ForumIAS announcing GS Foundation Program for UPSC CSE 2025-26 from 19 April. Click Here for more information.
Source: The post concerns related to generative AI has been created on the article “Gen-Al generates real worries of privacy and accuracy” published in “Live mints” on 12th December 2023.
UPSC Syllabus Topic: GS paper 3- Science and Technology – Developments and their applications and effects in everyday life.
News: The article talks about Google’s generative AI model Gemini, enhancing Bard for handling text, images, and video. It highlights concerns about AI chatbots’ privacy, data use, intellectual property, and reliability. It compares Google’s approach to AI and data privacy with Microsoft’s generative AI model ChatGPT’s methods.
What is Generative AI?
Generative AI refers to artificial intelligence that creates new content, including text, images, music, and videos. It’s powered by large, multi-tasking foundation models requiring minimal training for specific use cases. For example, AI models like DALL-E or DeepDream can generate unique images, OpenAI’s Jukebox can compose new music pieces in various styles, Tools like GPT-3 can write articles, create poetry, or generate code, etc.
Applications of Generative AI
Customer Interactions: Enhances chat and search experiences for better user engagement.
Data Analysis: Processes vast content, generating insights through conversational interfaces and summarizations.
Task Automation: Handles repetitive tasks like responding to RFPs, localizing content in multiple languages, and checking contract compliance.
Content Creation: Capable of generating diverse forms of media for various industries.
Research and Development: Assists in scientific fields by simulating experiments and predicting outcomes.
Personalization: Tailors content and experiences to individual preferences, increasing user engagement in sectors like e-commerce and content streaming.
What are the concerns related to generative AI?
Reliability Issues: AI models can produce unreliable or incorrect results. For example, Bard’s initial version incorrectly stated that the James Webb Space Telescope took the first pictures of a planet outside our solar system, demonstrating AI’s potential for factual errors.
Privacy and Data Use Concerns: AI models are developed using extensive datasets, which might inadvertently include personal details, posing a risk to user privacy. Additionally, the disclaimers for these AI models are often written in complex legal terms. This complexity makes it difficult to understand how they collect and use data, raising concerns about the transparency of their data handling processes.
Intellectual Property and Ownership Issues: There’s uncertainty about who owns the content AI chatbots create, posing legal and ethical challenges.
Accountability for Harmful Outputs: AI chatbots face difficulty in being held accountable for misinformation, offensive content, or hate speech.
What are the initiatives taken to promote AI in India?
- Kamakoti led AI Task Force established for exploring AI applications in various fields.
NITI Aayog’s discussion paper presents a national AI strategy focusing on healthcare, agriculture, education, smart cities and infrastructure, and smart mobility and transportation.
ICMR’s “Ethical Guidelines for Application of AI in Biomedical Research and Health care” sets out 10 key ethical principles for AI in healthcare.
DRDO’s Center for Artificial Intelligence and Robotics (CAIR) engages in AI research.
IIT Kharagpur collaborates with Amazon Web Services for the National AI Resource Platform (NAIRP) to enhance teaching and learning through AI.
SUVAS (Supreme Court Vidhik Anuvaad Software), an AI tool developed for the Supreme Court, helps translate judgments into various regional languages.
What is the status of regulation of AI in India and across the globe?
Question for practice:
Discuss the concerns related to AI chatbots and provide examples to illustrate these concerns.
