24 March 2023

DAILY QUESTIONS & MODEL ANSWERS

Q1. A growing urban and young population is predicted to increase the demand for processed food products in the coming years. The food processing sector in India must invest in the necessary infrastructure to meet the demand. Examine. (250 words)

 Paper & Topic: GS III – Food Processing Sector

 Model Answer:

Introduction:

• Basic food preparation, the conversion of a food product—often raw—into another form (such as making preserves from fruit), as well as preservation and packaging techniques—are all regarded as components of food processing. To produce food products with a long shelf life, food processing typically uses harvested crops or animal resources.
• In order to effectively preserve food ingredients, extend their shelf lives, and enhance their quality, it includes the process of adding value to products through techniques like preservation, the addition of food additives, drying, etc.
• By the middle of the century, feeding the 10 billion people on the earth will be incredibly challenging.

Body:

The reach of FPI in India:

• India is the second-largest producer of fruits and vegetables in the world, behind China, yet just 2% of that supply is processed.
• Indian producers of coffee, tobacco, spices, seeds, and other goods rank in the top 5. It would be simple for us to outperform all other food suppliers internationally with such a large supply of raw materials.
• Despite having a sizable manufacturing base, processing is only minimal (less than 10%). Processing affects 8% of marine goods, 35% of milk, 6% of poultry, 2% of fruits and vegetables. This business continues to face significant challenges due to a lack of sufficient processable types.
• Economic Outlook for 2020: Over the past six years, which ended in 2017–18, the Food Processing Industries sector has grown at an average annual growth rate of roughly 5.06 percent.
• Employment: As of the 2016–17 annual survey of industries, 54 lakh people were employed in the recognised food processing sector (whereas unregistered FPOs supports 51.11 lakh workers)
• Beneficiaries of the SAMPADA programme include over 37 lakh farmers and 5.6 lakh direct and indirect jobs, according to estimates (ES 2020 data).
• Reducing Distress Migration: You can prevent people from moving to cities from rural areas by creating jobs there. solutions to urbanisation issues.

The food processing sector in India faces the following difficulties:

• The majority of the demand in India for processed foods comes from urban areas.
• Here is a rundown of the pressing issues:
• Due to dispersed ownership, there was little marketable excess.
• Lack of automation leads to poor agricultural production
• high seasonality in raw materials
• The perishability of raw materials and improper supply chain intermediation are the main causes of their lack of availability.
• In the end, this makes it challenging to process food and export it.
• More than 30% of the food is lost at the farm gate due to inadequate cold chain infrastructure.
• The NITI Aayog reported that post-harvest losses total more than Rs 90,000 crore annually.
• Supply is unpredictable due to a lack of all-weather routes and connectivity.
• Unorganized sectors make up a significant portion of the food processing business, accounting for over 75% of all product categories. As a result, the current production system is inefficient.
• Moreover, the majority of processing in India can be categorised as primary processing, which adds less value than secondary processing.
• Due to this, India’s agricultural exports as a percentage of GDP are very low compared to the rest of the world, despite being one of the world’s greatest producers of agricultural goods.

To overcome the difficulties:

• PMKSY is being implemented by the Ministry of Food Processing Industries (MoFPI) (Pradhan Mantri Kisan SAMPADA Yojana) (Pradhan Mantri Kisan SAMPADA Yojana). PMKSY seeks to modernise processes, augment agriculture, and reduce agri-waste.
• Massive food parks.
• Infrastructure for value addition, preservation, and the integrated cold chain.
• Development or expansion of facilities for food processing or preservation.
• Infrastructure for Clusters of Agro processing.
• Creating Backward and Forward Linkages Scheme.
• Policy for Foreign Direct Investment (FDI): With the automated route, FDI is permitted up to 100% in the food processing sector.
• Agriculture Export Zones Agri Export Zones, a new idea, were introduced in 2001 to boost the export of agricultural products. The cluster approach to identifying potential products, the geographic area in which these products are grown, and adopting an end-to-end approach to integrating the entire process from the stage of production until it reaches the market have all been nominated by APEDA as the Nodal Agency to coordinate the efforts (farm to market) (farm to market).

