AI Chatbots Replace Human Officials Raising Accountability Concerns
Governments are adopting AI chatbots like Albania's Diella for public services, but legal and practical challenges remain unanswered.
The small Balkan country of Albania recently announced an ambitious AI initiative: an AI-powered chatbot named Diella will serve as the country’s Minister for Public Procurement. From roadworks to public health services, Diella will oversee all government tenders, aiming to eliminate corruption, according to Prime Minister Edi Rama.
This trend extends beyond Albania. Estonia is trialing AI judges in civil disputes, while a UK report found over 10 million Britons use chatbots for mental health self-diagnosis.
Motivations Behind AI Adoption
Albania’s move aims to combat widespread corruption, documented in a US Department of State report. Other nations face bureaucratic backlogs—Estonia’s court cases doubled while judge numbers stagnated, and the UK Crown Court had 67,000 pending cases by 2024.
Risks of Unaccountable AI
Despite their efficiency, AI chatbots are fallible. Unlike humans, they lack explainability and accountability. When Air Canada’s chatbot provided false policy information, the company argued it was a "separate legal entity"—though courts ruled against it (Forbes).
- Legal Gaps: No framework exists for AI malpractice. Human experts face professional consequences, but AI’s "black box" decisions evade scrutiny.
- Practical Hurdles: Diella cannot attend cabinet meetings or face legal repercussions, highlighting implementation challenges.
Hybrid Solutions Emerge
Some countries integrate AI as assistants rather than replacements. Germany uses AI to aid judges with administrative tasks (Review of AI Law), while the UK NHS employs chatbots to triage mental health cases faster.
Albania’s AI minister headlines a broader debate: while AI can enhance public services, its unchecked adoption risks eroding trust and accountability.
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About the Author

Alex Thompson
AI Technology Editor
Senior technology editor specializing in AI and machine learning content creation for 8 years. Former technical editor at AI Magazine, now provides technical documentation and content strategy services for multiple AI companies. Excels at transforming complex AI technical concepts into accessible content.