Score:
9.5/15
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Topper’s Copy
GS3
Science & Technology
15 marks
As Artificial Intelligence becomes increasingly autonomous, concerns about its safety and reliability are growing. Discuss the major risks associated with autonomous AI systems and suggest measures for their safe and responsible development.
Student’s Answer
Evaluation by SuperKalam
Demand of the Question
- What major safety and reliability risks autonomous AI systems bring
- How to ensure safe and responsible development of AI systems
What you wrote:
Ans→ Autonomous AI systems, from self-driving vehicles to algorithmic decision-makers, act with minimal human oversight. As they enter critical sectors, their failures carry serious social, economic and security costs.
Ans→ Autonomous AI systems, from self-driving vehicles to algorithmic decision-makers, act with minimal human oversight. As they enter critical sectors, their failures carry serious social, economic and security costs.
Suggestions to improve:
- Could briefly define what makes AI "autonomous" (e.g., systems capable of independent decision-making with minimal human intervention in real-time scenarios) to establish technical clarity upfront.
What you wrote:
Major Risks
① Technical failure and opacity :-
systems may fail in unforseen condition as in the 2018 Uber-self-driving fatality while black-box models resist explanation.
② Bias :-
skewed training data can reproduce discrimination in hiring, credit or policing undermining Article 14. As with Amazon's scrapped hiring tool that penalised woman.
③ Accountability Gap :-
Liability is unclear among developer, deployer and user, as in Tesla Autopilot crashes.
④ privacy and security :-
Data hungry systems erode privacy (Putta Swamy Judgement, 2017) Deep fakes (Rashmika Mandana case, 2023) violate dignity, while autonomous weapons threatens stability
⑤ Economic Disruptions :-
The IMF (2024) estimates nearly 40% of global jobs are exposed to AI, widening inequality.
⑥ Loss of control :-
Algorithms can act faster than humans can intervene, as in the 2010 "Flash crash"
Major Risks
① Technical failure and opacity :-
systems may fail in unforseen condition as in the 2018 Uber-self-driving fatality while black-box models resist explanation.
② Bias :-
skewed training data can reproduce discrimination in hiring, credit or policing undermining Article 14. As with Amazon's scrapped hiring tool that penalised woman.
③ Accountability Gap :-
Liability is unclear among developer, deployer and user, as in Tesla Autopilot crashes.
④ privacy and security :-
Data hungry systems erode privacy (Putta Swamy Judgement, 2017) Deep fakes (Rashmika Mandana case, 2023) violate dignity, while autonomous weapons threatens stability
⑤ Economic Disruptions :-
The IMF (2024) estimates nearly 40% of global jobs are exposed to AI, widening inequality.
⑥ Loss of control :-
Algorithms can act faster than humans can intervene, as in the 2010 "Flash crash"
Suggestions to improve:
- Could strengthen the accountability gap with specific legal ambiguity (e.g., in the Tesla case, courts struggled to determine whether the 'Autopilot' label created false confidence, making liability unclear between manufacturer marketing and user negligence)
- Can add India-specific economic context (e.g., NITI Aayog's estimate that AI could add $500 billion to India's GDP by 2025 but sectors like transport and manufacturing face displacement risks requiring urgent reskilling frameworks)
What you wrote:
Measures
① Risk based regulations :-
Stricter norms for high risk uses, as in the EU AI Act.
② Human-in-the loop :-
Mandatory oversight in critical decisions as with SUPACE where AI Assists judge but they decide.
③ Audit and Transparency :-
Explainability and bias audits, with safety testing by the India AI safety Institute
④ clear liability :-
Fix responsibility on deployers, as Air canada was held liable for its chatbot's missinformation.
⑤ Global cooperations :-
Align norms via the 2023 Bletchley Declarations and UN Talks on autonomous weapons.
⑥ capacity building :-
Reskill workers through int initiatives like India AI Future skill.
Measures
① Risk based regulations :-
Stricter norms for high risk uses, as in the EU AI Act.
② Human-in-the loop :-
Mandatory oversight in critical decisions as with SUPACE where AI Assists judge but they decide.
③ Audit and Transparency :-
Explainability and bias audits, with safety testing by the India AI safety Institute
④ clear liability :-
Fix responsibility on deployers, as Air canada was held liable for its chatbot's missinformation.
⑤ Global cooperations :-
Align norms via the 2023 Bletchley Declarations and UN Talks on autonomous weapons.
⑥ capacity building :-
Reskill workers through int initiatives like India AI Future skill.
Suggestions to improve:
- Can elaborate risk categories relevant to India (e.g., high-risk applications could include AI in healthcare diagnostics, credit scoring for financial inclusion, and facial recognition in law enforcement—all requiring stricter oversight under a risk-based framework)
- Could strengthen international cooperation with specific mechanisms (e.g., the 2023 Bletchley Declaration led to the May 2024 AI Seoul Summit establishing the International Network of AI Safety Institutes for coordinated frontier AI testing across partner countries)
What you wrote:
A human-centric accountable and innovation friendly framework can harness AI's potential while protecting rights upholding the constitutional values of Justice, liberty and dignity.
A human-centric accountable and innovation friendly framework can harness AI's potential while protecting rights upholding the constitutional values of Justice, liberty and dignity.
Suggestions to improve:
- Could add a forward-looking dimension (e.g., As India drafts its Digital India Act 2.0, embedding explainability standards and mandatory algorithmic impact assessments can position the country as both an AI innovator and a responsible governance model for the Global South)
Your answer demonstrates strong command over AI governance issues with excellent use of contemporary examples (SUPACE, Air Canada chatbot, Rashmika case) and constitutional grounding. The structure systematically addresses both demands. Minor improvements in explaining legal ambiguities and adding India-specific economic context would further strengthen the response. Well-done overall!
Demand of the Question
- What major safety and reliability risks autonomous AI systems bring
- How to ensure safe and responsible development of AI systems
What you wrote:
Ans→ Autonomous AI systems, from self-driving vehicles to algorithmic decision-makers, act with minimal human oversight. As they enter critical sectors, their failures carry serious social, economic and security costs.
Ans→ Autonomous AI systems, from self-driving vehicles to algorithmic decision-makers, act with minimal human oversight. As they enter critical sectors, their failures carry serious social, economic and security costs.
Suggestions to improve:
- Could briefly define what makes AI "autonomous" (e.g., systems capable of independent decision-making with minimal human intervention in real-time scenarios) to establish technical clarity upfront.
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