In the dynamic era of Artificial Intelligence, Bangladesh embraces both transformative opportunities and challenges. AI’s profound impact on industries, economies, and societal structures demands a strategic approach. Revolutionizing the global landscape, AI brings unprecedented innovation, requiring a policy framework to harness its potential and mitigate risks. Introduced in 2020, the National Artificial Intelligence Strategy lays this foundation. Now, with the National AI Policy, the government reaffirms its commitment to navigating AI with wisdom and ethics. Aligned with ‘Vision 2041’ for a ‘Smart Bangladesh,’ AI becomes pivotal across sectors, driving innovation, economic growth, and inclusive development while addressing legal, ethical, and societal dimensions effectively.
Table of Contents
Vision and Objectives
Vision
Establishing Bangladesh as a pioneer in AI innovation and adoption, creating a Smart Bangladesh that leverages AI technologies for the well-being of all citizens, economic prosperity, and sustainable development.
Objectives
In alignment with the vision, this policy facilitates the transformation of ‘Digital Bangladesh’ to ‘Smart Bangladesh’, to achieve the following objectives:
- To accelerate equitable economic growth and productivity through AI-driven optimization, forecasting, and data-driven decision-making.
- To ensure efficiency and accessibility of public services through AI-enabled personalization.
- To adopt data-driven policy making in every sector through AI-supported analytics and insights.
- To nurture a skilled workforce that can utilize and build AI technologies through embedding AI in education and skills development who will meet the demands of the future.
- To foster a culture of AI research and innovation through appropriate public and private funding.
- To ensure development and adhere to a robust ethical framework by establishing regulatory measures that uphold human rights in AI development and deployment.
Key Principles for AI Implementation
Having a unified set of guidelines is crucial to direct all stakeholders toward the responsible use of AI. The development and use of AI technologies in Bangladesh shall be guided by the following principles that are consistent with Bangladesh’s national values, visions, and goals:
Social Equity, Equality, and Fairness
Ensuring equitable access, equal opportunities, and inclusivity, and avoid bias in AI implementation to benefit all citizens regardless of religion, gender, ethnicity, geographic location, socioeconomic status, or physical abilities, by adhering to the latest user-centered design practices and accessibility standards.
Transparency and Accountability
Ensuring transparency and lines of accountability in the collection, storage, and usage of data in AI systems to ensure that the decision-making process is explainable and interpretable, allowing users and stakeholders to understand how AI arrives at decisions, and can challenge them.
Safety, Security, and Robustness
Ensuring that AI systems must be safe, ethical, secure from malicious use, robust against errors and biases, and potential risks be continually assessed and managed and when procuring technologies across all technology providers.
Sustainability
Promoting a circular economy approach, developing AI technologies that minimize their carbon footprint and promote green AI practices.
Partnership and Collaboration
Promoting local and global multi-stakeholder engagement to create a vibrant AI research, implementation, and risk-mitigation ecosystem and to leverage combined expertise and resources.
Human-Centered AI
Ensuring AI technologies uphold the rule of law, human rights, dignity, values, and preferences, including human intervention scopes and human oversight in AI systems where necessary.
Find all about the AI Law in Bangladesh.
Priority Sectors for AI Integration
Smart Public Services, Governance, and Judiciary
- AI systems will improve public service efficiency, ensure personalized service delivery, enhancing citizen-friendly services through automation and predictive processes.
- AI technologies will be applied with a whole-of-the-government architecture by leveraging data from multiple departments to enhance service delivery, coordination, and decision-making.
- AI systems will facilitate an advanced digital ecosystem by enabling interoperability through data standardization and sharing protocols.
- AI technologies will improve legal processes, streamline judicial efficiency, and enhance access to justice, legal information, and legal aid services.
- AI tools will be deployed for comprehensive court management, including case processing, tracking, scheduling, legal research, document analysis, prediction of case outcomes, transcription, translation of proceedings, and providing legal recommendations to assist the court.
Telecommunication, Data Governance, and Surveillance
- AI technologies will strengthen telecommunication networks, digital infrastructure, data governance, data protection, and cybersecurity.
- Responsible data sharing and interoperability will foster AI-driven decentralized data governance solutions.
- AI platforms will strengthen the linkage of public and private data in a secure open data ecosystem, establishing a foundation for transparent and accessible data utilization.
- Scalable and secure access to high-performance computing resources will be provided for training and building AI models, allowing organizations to rent or import necessary hardware.
- AI-friendly digital infrastructure, including national computing power, distributed cloud systems, interoperable applications, and machine-readable legislation, will be developed.
- AI systems will be implemented for comprehensive threat detection, enhancing national security, intelligence, and surveillance capabilities, including the analysis of various surveillance feeds for targeted detection, alert generation, and incident response.
- AI systems will be employed to identify early warnings or emerging trends which may have negative implications through data amalgamation, source verification, and hypothesis generation.
Agriculture
- AI systems can be harnessed to improve agricultural productivity.
- AI models will be used to predict market demand and supply to optimize agribusiness planning, including planting and harvesting schedules.
- AI systems will be integrated to conduct critical analysis for precision agriculture techniques.
