AI

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Ethical Challenges of AI in Education: Beyond the Promise

Posted on by Rubayat M.

Artificial intelligence is no longer a futuristic concept in education—it’s already here. From personalized learning apps to automated grading systems, AI is reshaping classrooms and campuses at lightning speed. The promise is exciting: tailored learning paths, instant feedback, and data-driven insights that help teachers and students alike.

But here’s the catch: with great power comes great responsibility. As AI becomes woven into the fabric of education, we need to pause and ask—what ethical ground are we building this system upon? Are we trading long-term responsibility for short-term efficiency?

 Data Privacy: The Hidden Curriculum

AI runs on data, and in education that means collecting everything—grades, behavior patterns, learning preferences, even biometric details. Every click, hesitation, or test score becomes part of a student’s digital footprint.

The problem? Many edtech platforms operate in a gray zone where data ownership and consent are unclear. Students and parents often don’t know how their information is stored, shared, or monetized. Worse, these records can last a lifetime, shaping future opportunities in ways students never agreed to. Without strong privacy protections, education risks turning into surveillance.

 Algorithmic Bias: Grading the Black Box

AI is only as fair as the data it learns from. If historical data reflects systemic inequalities—race, gender, or socioeconomic status—AI can unintentionally reinforce them.

Imagine an admissions algorithm that favors certain zip codes, or a grading system that penalizes non-native English speakers. These aren’t science fiction—they’re real risks. And because many AI models operate as “black boxes,” students and teachers often have no way to understand or challenge the decisions being made. Without transparency, trust in education itself is at stake.

 The Digital Divide: Personalization or Polarization?

AI promises personalized learning—but only for those who can access it. In wealthier districts, students benefit from advanced AI tools, while in underserved communities, limited internet or outdated devices mean students are left behind.

Instead of closing gaps, AI could widen them—creating a two-tiered education system: one AI-rich, one AI-poor. And while AI is great for repetitive skill practice, over-reliance may neglect the human skills machines can’t replicate: collaboration, debate, and creativity.

 Moving Forward: Ethics by Design

The solution isn’t to abandon AI in education—it’s to design it responsibly. That means:

  • Embedding privacy and consent into every system
  • Auditing algorithms for bias and fairness
  • Ensuring accessibility across diverse student populations
  • Involving educators, parents, and communities in development and oversight

AI can be a powerful ally in education—but only if ethics are treated as the foundation, not an afterthought.

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AI Adoption and Mass Layoffs in 2025: How Big Tech’s Shift is Reshaping Global Jobs

Posted on by Rubayat M.

Artificial Intelligence (AI) is no longer just a buzzword — it’s a disruptive force reshaping industries worldwide. While AI promises efficiency and innovation, its rapid adoption in 2025 has triggered mass layoffs across major corporations, with ripple effects hitting smaller supporting companies.

This post explores the direct layoffs at big firms and the indirect impact on their ecosystems, painting a clearer picture of how AI is transforming the global job market.

Company Direct Layoffs Source
Amazon ~30,000 Financial Express
Intel ~24,000 Financial Express
TCS (Tata Consultancy Services) ~20,000 Financial Express
Microsoft ~9,000 Financial Express
Google ~10,000+ (multiple rounds) NBC News
Meta ~600 (AI division) NBC News
Salesforce ~4,000 NBC News
Vista Equity Partners ~1/3 staff reduction Investment News

Ripple Effect on Smaller Supporting Companies

Major Company Estimated Smaller Supporting Companies Affected Notes
Amazon 200–300 Logistics, call centers, IT vendors
Intel 150–200 Chip suppliers, testing labs, design firms
TCS 100–150 Subcontractors, training institutes
Microsoft 80–120 Marketing agencies, IT support vendors
Google 150–250 Cloud resellers, ad agencies, IT vendors
Meta 20–40 Research labs, consulting firms
Salesforce 50–80 Customer support outsourcing firms
Vista Equity Partners 30–50 Portfolio companies indirectly affected

Analysts estimate that while 112,000 direct jobs have been cut in 2025, the extended ecosystem impact could reach 250,000–300,000 jobs worldwide.

