AI Act (Q105)
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A policy proposal by ISAIL (under Indic Pacific Legal Research LLP)
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | AI Act |
A policy proposal by ISAIL (under Indic Pacific Legal Research LLP) |
Statements
Utilisation - Specific use cases and applications;
Development - Design, training, and development;
Maintenance - Ongoing support, updates, and modifications
Proliferation - Dissemination and adoption across sectors.
1 reference
Medical AI applications
Financial AI applications
Utilisation - Impact on ethical principles in sectors;
Development - Integration of ethical considerations;
Maintenance - Upholding ethical responsibilities;
Proliferation - Ethical implications of widespread adoption.
Social media content moderation AI
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Utilisation - Effects on individual or collective rights
Development - Incorporation of rights protections
Maintenance - Protection of user rights
Proliferation - Rights-based implications of adoption
Advertising AI with data privacy considerations
Automotive AI with safety and user rights focus
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Autonomy - Independent decision-making
Perception - Understanding sensory information
Reasoning - Problem-solving and conclusion drawing
Interaction - Engagement with humans or other AI systems
Adaptation - Learning from experiences
Creativity - Generation of novel ideas or outputs
Drone delivery system for autonomy
Hotel service robot for perception
Medical diagnostic AI for reasoning
Virtual assistant for interaction
Stock trading AI for adaptation
Music composition AI for creativity
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Scale - Address specific, well-defined problems; Proof-of-concept implementations at a small scale
Inherent Purpose - Provide specialized solutions for individualuse cases; Validate AI technique feasibility in controlled environments
Technical Features - Focused and optimized architectures for specific requirements
Technical Limitations - Constraints on generalizability; Difficulties scaling beyond initial use case
AI chatbot for customer service during a product launch
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Scale - Address specific, well-defined problems; Proof-of-concept implementations at a small scale
Provide specialized solutions for individual use cases; Validate AI technique feasibility in controlled environments
Technical Features - Focused and optimized architectures for specific requirements
Technical Limitations - Constraints on generalizability; Difficulties scaling beyond initial use case
AI chatbot for customer service during a product launch
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Scale - Address specific short-term needs or exploratory applications; Medium scale within relevant sectors
Inherent Purpose - Targeted solutions for emerging or temporary use cases; Potential for future adaptation and expansion
Technical Features - Modular and adaptable architectures for rapid development and deployment
Technical Limitations - Long-term viability uncertainties; Scalability and compliance with changing standards; Challenges in real-world robustness and reliability
Experimental AI for smart city projects (traffic management, pollution monitoring, public safety)
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Scale - Ability to operate across a wide range of domains; Handle large volumes of data and users
Inherent Purpose - Adaptable and applicable to multiple well- defined use cases
Technical Features - Robust and flexible architectures for diverse tasks
Technical Limitations - Challenges in maintaining consistent performance; Compliance issues with sector-specific regulations
Healthcare AI for diagnostics, treatment recommendations, and patient management
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Core Functionality - Cloud-based AI solutions accessed on- demand
Machine learning platform on subscription
Customer service chatbot service
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Core Functionality - End-to-end AI solutions integrating multiple components
Enterprise AI middleware platform
AI in smart manufacturing
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Core Functionality - AI technologies available for testing/early access
AI system for open-ended dialogue made available for preview
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Core Functionality - Standalone AI applications or software
AI-powered home assistant device
Predictive analytics software for businesses
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Core Functionality - AI technologies integrated into existing systems
AI-enhanced smartphone cameras
E-commerce recommendation engine
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AI integrated into underlying digital infrastructure
Traffic management systems
Utility management systems
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Regulatory Framework - 1. Central Government Role - Designate strategic sectors, Establish sector-specific standards, Determine risk classifications; 2. Indian AI Council (IAIC) Responsibilities - Collaborate with regulatory bodies, Develop harmonized guidelines, Ensure compliance with Act provisions
Core Requirements - 1. Safety Measures - Safe operation protocols, Controlled implementation, Harm minimization strategies, Environmental protection; 2. Security Protocols - Access control mechanisms, System manipulation prevention, Data confidentiality, System integrity protection
Reliability Standards - 1. Performance consistency; 2. Accuracy metrics; 3. Testing protocols; 4. Validation processes; 5. Monitoring systems.
Transparency Framework - 1. Algorithm disclosure; 2. Data source documentation; 3. Decision-making process clarity; 4. Stakeholder communication.
Accountability Structure - 1. Clear responsibility lines; 2. Impact assessment; 3. Redressal mechanisms; 4. Remediation procedures
Legitimate Use Compliance - 1. DPDP Act 2023 alignment; 2. Section 7 provisions; 3. Usage restrictions; 4. Compliance monitoring
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