- AI initiatives will monitor livestock and fisheries health for animal well-being and minimize economic risks.
- AI technologies will be deployed to enhance crop protection by predicting disease outbreaks and enabling early intervention measures to safeguard yields.
Environment, Energy, and Climate Change
- AI systems can be harnessed to improve weather forecasts, environmental monitoring, and energy sustainability.
- AI will be used in water resource management, including monitoring, and optimizing water supply, distribution, and conservation efforts.
- AI systems will be integrated to conduct critical analysis for sustainable practices, climate-focused investment, and risk mitigation.
- AI systems will optimize renewable energy production and distribution, promoting clean energy adoption and reduced reliance on fossil fuels.
- AI technologies will provide personalized recovery strategies for various environmental zones and disaster-prone areas.
Smart Cities, Transportation, and Mobility
- AI-based urban planning will optimize infrastructure development, resource allocation, and support the development of sustainable and inclusive smart infrastructure for cities and villages.
- AI-driven solutions will be implemented for efficient waste management, recycling systems, and environmental monitoring to enhance sustainability.
- Introduction of AI-driven public safety measures, including smart surveillance, will enhance security and emergency response capabilities.
- AI systems will be used to optimize traffic flow, reduce congestion, and incorporate efficient traffic signal control and smart parking management.
- AI systems will be used to enhance road safety, pedestrian safety, and prevent accidents by analyzing traffic patterns and pedestrian behavior.
- AI technology will integrate intelligent scheduling, real-time monitoring, and predictive maintenance in public transportation.
- AI will promote the adoption of electric and autonomous vehicles.
Finance, Trade, and Economy
- AI-powered solutions shall be used to foster economic growth, financial stability, and international trade.
- AI shall be used for risk assessment and fraud detection in financial services.
- AI systems for trade facilitation and supply chain optimization will boost international trade.
- AI-driven platforms will be used for personalized financial advice, improving financial literacy and empowering citizens to make informed investment decisions.
- AI-based solutions will facilitate credit scoring and lending, promoting financial inclusion.
- Tax collection processes and revenue management shall be optimized through AI-driven solutions like tax compliance monitoring and fraud detection.
- AI shall be used in revenue collection, automated reporting, data processing, and analysis.
- AI algorithms for predictive analytics will forecast revenue trends, facilitating better fiscal planning and resource allocation.
- AI-driven economic forecasting, policy analysis, and impact assessment will inform evidence-based adjustments, facilitating data-driven decisions and policy formulation.
Manufacturing and Industrial Transformation
- AI technologies will be adopted for predictive maintenance, process optimization, and quality control in the manufacturing and industrial sectors.
- AI solutions will be implemented for inventory management, supply chain optimization, and market dynamics.
- AI-driven robotics and data analytics will be used for insights into productivity bottlenecks and manufacturing processes to increase efficiency, reduce waste, and improve quality.
- AI will promote advanced automation, intelligent control systems, and smart factory concepts, creating adaptable and efficient production environments.
- AI systems will facilitate the integration of IoT devices and sensors into manufacturing processes, enabling real-time monitoring and data-driven decision-making for enhanced productivity and reduced downtime.
- AI technologies will be adopted to forecast market trends, consumer preferences, and demand patterns, enabling manufacturers to align their production strategies and optimize inventory management.
- AI-driven digital twins and simulation models will be employed to design and optimize manufacturing processes, allowing for virtual testing, process refinement, and identification of potential improvements before implementing physical changes.
Education
- AI-driven adaptive learning platforms will be developed to personalize education, enhance student engagement, and improve learning outcomes.
- AI-based tools for curriculum development, teacher training, and administrative tasks will streamline educational processes.
- AI-powered assessment and feedback systems will be implemented to provide timely and personalized feedback to students.
- AI technologies will support inclusive education, catering to diverse learning needs and promoting equal access to quality education.
- AI-driven career counseling and skills development platforms will guide students toward suitable career paths and training opportunities.
- AI systems will facilitate educational research, data analysis, and evidence-based policy formulation.
- AI-enabled virtual classrooms and e-learning platforms will provide remote learning opportunities and expand access to quality education for underserved regions.
- AI-driven natural language processing tools will support language learning and translation services, enabling students to access educational resources in their preferred languages.
Healthcare and Wellbeing
- AI aids precise disease detection, chronic disease management, and personalized treatment.
- AI improves telemedicine, enabling remote consultations and real-time health monitoring.AI streamlines healthcare operations: scheduling, resource allocation, inventory, and data management.
- AI-driven chatbots enhance patient monitoring, especially in mental health, offering timely support.
- AI language translation services ensure care for patients with diverse linguistic backgrounds.
- AI detects healthcare billing and insurance fraud.
- AI advances robot-assisted surgery, medical imaging, drug discovery, and alerts for drug dosage and interactions.
Science, Technology, Research, and Innovation
- Scientific research, technological innovation, and AI-driven breakthroughs will collaborate closely with academia and research institutions.
- AI will simulate lab experiments, making science education more accessible and cost-effective with virtual labs.
- AI extracts, summarizes, and analyzes info from scientific literature, patents, and technical docs, boosting research efficiency.