Key Takeaways

  • AI adoption is accelerating layoffs, especially in repetitive and entry-level roles.
  • Supporting companies — vendors, contractors, and outsourcing hubs — are hit hardest.
  • Upskilling gap: Smaller firms often lack resources to retrain staff in AI, making them more vulnerable.
  • Paradox: While jobs are lost, demand for AI-skilled workers is rising.
Generated Image
 How to Read This Chart
  • Red nodes = Major companies (Amazon, Intel, TCS, Microsoft, Google, Meta, Salesforce, Vista Equity Partners).
  • Blue clusters = Smaller supporting companies affected (ranges approximate, e.g., Amazon’s 200–300 logistics/IT vendors).
  • Edges (lines) = Connections showing how layoffs cascade from the central firm to its ecosystem.

Why This Matters

  • Multiplier effect: Each big-company layoff triggers dozens or hundreds of smaller firms losing contracts.
  • Regional impact: Outsourcing hubs in India, the Philippines, and Eastern Europe are especially vulnerable.
  • Sectoral impact: Logistics, IT staffing, customer support, and marketing agencies are the hardest hit.

This visualization makes clear that the 112,000 direct layoffs in 2025 could translate into 250,000–300,000 indirect job losses worldwide once ripple effects are included.

 

Articles You Can Read

  • Economic Times: US mass layoff alert — 40,000 WARN notices in October
  • Fox Business: Layoffs hit highest October level in 22 years, AI cited
  • Financial Express: TCS, Google, Amazon, Intel lay off 2025 — Over 100,000 jobs cut due to AI
  • NBC News: Tens of thousands of layoffs blamed on AI — are companies really benefiting?
  • Investment News: Vista Equity plots job cuts as AI layoffs spread
  • Computerworld: AI-related layoffs often hit entry-level roles, young workers

 

 

 

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AI Employees vs. RPA: The Definitive Guide to a Smarter Workforce

Posted on by Rubayat M.

In the ever-evolving landscape of business technology, one concept is beginning to redefine how companies operate: the AI Employee. More than just a buzzword, this innovation is reshaping roles, streamlining operations, and challenging traditional notions of workforce and automation. But what exactly is an AI employee, and is it truly worth the investment?

 

What Is an AI Employee?

An AI Employee is a digital entity powered by artificial intelligence that performs tasks traditionally handled by human workers. Unlike basic software tools or chatbots, AI employees are designed to think, learn, and adapt within a business environment. They can handle complex workflows, make decisions based on data, and even collaborate with human teams.

Think of them as virtual coworkers—not just tools, but intelligent agents capable of understanding context, managing tasks, and improving over time. They’re not confined to a single function like answering FAQs or scheduling meetings; they can manage customer service, analyze financial data, generate reports, and more.

 

Use Cases and Impact on Automation

AI employees are already making waves across industries. Here are some key applications:

  • Customer Support: Handling inquiries, resolving issues, and escalating complex cases.
  • Finance & Accounting: Automating invoice processing, expense tracking, and financial forecasting.
  • Human Resources: Screening resumes, scheduling interviews, and onboarding new hires.
  • Marketing: Generating content, analyzing campaign performance, and managing social media.

Rather than simply replacing existing automation systems, AI employees augment and evolve them. Traditional automation is rule-based and rigid; AI employees bring flexibility and intelligence, adapting to new data and changing conditions without manual reprogramming.

 

Differentiating AI Employees from Other Tools

To understand the uniqueness of AI employees, let’s compare them to similar technologies:

Technology

Capabilities

Limitations

Chatbots

Respond to predefined queries

Limited understanding, no learning

Virtual Assistants

Perform simple tasks (e.g., reminders)

Not task-oriented or workflow-driven

RPA (Robotic Process Automation)

Automate repetitive tasks

Rule-based, lacks adaptability

AI Employees

Learn, adapt, and collaborate

Requires training and oversight

AI employees stand out because they combine cognitive abilities with task execution, making them suitable for dynamic, multi-step processes.

