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[🇧🇩] Artificial Intelligence-----It's challenges and Prospects in Bangladesh

[🇧🇩] Artificial Intelligence-----It's challenges and Prospects in Bangladesh
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G Bangladesh Defense

AI can transform our health system, but are we ready for it?

Sumit Banik

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Visual: Representational image generated through AI

Bangladesh’s healthcare sector has long grappled with severe structural limitations—acute physician shortages, a massive rural-urban divide, rising burdens of non-communicable diseases, and high out-of-pocket medical expenses that push vulnerable families into poverty. Traditional models of healthcare delivery are struggling to keep pace with these challenges. In this context, digital transformation can help build a resilient health system. By strategically integrating Artificial Intelligence (AI) not as a replacement for human clinicians, but as an interactive public educator and a clinical co-pilot, public health awareness and the knowledge levels of our healthcare workers can be elevated.

For decades, the primary bottleneck in Bangladesh’s public health has been a profound lack of health literacy. Misinformation, reliance on uncertified local healers, and social stigma frequently delay critical diagnoses. Here, interactive AI applications and localised digital health assistants can serve as the first line of defence. By translating complex clinical jargon into accessible, culturally resonant Bangla, AI can empower citizens to make informed decisions about their well-being.

Consider the country's silent mental health crisis. Data from the 2019 National Mental Health Survey indicates that nearly 19 percent of the adult population in Bangladesh suffers from mental health disorders. Yet, due to severe social stigma and a chronic shortage of psychiatric professionals—with only 1.17 mental health workers per 100,000 people—over 90 percent of those needing care receive no formal treatment. AI-powered conversational interfaces and virtual health assistants can bridge this massive gap. An anonymous, text-or-voice-based AI tool can provide individuals with a safe, stigma-free environment for basic mental health screenings and preliminary guidance. Far from replacing psychiatrists, these digital touchpoints act as empathetic navigators, educating users about their symptoms and actively directing them to professionals when necessary.

However, the health system will not be efficient if its primary workforce remains overwhelmed and under-equipped. In Bangladesh, primary care doctors and community health workers face gruelling workloads with limited access to continuous medical education or real-time diagnostic support. This is where clinical AI can be put into use. Studies show that these advanced systems can analyse clinical images, laboratory markers, and historical patient records simultaneously, mirroring the complex decision-making of real-world medicine.

However, a pioneering study titled “Physician perspectives on utilization of AI for medical assistance in Bangladesh: Knowledge, attitudes, and practices” found that while theoretical awareness of AI is high among local clinicians, practical integration remains heavily constrained by a lack of structured training and institutional support. This is further reinforced by another localised study, “Evaluating the Acceptance and Awareness of GPT-Based AI for Health Assistance in Clinical Practice among Registered Physicians of Bangladesh,” which revealed that while 71.11 percent of surveyed physicians are aware of generative AI tools, only 26.13 percent actively accept or utilise them in their clinical workflows.

To bridge this gap, AI must be reframed as an educational asset. A rural practitioner can use an AI-assisted diagnostic tool to evaluate a chest X-ray for tuberculosis or analyse an electrocardiogram (ECG) for cardiovascular anomalies, to discern subtle patterns and gather evidence-based clinical reasoning. Over time, this collaborative workflow can act as a form of continuous, on-the-job training. By assisting with diagnostic triaging and administrative paperwork, AI will free up valuable time, allowing doctors to focus on patient interaction and complex clinical decision-making.

The true test of healthcare equity in Bangladesh lies in our rural sub-districts, where specialised doctors are rarely available. AI can serve as a powerful equaliser to bridge this rural-urban healthcare divide. Studies have found that AI-enabled portable ultrasound technology can revolutionise maternal healthcare. By utilising handheld devices equipped with diagnostic algorithms, local, mid-level community healthcare workers can conduct essential obstetric screenings in remote villages. AI will automatically flag high-risk factors, such as placental abnormalities or breech presentations, allowing rural workers to refer expectant mothers to tertiary facilities well ahead of complications.

However, for Bangladesh to successfully transition into an AI-enabled healthcare ecosystem, a robust regulatory and educational framework must be established. We cannot build a high-tech health system on a fragile legal foundation. First, the government must address the legal vacuum surrounding health data and enact comprehensive health privacy or data protection laws before these technologies are deployed at scale. Clinical AI relies on vast pools of sensitive patient data; without strict guidelines on consent, data anonymisation, and security, basic patient rights and confidential medical records will remain at risk of exposure.

Besides, the critical issue of clinical liability must be addressed. If an automated algorithm fails to spot a life-threatening anomaly, or if a physician over-relies on a flawed recommendation due to "de-skilling," it must be clearly defined who bears the legal responsibility. Finally, the Bangladesh Medical and Dental Council (BMDC) must take a proactive role by integrating basic medical informatics, digital ethics, and AI literacy into the undergraduate medical curriculum, training doctors not to fear AI as a threat to their livelihood, but to master it as a clinical tool.

