GS Paper 4 (Ethics)Ethics in technology and environmentUPSC CSE Mains 2024
There is a technological company named ABC Incorporated which is the second largest worldwide, situated in the Third World. You are the Chief Executive Officer and the majority shareholder of this company. The fast technological improvements have raised worries among environmental activists, regulatory authorities, and the general public over the sustainability of this scenario. You confront substantial issues about the business's environmental footprint. In 2023, your organization had a significant increase of 48% in greenhouse gas emissions compared to the levels recorded in 2019. The significant rise in energy consumption is mainly due to the surging energy requirements of your data centers, fuelled by the exponential expansion of Artificial Intelligence (AI). AI-powered services need much more computational resources and electrical energy compared to conventional online activities, notwithstanding their notable gains. The technology's proliferation has led to a growing concern over the environmental repercussions, resulting in an increase in warnings. AI models, especially those used in extensive machine learning and data processing, exhibit much greater energy consumption than conventional computer tasks, with an exponential increase. Although there is already a commitment and goal to achieve net zero emissions by 2030, the challenge of lowering emissions seems overwhelming as the integration of AI continues to increase. To achieve this goal, substantial investments in renewable energy use would be necessary. The difficulty is exacerbated by the competitive environment of the technology sector, where rapid innovation is essential for preserving market standing and shareholders' worth. To achieve a balance between innovation, profitability and sustainability, a strategic move is necessary that is in line with both, business objectives and ethical obligations. a) What is your immediate response to the challenges posed in the above case? b) Discuss the ethical issues involved in the above case. c) Your company has been identified to be penalized by technological giants. What logical and ethical arguments will you put forth to convince about its necessity? d) Being a conscience being, what measures would you adopt to maintain balance between AI innovation and environmental footprint?
Based on 25 evaluated answers to this question on CollectorBabu: here is what aspirants most often missed, the mistakes that cost marks, and a model answer.
What most aspirants missed
- Specific renewable targets with timelines (e.g., PPAs, RE100, 40% by 2025, 70% by 2027) to show how the 2030 net-zero goal will be met
- Concrete AI efficiency techniques such as model pruning, quantisation, knowledge distillation and parameter-efficient fine-tuning
- Dual-use dilemma and intergenerational equity in part (b), with ethical principles named
- Clear distinction between a regulatory fine and competitive disadvantage in part (c), with penalty logic tied to ethics
- KPIs such as PUE and carbon per training run to track progress
- Stakeholder engagement plan with employees, investors, regulators and communities
Common mistakes
- Defending the company against penalties instead of arguing why penalties are necessary
- Generic immediate response without a data audit, pause on new projects or time-bound steps
- Listing ethical issues without naming the principle behind each, such as utilitarianism, deontology or the precautionary principle
- Giving only two measures in part (d) and repeating the same green bonds point across parts
- Using weak justifications such as 'everyone else is doing it' instead of accountability and fairness
What the better answers did
- Quantifying the problem with the 48% rise and the 2030 net-zero target from the start
- Linking each ethical issue to a named principle and a concrete example
- Giving phased targets, KPIs and reporting mechanisms in part (d)
- Framing penalties as accountability and a level playing field, linked to ESG disclosure norms
Introduction
Open by quantifying the 48% rise against the 2030 net-zero target and state that you will act immediately while protecting innovation.
Conclusion
End by tying the balance between profit and sustainability to your own accountability as CEO and to a clear next step, such as the emergency board meeting.
Model answer
A 48% rise in emissions since 2019 is incompatible with our 2030 net-zero pledge. As CEO, I will act immediately, protect long-term sustainability and keep innovation going, because growth and sustainability must be pursued together.
(a) Immediate response
- Convene an emergency board meeting and pause approval of new energy-intensive AI projects until a green transition plan is finalised.
- Complete an efficiency audit of all data centres within 90 days, reporting PUE (Power Usage Effectiveness) and carbon per training run for every AI model.
- Shift to energy-efficient models through pruning, quantisation and knowledge distillation, and move non-urgent workloads to carbon-aware schedules.
(b) Ethical issues
- Intergenerational equity: future generations bear the climate cost of today's AI boom.
- Dual-use dilemma: AI brings benefits but carries environmental costs that must be weighed through utilitarian analysis.
- Transparency versus greenwashing: published emissions must match net-zero claims.
- Environmental justice: siting data centres in water-stressed communities breaches fairness, linked to Article 48A and the fundamental duty under Article 51A(g).
- Precautionary principle: AI expansion is a choice, not technological inevitability.
(c) Case for penalties
- Polluter pays principle: penalties make emission costs internal, deter excess and level the playing field among firms.
- Accountability and precedent: penalties fund green R&D and renewable procurement, and signal to the industry that ESG commitments are enforceable.
- Fairness: large emitters that have historically contributed more must lead, in the spirit of Common But Differentiated Responsibilities; ABC accepts this and will report progress under EU CSRD-style disclosure.
(d) Measures
- Power Purchase Agreements and RE100 membership: 40% renewable supply by 2025, 70% by 2027, 100% by 2030.
- Liquid cooling, server virtualisation and energy-efficient AI chips, with a target of 30% lower computation per model.
- Carbon-per-training-run KPIs, quarterly sustainability reports and third-party audits.
- Open-source energy-efficient AI frameworks with industry peers; carbon offsets in Third World community projects used only as a supplement.
Sustainable AI is a competitive advantage. As CEO, I will accept lower short-term margins to secure long-term trust, and lead the industry towards net zero.
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