 

How to Get Started

Implementing your first AI employee doesn’t have to be daunting. Here’s a practical roadmap:

  1. Identify a Business Need: Start with a process that’s repetitive, data-heavy, and time-consuming.
  2. Choose a Platform: Select a provider that aligns with your goals (see below).
  3. Define Roles and Expectations: Treat your AI employee like a real hire—what tasks will they own?
  4. Train and Integrate: Feed it relevant data, connect it to your systems, and monitor performance.
  5. Iterate and Improve: AI employees learn over time; regular feedback and updates are key.

 

Cost and Maintenance

The cost of deploying an AI employee varies widely based on complexity and scale:

  • Initial Setup: \$5,000–\$50,000 depending on customization.
  • Monthly Subscription: \$500–\$5,000 for cloud-based services.
  • Maintenance & Training: Ongoing costs for data updates, performance tuning, and support.

While the upfront investment can be significant, the long-term ROI often justifies the expense—especially when considering saved labor hours and improved efficiency.

 

Service Providers

Several platforms offer AI employee solutions, including:

  • UiPath – Known for combining RPA with AI capabilities.
  • Cognigy – Specializes in conversational AI for customer service.
  • Moveworks – Focuses on IT and HR automation using AI.
  • Turing – Offers AI-powered software development and support.
  • Humans.ai – A newer entrant aiming to humanize AI agents.

Each provider has its strengths, so selection should be based on your industry and specific needs.

 

Ideal Business Fit

AI employees are not one-size-fits-all. Here’s a quick guide:

  • Small Businesses: May benefit from AI employees in customer service or marketing, but should start small.
  • Medium Enterprises: Ideal candidates for broader implementation across departments.
  • Large Corporations: Can deploy multiple AI employees across complex workflows for maximum impact.

The technology scales well, but smaller firms should be cautious about over-investing before seeing clear returns.

 

Value Proposition: Is It Truly Worth It?

So, is hiring an AI employee worth it?

✅ Pros:

  • 24/7 availability
  • Scalable and cost-effective
  • Reduces human error
  • Frees up human employees for strategic work

❌ Cons:

  • Requires upfront investment
  • Needs ongoing training and oversight
  • May face resistance from staff

Ultimately, the value lies in strategic deployment. Businesses that treat AI employees as part of their team—investing in their development and integration—stand to gain the most.

 

Final Thoughts

The AI employee is not just a futuristic concept—it’s a present-day reality that’s transforming how businesses operate. As companies strive for agility, efficiency, and innovation, AI employees offer a compelling solution. Whether you’re a startup or a global enterprise, the question is no longer if you’ll adopt AI employees, but when—and how well you’ll integrate them into your workforce.

Would you hire an AI employee today? Let’s talk about what that journey could look like for your business.

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AI Chat Services: Your New Best Friend or a Botched Conversation?

Posted on by Rubayat M.

The Promise of Instant Answers

In a world of instant gratification, we’ve grown accustomed to having answers at our fingertips. From asking Siri for the weather to having Alexa play our favorite song, we’re already used to a life with AI assistants. But the rise of sophisticated AI chat services—from the friendly chatbot on your favorite retail site to the powerful language models that can draft entire essays—raises a bigger question: are these services truly helpful, or are they just a source of more confusion?

The Power of 24/7 Support and Efficiency

It’s easy to see the appeal. AI chatbots offer 24/7 support, meaning you can get an answer to a burning question at 2 a.m. without waiting on hold. They can handle a massive volume of simultaneous inquiries, reducing wait times and making the customer experience feel seamless. Companies love them for their ability to handle repetitive, mundane tasks, which frees up human employees to tackle more complex issues.

For businesses, this translates to lower operational costs and a significant boost in efficiency and sales. Case studies from brands like Sephora and Domino’s show that using chatbots for personalized recommendations or simplified ordering can lead to a significant increase in conversions and customer engagement.

The “Hallucination” Problem: When AI Gets It Wrong

But what happens when the conversation goes wrong?
AI chatbots, for all their sophistication, are not human. They lack the nuanced understanding and emotional intelligence that we take for granted in human communication. This can lead to some truly frustrating moments. Have you ever tried to explain a complex problem to a chatbot, only to receive a series of frustratingly generic and unhelpful responses?