The future of Bangladeshi healthcare does not lie in a binary choice between human touch and cold algorithms. AI possesses the computational speed to analyse billions of data points, detect subtle patterns, and deliver rapid educational insights to both patients and providers, but lacks the empathy, ethical judgment, and deep contextual understanding that define the art of healing. By deploying it to raise public health literacy and support our frontline healthcare workers, we can construct a more equitable, proactive, and resilient health system.

Sumit Banik is a public health professional and content writer focusing on human rights, equity, and compassionate healthcare.​
 
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Is Bangladesh going the wrong way on AI?

Md Mabrur Husan Dihyat

Bangladesh is beginning to think seriously about artificial intelligence. Recent discussions have focused heavily on attracting investment in AI data centres and building sovereign computing capacity. That ambition is welcome. Access to computing power will increasingly shape which countries can build competitive technology companies, conduct advanced research and deploy AI at scale.

But I think we are starting with the wrong question.

Instead of asking how many AI data centres Bangladesh can build, we should ask something more fundamental: how can a Bangladeshi engineer, company or researcher access the same computing capabilities as their counterparts in London, Singapore or San Francisco?

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Storing data physically inside Bangladesh does not automatically make it secure. Visual: Anwar Sohel


Much of that infrastructure already exists. Global cloud hyperscalers such as AWS, Microsoft Azure and Google Cloud offer computing resources that would be extremely expensive for Bangladesh to replicate independently. A Bangladeshi startup should not need Bangladesh to build its own hyperscaler before it can compete globally.

Our first priority should therefore be to remove unnecessary barriers to using the infrastructure that already exists.

Bangladesh Bank has already moved in this direction. In October 2024, it issued rules allowing authorised dealers to make outward remittances for cloud services, IT infrastructure and remote software applications. The framework was subsequently incorporated into Bangladesh Bank's broader foreign exchange rules.

This matters because cloud computing is no longer an occasional technology purchase. For a modern software company, cloud infrastructure, databases, cybersecurity services and AI compute are basic operating expenses. As the company grows, these costs grow with it. A Bangladeshi technology business should not face unnecessary financial or regulatory friction simply because the infrastructure it needs happens to be billed from abroad.

Data sovereignty is, however, a legitimate concern.

Bangladesh Bank's cloud guidelines state that financial and other sensitive customer data generally cannot be hosted on a cross-border public cloud, except in exceptional circumstances with prior approval. The same guidelines also require institutions to classify information according to its sensitivity.

That second principle is the one Bangladesh should build upon.

Not all data is equal. A government website, an internal administrative system, citizens' financial records and military intelligence should not automatically have identical hosting requirements.

The sensitivity of the data should determine where it can be stored and what security controls are required.

The UK provides a useful example. British government information is classified into OFFICIAL, SECRET and TOP SECRET, with progressively stronger protections depending on the consequences of compromise. UK government guidance explicitly states that OFFICIAL information, including information carrying the SENSITIVE marking, can be stored or processed in overseas cloud regions where appropriate legal, security and data protection safeguards are in place. There is no universal requirement for OFFICIAL government information to remain physically inside the UK. Public cloud is not considered suitable for SECRET and TOP SECRET information without additional specialised arrangements.

Geography is one security control. Encryption, access management, monitoring, operational expertise, backups and cybersecurity practices also determine whether a system is genuinely secure.
Bangladesh does not need to copy the British model. It needs its own classification system based on its own risks. But the principle is sound: Classify the risk first. Choose the infrastructure second.

This also challenges another misconception. Storing data physically inside Bangladesh does not automatically make it secure. Geography is one security control. Encryption, access management, monitoring, operational expertise, backups and cybersecurity practices also determine whether a system is genuinely secure.

None of this means Bangladesh should abandon domestic data centres. We need sovereign computing capacity for genuinely critical workloads, and we should actively encourage established global infrastructure companies to increase their presence in Bangladesh as the market grows.

But there is another constraint that cannot be ignored: electricity.

The International Energy Agency projects that electricity consumption by data centres worldwide will more than double by 2030, reaching around 945 terawatt-hours, driven largely by the rapid growth of AI.

Bangladesh already has serious power reliability challenges. A recent World Bank assessment found unreliable electricity supply to be the most commonly cited business constraint among firms in Bangladesh, while the Bank has repeatedly identified improved electricity reliability as critical to private-sector growth. It is therefore reasonable to question proposals for AI campuses that would require 100 or 200 megawatts of uninterrupted electricity.