Conclusion:

• Future prospects for the food processing industry are bright, assuming proper government assistance. The largest outlay for an urban Indian household is food. The average household spends about 35% of its overall consumption budget on food. As previously indicated, food processing has a number of benefits unique to the Indian environment. It has the power to rescue millions from malnutrition. Government must work hard to build the economy in a way that protects small businesses while also luring high-value domestic and international investments.

Q2. Although having great technological potential, artificial intelligence raises ethical issues as well. Explain with specific examples. (250 words)

 Paper & Topic: GS IV – Ethics related issues

 Model Answer:

Introduction:

• Technology is frequently viewed as a helping hand, or even better, as a way to a better world. But before doing any of that, we must establish the ethics included therein so that we may establish a moral foundation from which to work. In the case of artificial intelligence, this is particularly true.

Body:

• Techno ethics emphasises identifying the moral applications of technology, guarding against its abuse, and developing shared norms to direct future developments in technical development and use for the good of society. It sees technology and ethics as socially embedded enterprises.

Background: AI is developing quickly:

• AI has advanced at an unheard-of rate in the last ten years, defeating human champions in the game Jeopardy in 2011, defeating the top Go player in the world, and even decoding proteins.
• Already, AI has improved access to credit, boosted corporate productivity, increased crop yields, and sped up and improved cancer detection.
• By 2030, it might add 14% to global GDP and more than $15 trillion to the global economy. More than 2,600 “AI for good” use cases have been uncovered by Google globally.
• New ethical and legal issues are emerging as AI develops. As data is introduced into AI, it analyses it and makes inferences based on what it has learnt or been trained to do.
• Despite its many advantages, it might be dangerous for people, the privacy of their data, and the possible results of their actions. Organizations and policymakers are developing guidelines for guaranteeing the responsible and ethical use of AI in an effort to reduce the likelihood of such results.

Value-based global AI governance framework is required:

• First, algorithms have values, whether they are dynamic or learned by machine learning. Their creators’ and history’s biases are embodied in the data that underlies them as well as the formulas that enable them to think, act, and change across time.
• This implies that algorithms should be subject to the same kind of global ethical framework that controls behaviour by people and governments, i.e., something akin to the Universal Declaration of Human Rights.
• Human life will become more effective thanks to artificial intelligence.
• Yet in this case, we must be careful not to confuse effectiveness with morality; just because something is more effective does not imply that it is ethically superior.
• People can create weapons that are more effective at killing people and destroying things, for instance, but it does not imply that they are good or that they will be used for good. Weapons always represent some sort of harm to society.
• Existing regulations will become obsolete as AI develops in its uncharted territories.
• The issue right now is that a number of AI applications have been utilised by organisations or consumers, only for them to subsequently realise that the project was unethically inappropriate. A prime example is the creation of a fully autonomous AI-controlled weapon system, which is coming under fire from several countries around the world and even the UN.
• Because AI models require data sets for their training and development, data protection presents another difficulty. The usage history and data tracking that could jeopardise a person’s identification are frequently used to collect this data.
• Autonomous vehicles are another illustration.
• It operates according to the algorithm that was provided to it. Now, the car must choose whether to veer left or right in a hypothetical situation. Yet, there is always collateral damage, such as harm to a pedestrian or a school bus carrying youngsters.
• Can a sensible choice be made in this situation? It is impossible to pick and choose whose life should be saved or to assign a higher value to one life over another.

Conclusion:

• Any new technology that improves our society or enterprises frequently has a possible downside that is viewed with distrust and mistrust. More oversight is required because of the looming ethical, transparent, and security threats that come with AI’s disruptive potential. Only once governance and policies regulating its usage have been developed can AI be deployed safely.