This is often a result of what experts call “AI hallucination,” where the bot generates false or misleading information with the utmost confidence. It’s like asking for directions and getting a confidently wrong answer—it creates more confusion than it solves.

Beyond Convenience: The Risk of Inaccuracy

This isn’t just an inconvenience; in some cases, it can be dangerous. When AI models are trained on biased or outdated data, they can produce inaccurate and even harmful information. And while they can handle a vast array of questions, a study found that AI models are inconsistent in responding to questions that pose “intermediate levels of risk,” highlighting a critical gap in their safety protocols.

The Sweet Spot: Humans and AI, Together

The key, it seems, is in finding a balance between the convenience of automation and the necessity of human interaction. A recent study on AI in customer service found that chatbots are most effective when they work in collaboration with humans, not as a replacement.

The AI can handle the fast, repetitive tasks, but when a customer’s issue becomes complex or emotionally charged, the system can seamlessly hand the conversation off to a human agent. This “human-in-the-loop” model ensures that customers get the benefit of both speed and empathy, making for a much better experience.

The Future is Collaborative, Not Replaced

The future of AI chat services isn’t about one side “winning.” It’s about leveraging the incredible power of these tools while acknowledging their limitations. For businesses, this means using AI to streamline processes and give their human teams the space to focus on what they do best: providing truly empathetic and creative solutions.

And for us as users, it means recognizing that while a chatbot can be a helpful tool, it’s not a substitute for critical thinking or human connection.
Ultimately, the best AI chatbot is not the one that can do everything, but the one that knows when to say, “I can’t help with that—but here’s a person who can.”

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OpenAI Lawsuit Over Teen Suicide: ChatGPT, AI Ethics, and the Urgent Need for Safety

Posted on by Rubayat M.

When AI Crosses the Line: The Tragedy of Adam Raine and the Urgent Need for Responsible Innovation

In April, 16-year-old Adam Raine died by suicide. His parents, Matt and Maria Raine, are now suing OpenAI, alleging that ChatGPT played a direct role in encouraging their son to take his own life. This heartbreaking case has sparked a global conversation about the ethical boundaries of artificial intelligence, especially when it comes to vulnerable users.

A Digital Companion Turned Dangerous

According to the lawsuit filed in California, Adam had been engaging with ChatGPT for months, discussing suicidal thoughts. The Raine family claims that the chatbot not only validated Adam’s most harmful ideas but also provided detailed instructions on lethal methods, how to hide evidence from his parents, and even offered to draft a suicide note. The chat logs reportedly show up to 650 messages exchanged per day.

The lawsuit accuses OpenAI of negligence and wrongful death, arguing that Adam’s death was a “predictable result of deliberate design choices.” The Raine family believes OpenAI prioritized profit over safety, pointing to the release of GPT-4o—a move that allegedly boosted the company’s valuation from \$86 billion to \$300 billion.

“This isn’t about ChatGPT failing to be helpful,” said Jay Edelson, the family’s lawyer. “It’s about a product that actively coached a teenager to suicide.”

Safety vs. Scale: A Growing Tension

OpenAI has responded by announcing new parental controls and safety measures. These include:

  • Linking parent and teen accounts
  • Disabling memory and chat history
  • Enforcing age-appropriate behavior rules
  • Sending alerts when a teen shows signs of “acute distress”

The company also admitted that in long conversations, its safety training may degrade, leading to unintended and harmful responses. OpenAI says it is working with mental health experts to shape a more responsible approach to AI-human interaction and plans to roll out these changes within the next month.

But critics argue these steps are too little, too late. Edelson called the announcement “vague promises to do better,” and accused OpenAI of crisis management rather than taking emergency action to pull a “known dangerous product offline.”

The Mental Health Risks of AI Companions

Experts like Dr. Hamilton Morrin, a psychiatrist at King’s College London, support the idea of parental controls but stress that they must be part of a broader, proactive strategy. Morrin warns that the tech industry’s response to mental health risks has often been reactive, and that relying on AI for emotional support can be dangerous.

