Research Paper Example: Artificial Intelligence and Law: Challenges for Bangladesh’s Legal Framework

Artificial Intelligence and Law: Challenges for Bangladesh’s Legal Framework

1. Abstract

Artificial Intelligence (AI) is transforming legal processes across jurisdictions, presenting both opportunities and regulatory challenges. This paper examines key obstacles within Bangladesh’s legal framework for accommodating advanced AI applications. By employing a qualitative policy analysis supported by comparative insights, the study identifies legislative gaps related to data protection, algorithmic transparency, liability allocation, and institutional governance. Findings highlight the misalignment between current statutes—originally crafted for traditional technologies—and the emergent complexities of AI. The paper concludes with actionable recommendations for updating legal provisions, establishing specialized oversight bodies, and fostering collaboration between regulators, technologists, and civil society to ensure ethical, accountable, and innovation-friendly AI deployment in Bangladesh.

Note: This section includes information based on general knowledge, as specific supporting data was not available.

2. Introduction

2.1 Background of AI in global and Bangladeshi context

Over the last decade, AI technologies—ranging from machine learning algorithms to natural language processing—have become integral to diverse sectors such as finance, healthcare, and public administration. Globally, advanced economies have begun enacting AI-specific guidelines and regulations to address ethical concerns, data privacy, and accountability. In Bangladesh, AI adoption is accelerating in fintech services, government e-governance initiatives, and manufacturing processes. However, existing legal instruments, including data protection and electronic transaction laws, were not originally designed to regulate intelligent, autonomous systems, leading to uncertainty regarding liability, privacy safeguards, and consumer protection.

2.2 Research objectives and questions

This research aims to (1) identify critical gaps in Bangladesh’s current legal framework concerning AI regulation, (2) analyze case studies of AI deployments to understand practical enforcement challenges, and (3) propose policy and legislative reforms tailored to the Bangladeshi context. The primary research questions are: What are the key legal and institutional shortcomings hindering responsible AI deployment? How do international AI regulation approaches inform potential local reforms? Which governance mechanisms can balance innovation incentives with risk mitigation?

Note: This section includes information based on general knowledge, as specific supporting data was not available.

3. Legal and Technological Background

3.1 Overview of key AI technologies

Key AI technologies include supervised and unsupervised machine learning, deep neural networks, natural language processing, and computer vision. These systems can autonomously analyze large datasets, derive patterns, generate predictions, and support decision-making. Emerging subfields such as explainable AI and reinforcement learning pose new regulatory considerations, particularly around algorithmic opacity and adaptive behaviors in complex environments.

3.2 Current Bangladesh legal framework on technology and data

Bangladesh’s primary statutes governing technology include the Digital Security Act, the Information and Communication Technology Act, and draft data protection regulations. These laws address cybercrime, electronic transactions, and basic data privacy, but lack explicit provisions for algorithmic accountability, automated decision-making transparency, and AI-specific liability norms. Enforcement mechanisms are often generalized, leaving regulators without specialized mandates to oversee AI innovations effectively.

Note: This section includes information based on general knowledge, as specific supporting data was not available.

4. Methodology

4.1 Research design and data sources

This study adopts a qualitative, multi-method design combining legal doctrinal analysis with comparative policy review. Primary sources include publicly available statutes of Bangladesh and selected international AI regulation frameworks. Secondary data were collected through policy papers, governmental reports, and expert commentaries. Due to limited AI-specific legislation in Bangladesh, the analysis heavily relies on analogous provisions from established jurisdictions such as the European Union and leading industrialized nations.

4.2 Analytical framework and legal analysis methods

The analytical framework integrates principles from regulatory theory, risk governance, and technology law. Doctrinal methods are used to interpret statutory texts and identify normative gaps, while comparative analysis highlights best practices and potential pitfalls observed in international contexts. Stakeholder mapping and gap analysis techniques support the development of targeted recommendations for legislative reform.

Note: This section includes information based on general knowledge, as specific supporting data was not available.

5. Results

5.1 Identification of regulatory gaps and challenges

The study reveals several critical deficiencies: (1) absence of clear liability regimes for AI-induced harm, resulting in legal uncertainty for developers and users; (2) lack of mandatory algorithmic transparency or reporting standards, undermining accountability; (3) insufficient data protection safeguards especially for sensitive personal data processed by AI systems; and (4) no dedicated oversight body with technical expertise to monitor AI deployments and enforce compliance.

5.2 Case studies of AI applications and legal responses

Analysis of a financial institution’s use of credit-scoring algorithms shows challenges in contesting adverse decisions due to opaque model structures. In public health, AI-driven diagnostic tools faced regulatory delays because existing medical device guidelines did not accommodate software-based risk. These case studies illustrate how outdated regulatory categories impede effective governance and risk management for AI innovations.

Note: This section includes information based on general knowledge, as specific supporting data was not available.

6. Discussion

6.1 Implications for policy and legislation

To address identified gaps, Bangladesh should enact a standalone AI regulation establishing principles for transparency, fairness, accountability, and human oversight. Mandating algorithmic impact assessments, data protection impact assessments, and predefined liability frameworks will enhance legal clarity. Additionally, capacity-building initiatives for regulators and judiciary members are critical to interpret and enforce AI-specific norms effectively.

6.2 Comparative insights from international AI law frameworks

International examples—such as the European Union’s AI Act and related guidelines on “right to explanation”—provide valuable blueprints. These frameworks emphasize risk-based categorization of AI systems, tiered obligations aligned with potential harms, and institutional coordination mechanisms. However, transposition must account for Bangladesh’s socio-economic context, existing institutional capacities, and enforcement realities.

Note: This section includes information based on general knowledge, as specific supporting data was not available.

7. Conclusion

7.1 Summary of findings

This research highlights significant disparities between advanced AI applications and Bangladesh’s current legal regime. Key findings include the absence of tailored liability rules, data protection gaps, and a lack of institutional structures for oversight and enforcement.

7.2 Recommendations for Bangladesh’s legal reform

Recommendations include enacting comprehensive AI legislation, establishing an AI regulatory authority, integrating algorithmic transparency requirements, and developing targeted capacity-building programs for stakeholders.

7.3 Future research directions

Future studies should examine the socio-legal impacts of AI in rural and informal economic sectors, explore public perceptions of AI governance in Bangladesh, and evaluate the implementation of pilot regulatory sandboxes for AI innovation.

Note: This section includes information based on general knowledge, as specific supporting data was not available.

8. References

No external sources were cited in this paper.