still rests with humans.


Vulnerable to AI

The third category consists of jobs that are more vulnerable to automation. These occupations often involve routine, repetitive tasks or structured information processing.


Data entry operators, clerical staff, telemarketing executives, and certain types of call centre work are typical examples. Activities such as processing forms, maintaining records, or handling standardised transactions can increasingly be performed by algorithms and automated systems.


As digital technologies advance, many such tasks may gradually be absorbed by software systems that operate faster and more efficiently than manual processes.


This transition is unlikely to be abrupt, but rather a steady reallocation of routine work from humans to machines, often unnoticed until its cumulative effects become visible. In many sectors, automation will not eliminate jobs entirely but will redefine them, reducing the need for repetitive functions while increasing the value of oversight and decision-making.


When these categories are examined together, a striking pattern emerges. Many hands-on and community-oriented professions appear more secure than several desk-based clerical jobs.


Skilled trades, caregiving roles, and hospitality services require flexibility, judgment, and human understanding - qualities that machines struggle to replicate.


Another important observation is that resilient careers tend to combine several uniquely human abilities: problem solving, creativity, emotional intelligence, communication, and adaptability. Occupations that depend mainly on routine information processing are the most vulnerable to technological disruption.


It is important to recognize that this classification is not fixed. Technological progress is dynamic, and the relationship between humans and machines continues to evolve.


Some professions that appear secure today may change in the future, while entirely new careers will emerge. A century ago, professions such as software engineering, cybersecurity, and data science did not even exist. The coming decades will undoubtedly create new roles that we cannot yet fully imagine.


The real lesson from this exercise is not simply identifying which job is “safe.” Rather, it highlights the importance of developing capabilities that complement technology instead of competing with it.


This requires a shift in mindset - from viewing machines as rivals to understanding them as tools that can extend human potential.


For students choosing careers, the message is clear: cultivate skills that machines struggle to replicate like curiosity, creativity, empathy, communication, and the ability to solve complex problems in real-world settings. For parents and educators, the challenge is to encourage learning that goes beyond rote knowledge and prepares young people for a world where humans and intelligent machines work together.


Artificial intelligence will undoubtedly reshape the world of work, but it will not eliminate the need for human imagination, judgment, and compassion. As machines become more capable, these distinctly human qualities may become even more valuable.


To make this discussion more concrete, a detailed classification of occupations has been compiled and organized into the three categories described above. Readers who wish to explore the full list of professions and the reasoning behind the classification can download the dataset here:


Such classifications should be viewed as evolving guides rather than final answers. As artificial intelligence advances, the boundaries between categories will continue to shift. What will remain constant, however, is the enduring value of human creativity and judgment in shaping the future of work.


(The author is an ANRF Prime Minister Professor at COEP Technological University, Pune; former Director of the Agharkar Research Institute, Pune; and former Visiting Professor at IIT Bombay. Views personal.)

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