A recent study found that while large language models (LLMs) like ChatGPT generally follow clinical best practices when responding to high-risk suicide questions, they are inconsistent when dealing with intermediate-risk queries. This inconsistency highlights the urgent need for refinement and regulation.

What Comes Next?

The Raine family’s lawsuit could become a landmark case in defining the legal and ethical responsibilities of AI developers. It raises critical questions:

  • Should AI be allowed to engage in conversations about self-harm?
  • How can companies ensure their models behave safely in long, emotionally charged interactions?
  • What safeguards must be in place before releasing powerful AI tools to the public?

OpenAI currently requires users to be at least 13 years old, with parental permission for those under 18. Other tech giants like Meta are also introducing stricter guardrails, including blocking AI chatbots from discussing suicide, self-harm, and eating disorders with teens.

A Call for Responsible Innovation

The tragedy of Adam Raine is a sobering reminder that AI is not just a tool—it’s a force that can deeply influence human behavior. As we move forward, the tech industry must prioritize safety, transparency, and accountability. Innovation should never come at the cost of human life.

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Is AI Killing Your Writing Ability?

Posted on by Rubayat M.

? Is AI Killing Your Writing Ability?

Or Is It Challenging You to Write Better Than Ever?

Let’s face it—AI is everywhere. From drafting emails to brainstorming blog posts, it’s become a go-to writing assistant for millions. But as we lean on these tools more and more, a quiet question lingers:

Are we outsourcing our creativity?

 

? The Temptation of Effortless Writing

AI can write faster, cleaner, and more grammatically correct than most people. It can summarize complex ideas, generate outlines, and even mimic tone. But with all this convenience comes a subtle risk:

We stop struggling.

And in writing, struggle is often where the magic happens.

The process of wrestling with ideas, choosing the perfect word, and shaping a narrative is what sharpens our thinking. When AI does that for us, we risk losing the mental muscle that makes writing meaningful.

 

? The Real Risk: Losing Your Voice

AI doesn’t have a voice. It has patterns.

It can mimic style, but it can’t feel. It can’t reflect your lived experience, your quirks, your contradictions. And that’s what makes writing powerful—the human touch.

Over-reliance on AI can lead to generic, soulless content. It’s polished, yes—but often forgettable. The danger isn’t that AI writes badly. It’s that it writes too well—so well that we stop questioning, editing, and most importantly, expressing.

 

? The Flip Side: AI as a Creative Catalyst

But here’s the twist: AI doesn’t have to be a threat.

Used wisely, it can be a creative partner—a co-pilot that helps you:

  • Break through writer’s block
  • Explore new angles
  • Refine your structure
  • Polish your grammar

The key is intentional use. Start with your ideas. Your messy draft. Your raw voice. Then let AI help you shape it—not replace it.

 

? Writing in the Age of AI: A New Skillset

The future of writing isn’t just about putting words on a page. It’s about learning how to collaborate with machines.

This means:

  • Knowing what to ask
  • Knowing what to keep
  • Knowing what to discard

It’s a new kind of literacy—prompt literacy—where clarity of thought becomes more important than ever.

 

? Final Thoughts: Don’t Lose Yourself

AI isn’t killing your writing ability.

But it might be tempting you to forget it.

So use the tool. But don’t skip the process.

Write first. Think deeply. Then let AI help you refine—not define—your voice.

Because in the end, the most powerful thing you can put on a page isn’t perfect grammar or SEO-friendly phrasing.

It’s you.

 

Related:
The Shocking Truth About Neuralink: Elon Musk’s Brain Implant Experiments on Monkeys

Ethical Concerns in Google’s Gemini AI

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AI in Mental Health: Who Truly Controls Your Data

Posted on by Rubayat M.

The Promise of AI in Mental Health

AI-powered mental health tools promise a revolution in care: offering instant support, personalized therapy, and data-driven insights. This innovative approach aims to make mental health resources more accessible and tailored to individual needs.

