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daniyasiddiquiEditor’s Choice
Asked: 07/09/2025In:

give people more privacy and control ...

aitechnology
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    The Cloud Convenience That We're Grown Accustomed To Most artificial intelligence systems for decades have relied on the cloud. If you ask a voice assistant a question, send a photo to be examined, or converse with an AI chatbot, data typically flows through distant servers. That's what drives theseRead more

    The Cloud Convenience That We’re Grown Accustomed To

    Most artificial intelligence systems for decades have relied on the cloud. If you ask a voice assistant a question, send a photo to be examined, or converse with an AI chatbot, data typically flows through distant servers. That’s what drives these services—colossal models computing on massive computers somewhere in the distance.

    But it has a price tag. Every search, every voice query, every photo uploaded creates a data trail. And once our data’s on a stranger’s servers, we’re at their mercy—who’s got it, who’s studying it, and how it’s being used.

    Why Offline AI Feels Liberating

    Offline AI modes flip that math on its side. Instead of uploading data to the cloud, the AI works locally—on your laptop, phone, or even a little box in your living room.

    That shift might mean:

    • Privacy by default: Your voice clips, messages, or photos stay with you, not with some other person’s data center.
    • Control in your hands: You get to decide what you want to share and what you don’t.
    • No constant internet reliance: The AI functions even in rural regions, dead zones, or areas where connectivity is spotty.

    Whispering your secrets to a trusted friend as compared to screaming them into a public stadium.

    The Trade-Offs: Power vs. Freedom

    There is no free lunch. Offline AI comes with limitations.

    • Smaller models: The cloud can host enormous AI brains. Your phone or computer can only handle smaller ones, which will not be as creative or precise.
    • Updates and learning: Cloud AI keeps on learning and updating. Offline AI will fall behind if you do not update it manually.
    • Battery and storage strain: Using advanced AI locally can drain devices faster and take up memory.

    So, offline AI does sound safer, but sometimes it feels like swapping a sports car for a bike—you achieve freedom, but you lose a bit of power.

    A Middle Ground: Hybrid AI

    The most practical solution would be hybrids. Think about an AI that does local operation for sensitive tasks (e.g., scanning your health data, personal emails, or financial data), but accesses the cloud for bigger and more complex work (e.g., generating long reports or advanced translations).

    That way, you have the intimacy and privacy of local AI, along with the power and flexibility of cloud AI—a “best of both worlds” solution.

    Why Privacy Is More Important Than Ever

    The call for offline AI isn’t technology-driven—it’s driven by trust. Many simply don’t like the idea of their own personal information being stored, sold, or even hacked out on far-flung servers. Local AI operation provides a feeling of mastery of your digital life.

    It is a matter of taking power back in a world where information appears to be under perpetual observation. Offline forms of AI could put the power back into the possession of people, not companies.

    The Human Nature of the Issue

    Essentially, it is not a matter of devices—it is about people.

    • A parent may prefer an offline AI tutor for their youngster, so that conversations are not overheard.
    • An on-the-ground war correspondent journalist can employ offline translation AI without fear of being monitored by the government.
    • A regular consumer could want to have assurance his or her own personal voice recordings never leave his or her phone.
    • These aren’t geek arguments—they’re human needs for dignity, security, and autonomy.

    Conclusion

    Offline AI can be potential game-changers for privacy and autonomy. They may not always be as powerful or as seamless as their cloud-based counterparts, but they offer something that theirs do not: peace of mind.

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daniyasiddiquiEditor’s Choice
Asked: 07/09/2025In:

machines more empathetic, or just bet ...

aitechnology
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    The Promise of Emotion-Aware AI Picture an AI that answers your questions not only, but one that senses your feelings too. It senses frustration in the tone of a customer service call, senses sadness in your emails, or senses uncertainty in your facial expressions. Technologically, the equipment canRead more

    The Promise of Emotion-Aware AI

    Picture an AI that answers your questions not only, but one that senses your feelings too. It senses frustration in the tone of a customer service call, senses sadness in your emails, or senses uncertainty in your facial expressions. Technologically, the equipment can render computers as empathetic, friendly, and sympathetic.

