Ethical Considerations in AI-driven Access to Information

Syllabus: GS 3/Science and Tech 

In Context

• Artificial Intelligence (AI)  is celebrated as a transformative equalizer, enhancing how individuals access, interpret, and share knowledge.
  • However, concerns regarding bias, transparency, and accountability persist.

About Artificial Intelligence (AI)

• AI is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy.
• It  results from decades of advancements in data processing and machine learning.
• It has diverse applications, including translation tools, chatbots, content filtering, and censorship.

Transformative Potential of AI

• Democratising Information: AI overcomes historical barriers to information shaped by geography, language, and literacy.
• Access to Healthcare Information: AI tools like a signing avatar and the digital health worker Florence improved healthcare access during the pandemic.
  • S.A.R.A.H. Launch: The AI-powered digital health promoter helps users understand health risks and make informed decisions.
• Access to Education : Platforms like Khan Academy and Byju’s use AI to tailor education to individual needs.
  • Coursera translated courses into Hindi, increasing accessibility.
  • Language Proficiency Programs like  EBS’s AI-Pengtalk program improved English skills for students in Korea.
• Access to Government Services : Chatbot Jugalbandi Developed by Microsoft and AI4Bharat, this chatbot provides government service information in 10 Indian languages.
• Enhanced Information Discovery : National Digital Library Launched in 2019, it provides access to millions of digital resources with AI features.
  • Mission Bhashini aims to build an Indian language tech ecosystem for multilingual access to digital services.

Ethical Challenges in AI Development

• AI is viewed as a great equaliser with applications in translation, chatbots, and content filtering, it also raises critical concerns regarding
  • Algorithmic Bias: AI can replicate or amplify biases present in training datasets, leading to unequal information access.
  • Privacy Concerns: AI relies on personal data, raising issues of misuse and unauthorized access.
  • Accountability: Unclear responsibility for AI system failures complicates accountability.
  • Transparency and Explainability: AI often operates as a “black box,” making it difficult for users to understand decision-making processes.

Conclusion and Way Forward 

• AI-driven information access presents immense opportunities for improving how people find and consume information. 
• However, these opportunities come with ethical challenges that must be addressed to ensure that AI systems truly align with the spirit of universal access to information. 
• Inclusivity, transparency, privacy, and accountability must be at the centre of every stage of development and deployment to ensure that we create an equitable and reliable information ecosystem for all. 
• It is only by prioritising ethical AI that can we realise its full promise as a tool for universal information access.

Source :ORF