What is a major ethical concern related to AI?
Yes, India needs a National Security Strategy (NSS) to ensure its security, stability and prosperity. An NSS would provide a comprehensive framework for addressing various security challenges, prioritizing national interests and allocating resources effectively. Challenges in implementing an NSS - Read more
Yes, India needs a National Security Strategy (NSS) to ensure its security, stability and prosperity. An NSS would provide a comprehensive framework for addressing various security challenges, prioritizing national interests and allocating resources effectively.
Challenges in implementing an NSS –
- Coordination and integration challenges in implementing NSS arise from fragmented security agencies, ministries and stakeholders requiring unified efforts and strategies.
- Bureaucratic and institutional hurdles in implementing NSS include entrenched interests, slow decision making and outdated structures hindering effective policy formulation and execution.
- Resource allocation challenges in implementing NSS involve prioritizing competing demands optimizing limited resources and allocating budgetary funds to address diverse security threats.
- Balancing competing interests in implementing NSS involves reconciling national security with economic, social and political priorities while addressing diverse stakeholder demands.
- Ensuring flexibility and adaptability in implementing NSS involves responding to emerging threats evolving technologies and changing global circumstances while maintaining strategic coherence.
- Cybersecurity and technology challenges in implementing NSS involve protecting critical infrastructure, addressing cyber threats and leveraging emerging technologies like AI and drones effectively.
- Regional and global partnership challenges in implementing NSS involve building and sustaining alliances managing divergent interests and navigating complex geopolitics effectively.
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One major ethical concern related to AI is bias and fairness. AI systems can inadvertently reinforce and amplify biases present in the data they are trained on, leading to unfair and discriminatory outcomes. For example, an AI recruitment tool used by a major tech company was found to be biased agaiRead more
One major ethical concern related to AI is bias and fairness. AI systems can inadvertently reinforce and amplify biases present in the data they are trained on, leading to unfair and discriminatory outcomes.
For example, an AI recruitment tool used by a major tech company was found to be biased against female candidates. The tool was trained on historical resume data that predominantly featured male candidates, resulting in the system favoring men over women for technical positions. This instance highlights the challenges of ensuring fairness in AI-driven hiring processes.
Another significant issue is seen in facial recognition technology, which has been criticized for its inaccuracies and biases. Research has shown that such systems often perform less accurately on darker-skinned and female faces compared to lighter-skinned and male faces. This discrepancy underscores the importance of using diverse and representative training data to prevent reinforcing societal inequalities.
To address these concerns, it is crucial to implement robust testing, utilize diverse datasets, and ensure transparent and accountable methodologies in AI development. Fairness in AI is essential for building trust and ensuring that these technologies serve all individuals equitably.
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