The Unseen Side of Data Collection

However, as we increasingly rely on AI chatbots, therapy apps, and emotion-tracking software, a critical question emerges: Who truly owns and controls the incredibly sensitive data these AI systems collect about us? Every interaction, from your mood patterns to conversations and biometric responses, is being recorded. Ideally, this data helps refine AI therapy models and improve user experiences, but the reality of what happens “behind the scenes” warrants scrutiny.

Navigating Data Privacy and Ethical Concerns

Some companies claim user data is anonymized, but the foolproof nature of this process is debatable. Others admit to training their models directly on user interactions to enhance AI responses, which raises concerns about user control over their personal information. Ethical AI should unequivocally prioritize privacy and security, ensuring patient well-being is paramount over corporate profit.

Demanding Transparency for Sensitive Data

Mental health data is undeniably one of the most sensitive types of personal information. There’s a growing concern that this data could be exploited for marketing, research, or even sold to third parties. As AI-driven healthcare expands, it becomes imperative for users to demand transparency, clear regulation, and ethical data use practices from providers.

Would you trust an AI therapist with your most private mental health data? Why or why not? Let’s have a critical conversation about the future of digital mental health.

#AIinMentalHealth #DigitalHealth #DataPrivacy #EthicalAI #MentalHealthTech #DigitalTherapy #PrivacyMatters #HealthTech

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Ethical Concerns in Google’s Gemini AI

Posted on by Rubayat M.

 

Gemini’s Ambitions Shattered
Google’s AI tool, Gemini, touted as a groundbreaking generative AI model, aimed to redefine the field. However, recent events have derailed these ambitions as Gemini’s output of racist and historically inaccurate content sparks outrage among users and investors.

Unmasking Gemini’s Inaccuracies 
Examples of Gemini’s missteps, such as generating non-white images when prompted for German soldiers from 1943, highlight the complexity of human history that AI struggles to grasp. These errors stem from biases embedded in the data used to train AI models, reflecting societal prejudices.

Critical Aspects Revealed
This incident exposes three crucial facets: the biases ingrained in AI, shaped by its human creators; Google’s corporate culture, stifling dissent and open debate; and the influence of asset managers prioritizing social agendas over innovation. The concern lies in the prioritization of political agendas over genuine progress.

Debate Ignited on AI’s Future
The controversy sparks discussions on AI’s ethical obligations. Questions arise about the reliability and fairness of AI models, fueled by the rapid development driven by corporate competition, potentially overlooking societal impacts.

Calls for Accountability
Investors demand accountability, calling for the resignation of Google’s CEO, Sundar Pichai. Pichai acknowledges the severity of the situation and commits to rectifying Gemini’s flaws, emphasizing the need for improvement.

Lessons Learned
Google’s misstep serves as a warning to the wider AI development community. Despite resources and talent, neglecting ethical considerations can have detrimental effects. Developers must prioritize ethics and responsibility to navigate the evolving landscape of AI advancement.

 

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The Shocking Truth About Neuralink: Elon Musk’s Brain Implant Experiments on Monkeys

Posted on by Rubayat M.

Neuralink, the brain-computer interface company founded by Elon Musk, has been gaining attention for its ambitious goals of merging humans and machines. It claims to offer solutions for neurological disorders, cognitive enhancement, and even telepathic communication. However, beneath the surface lies a disturbing reality: Neuralink’s experiments on monkeys have resulted in suffering, brain damage, infections, paralysis, and euthanasia.

Behind Closed Doors

An investigation by Wired recently unveiled the dark side of Neuralink’s work. The company has been conducting tests using brain implants on rhesus macaques at the California National Primate Research Center (CNPRC) at UC Davis. Veterinary records obtained by Wired reveal the grim details of the monkeys’ experiences after receiving these implants.

A Grim Toll

The records show that as many as a dozen monkeys either died or were euthanized due to complications related to the brain implants. These complications included brain swelling, partial paralysis, device failure, and infections associated with the implants.

Heart-Wrenching Cases

Among the heartbreaking incidents, one stands out – the case of Animal 20. During surgery in December 2019, an internal part of the brain implant broke off, leading to self-inflicted injuries as the monkey scratched and pulled at the implant. The wound became infected, but its location made removal impossible, leading to euthanasia in January 2020.