- AI tools track market trends and consumer sentiment, guiding funding decisions and spurring innovative product development.
- AI fosters creativity and content innovation, optimizing product designs and solving problems creatively.
- AI safeguards products by enforcing restricted access to harmful content based on age, values, and preferences.
- AI blends systems for regulation, copyright protection, and privacy restrictions.
Policy Implementation and Governance
Governance Structure
The Information and Communication Technology Division, in collaboration with ministries, industry, academia, and civil society, will establish the National Artificial Intelligence Center of Excellence (NAICE). NAICE will:
- Coordinate and monitor AI initiatives using key performance indicators.
- Evaluate social, economic, and environmental impacts of AI initiatives, guiding adjustments for maximum benefits and risk mitigation.
- Form a High-Level National AI Advisory Council to guide sectoral AI initiatives (see Annexure 1 for council members).
- Facilitate collaboration among government agencies, industry, academia, and civil society to foster a holistic AI ecosystem.
- Ensure regulatory measures are proportionate to risks, balancing innovation encouragement.
- Establish a monitoring committee to oversee ethical AI conduct in public and private sectors.
- Implement mechanisms for AI compliance with regulations through regular audits and assessments.
Regulatory Framework
The legal and regulatory frameworks for AI policy are crucial. The National AI Strategy will include:
- A framework outlining goals, policies, and initiatives for AI development, updated regularly.
- AI ethics guidelines to ensure responsible and ethical AI use.
- Data retention policies covering governance and ownership.
- Standardization and certification guidelines for AI practices, focusing on interoperability.
- Legal framework for data accessibility, including a national open data platform.
- Intellectual Property (IP) framework for AI models, works, source code, and data.
- Biennial updates to the National AI Strategy to align with global AI advancements.
Implementation Plan for Ministries and Departments
The Information and Communication Technology Division will enable policies overall. Ministries and divisions will facilitate within their domains. They will plan AI initiatives with:
- Defining vision and time-bound AI goals.
- Identifying stakeholders: government, businesses, academia, research, startups.
- Analyzing AI’s current state, strengths, weaknesses, challenges, opportunities.
- Creating a roadmap and specific action items.
- Monitoring, evaluating, and adjusting implementation.
- Prioritizing initiatives via the AI Advisory Council.
- Developing AI literacy and skills through capacity-building programs.
- Implementing flexible governance for new technology advancements.
Implementation Plan for Academia
The academia stakeholders will implement the following steps:
- Integrate AI into academic curriculum and specialized programs, covering ethical, legal, and socio-economic implications.
- Establish AI research centers in all public and private universities.
- Organize conferences, seminars, workshops, public awareness programs, and other AI-related events.
- Establish an AI research hub by the University Grants Commission to support, promote, and collaborate on AI research, providing training for students and professionals.
- Identify research areas with potential for private sector investment and facilitate co-investment opportunities.
Private Institutions, Businesses, and Industries
Implementation plan for Private Institutions, Businesses, and Industries:
- Stakeholders align with national AI policy.
- Adopt responsible AI practices for public-sector procurement and high-risk AI.
- Implement ‘single-window clearance’ for AI projects.
- Develop AI training programs with industry.
- Offer AI internships and apprenticeships for students.
- Encourage private investment in AI research through incentives and partnerships.
Investment and Funding
Strategies for AI funding and investment include:
- Government funding for AI R&D across ministries.
- Corporate funding via CSR or other means.
- Tax benefits for AI in research, education, and infrastructure.
- Efforts to attract local and foreign investments.
- Building partnerships for global AI knowledge exchange.
Challenges and Mitigation Approaches
AI Risks and Trustworthiness:
- Ensure AI systems enable human decision-making, respecting fundamental rights and oversight.
- Implement fallback plans for safety, accuracy, reliability, and reproducibility.
- Prevent unlawful or unfair data usage and unintended bias.
- Document datasets, processes, and algorithms transparently.
- Establish audit methods for algorithms, data, and design processes.
Risk Management Framework:
- Evaluate AI products against requirements transparently.
- Ensure diverse profiles for fair assessment.
- Assess risks during procurement.
- Monitor AI initiatives periodically for new risks.
- Set national standards for risk management.
Privacy:
- Train models with minimal sensitive data.
- Require valid consent for personal data usage.
- Use encryption, anonymization, and aggregation.
- Allow users to flag privacy issues during data processing.
- Assess dataset types and scopes by experts.
Data Security and Cybersecurity:
- Address system vulnerabilities and hacking risks.
- Foster inter-agency cooperation for system security.
- Define governance procedures and recovery strategies.
- Establish incident response protocols and training.
- Conduct regular security audits to mitigate weaknesses.
Conclusion
By adopting a comprehensive and inclusive approach to AI policy, Bangladesh can harness the transformative potential of AI to address its societal challenges and drive sustainable development. The successful implementation of the AI policy will require collaboration and coordination among stakeholders, investment in capacity building and education, and the establishment of a robust regulatory framework. With these efforts, Bangladesh can position itself as a leader in AI innovation and create a future that benefits all its citizens.
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