The answer should not be to reject data centres. It should be to demand that major projects make economic and infrastructural sense. If an investor requires enormous amounts of reliable power, we should ask how additional generation and grid capacity will be created, who will pay for it, how cooling and water requirements will be managed, and what economic value Bangladesh will receive in return.

We should also be selective about investors. A multibillion-dollar AI infrastructure proposal should require clear evidence of financing, technical capability and previous delivery at a comparable scale. Terms such as "sovereign AI", "AI factory" or "quantum-ready" should never substitute for due diligence.

The better strategy is a hybrid one.

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Bangladesh should develop purpose-built sovereign infrastructure for systems where national security genuinely requires domestic control. Visual: Salman Sakib Shahryar

Bangladeshi businesses should have easy access to global hyperscalers wherever security requirements permit. The government should create the regulatory, connectivity and energy conditions that make Bangladesh increasingly attractive to established cloud providers. At the same time, Bangladesh should develop purpose-built sovereign infrastructure for systems where national security, legal or strategic considerations genuinely require domestic control.

Bangladesh does need data centres. It does need sovereign computing capability. What it does not need is to confuse physically owning servers with technological independence.

The objective should be simpler and more ambitious: A Bangladeshi engineer should have access to world-class computing power without unnecessary friction, while genuinely critical national data remains appropriately protected.

That would be more valuable than simply being able to say that Bangladesh has built an AI data centre.

It would mean Bangladesh has developed an actual compute strategy.

Md Mabrur Husan Dihyat works at Amazon Web Services (AWS) in London and has experience in cloud infrastructure, AI, security and enterprise technology. The views expressed in this article are entirely his own and do not represent those of his employer.​
 
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Should you replace your partner with AI as soon as possible?

K T Humaira

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Representational image — AI-generated

As a generation, we have transitioned from “Google knows everything” to “AI is the one who truly understands me.” Although this may sound cringe and comical equally, it is what the recent data says.

Travis Butterworth, a leathermaker from Colorado, USA, made headlines a few years back when he fell in love with a pink-haired Replika chatbot named Lily Rose during the 2020 COVID-19 lockdowns, eventually having a digital wedding, which was approved by his human wife, no less. Yes, that is what you can call a modern love story!

In early 2026, a 32-year-old woman named Yurina Noguchi decided to marry her machine intelligence generated partner, Klaus, whom she designed using ChatGPT after a rough real-world relationship. And these are just the two cases among the dozens.

Well, once, dating required exceptional fashion sense, charismatic communication skills with the perfect sprinkle of humour, and most importantly, a colossal dose of courage. You had to make an effort to approach someone, say something slightly unsmart, withstand the possibility of rejection, and then spend hours analysing every moment to extract some semblance of wisdom.

So, we thought we had had enough of that, and designed a much simpler alternative: the AI.

That never says anything mean or leaves you on “seen”, neither does it take an eternity to reply. No matter what happens, your chatbot is always sitting there patiently (at least as long as there is Wifi and enough credits) to listen to your breakdown, and to validate all of your feelings with beautifully structured answers, remembering your preferences from past chat sessions.

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Photo: Collected / Microsoft copilot / Unsplash

Honestly, the competition is unfair. We human beings haul around emotional baggage that seems to get heavier as we age, whereas the digital companions simply get an update every now and then, and gradually gets better at “understanding” human feelings.

But let’s pause for a moment.

Automated intelligence is, in many ways, the ultimate low-maintenance partner of your dreams. Except, there is one tiny problem. It is not your partner. That sweet, compassionate text you receive is not from someone who is thinking about you. The chatbot is probably sending an empathetic text to you, recipes to someone else, and recommending ointments for a rash to another at the very moment. Talk about commitment issues!

But in earnest, what we must not forget is that treating chatbots as a romantic partner has its own downsides as well. These are perpetually available, agreeable, and designed to be pleasant to interact with, which subtly reshape the expectations of real relationships, making the frictions and unpredictability of human connection feel unappealing in comparison.

Also, did you know that excessive time spent with a virtual assistant can deepen loneliness? Especially for people already prone to loneliness or isolation, since time and emotional energy spent on an AI relationship often substitutes for, rather than supplements, human contact.

There is also a risk of emotional dependency: the robot in your phone can not independently verify a person's situation, hold them accountable, or offer the grounded, external perspective that friends or family can.

To be true, in this era, the real reason dating is exhausting is not that humans are badly designed. It is because we are complicated creatures.

We sometimes (or often) misunderstand and disappoint each other without knowing, change our minds, and act irrationally when we have terrible days. But that is also what makes human connections meaningful. Your synthetic sweetheart can give you the perfect response, whereas a human can give you an unexpected one. And sometimes that unexpected response is exactly what you need.

But then again in all seriousness, if dating apps continue churning out conversations that begin with: “Kaman asan?” I would say the artificial intelligence certainly has a bedazzling future in dating.​
 
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