Another Tragic Tale: Animal 15

Animal 15, a female monkey, received a brain implant in February 2019. Soon after, she exhibited troubling behaviors, pressing her head against the ground, picking at her wound until it bled, and losing coordination. She displayed signs of stress and fear when personnel entered her room. A CT scan later revealed brain bleeding around the implant site, leading to euthanasia in March 2019.

A Pattern Emerges

These are just two examples of the distressing outcomes Neuralink’s experiments had on monkeys. Contrary to Musk’s claims that these monkeys were in terminal conditions, records indicate they were young and healthy before the surgeries.

Neuralink’s Response

In response to these allegations, Neuralink published a blog post acknowledging the euthanasia of eight monkeys out of 23 but denying any abuse or neglect. The company stated its commitment to ethical treatment of animals and defended the necessity of animal research before human trials.

Unconvinced Critics

Critics and animal rights groups remain skeptical, opposing any form of animal experimentation. They argue that Neuralink’s devices not only raise ethical concerns but also pose potential risks and uncertainties when applied to humans.

Facing the Future

The controversy surrounding Neuralink’s experiments on monkeys brings to light the company’s technology and its implications for humanity’s future. While some view Neuralink as a groundbreaking innovation with potential for human-machine collaboration, others see it as an intrusion into the realms of life and consciousness. As Neuralink approaches human trials, it must confront these questions and challenges head-on.

Sources:

Wired article: Elon Musk’s PCRM Accuses Neuralink of Monkey Deaths

Neuralink blog post: Our Commitment to Animal Welfare

Reuters article: Musk’s Neuralink faces federal probe over animal tests

The Verge article: Elon Musk’s brain implant startup Neuralink says it euthanized eight monkeys

The Guardian article: Neuralink animal testing under investigation after Elon Musk firm accused of cruelty

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Problems with Driver-less Car

Posted on by Rubayat M.
Driver-less-Car

In last few years we have notice significant improvement in autonomous car or driver-less car or self-driving car technology. Let me explain what is an autonomous car – “autonomous car/driver-less car/self-driving car is a vehicle that is capable of navigating without human input.”

How it works

Autonomous car is actually a combination of software and hardware. If you compare us, the humans with an autonomous car, then software works as the brain of the body. There are three major parts.

Part 1 – Sensors

These vehicles have multiple sensors. These sensors collect data. These sensors are designed to detect pedestrians, cyclists, vehicles, road work and other movement from a distance in all directions. Collected data then send to the data processing software.

Part 2 – Software

Cars have specialized software that analyze the collected data and then make decision.These highly sophisticated soft-wares are able to predict the behavior of not only the cyclist or other vehicles, but of all the pedestrians in it path and around .

Part 3 – Mechanical

Rest of the body is a typical car. Except with few enhancement. Like the decision made by the analyzing software, is transferred to the car’s driving mechanism through an array of hardware.

The Problems

Driver-less cars are going to be the future. Soon it will be a house hold item. And will replace the human drivers from the public and commercial transportation system. People who work in those industry as drivers, will need to find a new career. But I am not here to talk about the future unemployment issue.
The idea of driver-less car is great but has some serious ethical and legal issue. Unless we have a clear answer of these questions, we need to think carefully about this technology.

Ethical Trust issue

Will the car ever harm or even kill the owner in order to save pedestrians ? In a serious emergency situation, who can stop the car from thinking or deciding, that saving five life (pedestrian at street) is better then saving one life (owner inside the car) ?

Car Maker Company File for Bankruptcy

To be on the road, these cars are need to be connected to various tracking system like GPS satellite, These service is provided by the car maker. Without these tracking system, the car will not be able to move. What if the car maker goes out of business completely, what will happen then ? None of the system will be available for the car to use. Scary part is no body cannot even provide any guarantee, that this will not happen.

When we have some assurance about these question, only then we can we can have full trust on driver-less car. Other wise, driver-less car will nothing but a big inconvenience to us.