AI development and implementation are increasingly scrutinized for ethical implications and policy needs across various sectors. From healthcare and cybersecurity to finance and even jewel mining, the call for responsible AI practices is growing louder [1, 15, 19].
Ethical AI in Healthcare and Child Safety
The healthcare sector is grappling with unique ethical challenges, particularly concerning pediatric drug regulation [4, 5, 7]. In India, recurring tragedies highlight the urgent need for a robust regulatory framework focused on child safety and transparent reporting [5]. A national registry for Pediatric Clinical Trials (PCT-India) is proposed to collect crucial pharmacodynamic and safety data [4]. Simultaneously, large language models are being benchmarked for personalized, biomarker-based health intervention recommendations, raising questions about data privacy and algorithmic bias [10]. In New Zealand, debates continue over medical ethics and the application of core principles across the entire health system [11, 12].
Beyond pharmaceuticals, AI's role in safeguarding vulnerable populations is also under examination. EviSafe, an AI solution designed to combat violence, prioritizes user trust by employing end-to-end encryption to protect sensitive data [17, 18]. This approach balances innovation with survivor safety, ensuring reliability and accountability [17].
AI Governance and Market Accountability
Calls are growing for increased accountability in the AI market [8, 9]. The argument posits that AI should be governed as a market technology, subject to the same accountability mechanisms as other sectors [8]. Proposals include reversing loosened private-capital rules and increasing disclosure requirements for AI companies [8]. The "capped-profit" and "public-benefit" legal structures of companies like OpenAI and Anthropic are being questioned as potential "accountability shields" [8]. This push for transparency extends to cybersecurity, where AI-driven monitoring and response platforms are becoming essential to combat evolving threats like malware and deepfakes [14]. Addressing the cybersecurity skill gap through education and training is also crucial [14, 15]. In the financial sector, companies are exploring blockchain-enabled tokenization across post-trade operations, emphasizing the need for secure and transparent systems [16]. Even traditional industries like jewel mining are adopting AI for ethical sourcing and sustainable practices [1, 2, 3]. This includes using remote sensing and satellite imaging to minimize environmental impact and ensure ethically sourced gemstones [2].
TL;DR
- The healthcare sector faces urgent ethical considerations concerning pediatric drug safety and the use of AI in personalized interventions.
- Calls are growing for increased transparency and accountability in the AI market, with proposals to regulate AI companies like other market technologies.
- AI is being implemented across diverse sectors, including cybersecurity, finance, and even jewel mining, raising unique ethical and policy challenges.
- Public-private cooperation is essential to combat the misuse of virtual assets and maintain security [19].