    • A therapy robot can respond sympathetically when it senses tension in your voice.
    • A tutorial robot can prod you forward when it detects uncertainty, instead of dumping more information into you.
    • Customer service robots could defuse anger by calming angry customers rather than reading off rehearsed responses.
    • At its best, affect-aware AI could render technology interactions less transactional and robotic, and more personal.

    The Risk of Manipulation

    • But in that coin comes a dark twin. That we can recognize that we’re experiencing something also implies that AI can fool us—sometimes even secretly.
    • Advertising & Marketing: A mood-detecting AI that knows you’re lonely may push you towards comfort purchases.
    • Politics & Propaganda: Emotion-recognizing algorithms can present the news in a manner that pulls on fear, anger, or hope in an effort to sway opinions.
    • Social Media: Feeds can be crafted to engage you more by sensing your current mood and responding thereto.

    Instead of being empathized with, people will start to feel manipulated. Machines will not necessarily be more empathetic—perhaps they’re simply better at “reading the room” in trying to further someone else’s agenda.

    Do Machines Really Feel Empathy

    Here’s the tough truth: AI doesn’t “feel” anything. It doesn’t know what sadness, joy, or empathy actually mean. What it can do is recognize patterns in data—like the tremble in your voice, the frown on your face, or the choice of words in your text—and respond in ways that seem caring.

    That still leaves us to question: Is false empathy enough? For some, maybe so. If a sense of security is provided by an AI teacher or an anxiety app quiets an individual who lives in anxiety, the effect is real—regardless of whether the machine “feels” it or not.

    The Human Dilemma: Power or Dependence

    Emotion-sensing AI can enable us:

    • It could help in mental health when there are few human resources to do so.
    • It can reduce miscommunication in customer service.
    • It can bridge cultural and communication gaps.

    It can, however, make us more dependent on machines for comfort. As soon as we start depending on AI to make us feel more cozy in lieu of family, friends, and society, society breaks apart and gets isolated.

    Guardrails for the Future

    So that affective AI is not a tool of domination but empathy, we need guardrails:

    • Transparency: People should be able to always know if they are speaking to an AI or another person.
    • Ethical Design: AI can be designed to be resistant to employing affective information to drive people into their vulnerabilities.
    • Boundaries: There are some areas—like political persuasion—on which strong boundaries can be put on affective systems.

    Final Reflection

    Emotion-sensitive modes of AI are at a crossroads. They might make machines seem like friends who genuinely “get” us, rendering people who feel heard and understood. Or they can be the masters of subtlety and manipulate decisions we have no awareness of being manipulated.

    Ultimately, the outcome will depend less on the technology itself, and more on how humans choose to build, regulate, and use it. The big question isn’t whether AI can understand our emotions—it’s whether we’ll allow that understanding to serve our well-being or someone else’s agenda.

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daniyasiddiquiEditor’s Choice
Asked: 06/09/2025In: ,

cloud services, and data flows repla ...

ainews
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    What we mean by “digital tariffs” By “digital tariffs” I mean taxes, levies or customs-style duties applied to cross-border digital activity — things like data flows, remote cloud/AI services, digital advertising, streaming or the commercial use of foreign AI models. This is different from standardRead more

    What we mean by “digital tariffs”

    By “digital tariffs” I mean taxes, levies or customs-style duties applied to cross-border digital activity — things like data flows, remote cloud/AI services, digital advertising, streaming or the commercial use of foreign AI models. This is different from standard customs duties on imported physical goods: digital tariffs target transactions, data, or digital market access rather than the physical movement of items.

    Why the idea is appealing

    Economy has shifted — so have value chains. More value now sits in software, data, AI models and cloud platforms. Traditional tariffs aimed at protecting domestic manufacturing don’t capture those revenue sources or address digital “market access” asymmetries.

    Tax fairness / revenue reasons. Many countries felt large digital platforms paid too little tax where their users are located; this spurred digital services taxes and the OECD’s reform effort. Digital levies are a way to claim revenue from cross-border

    Policy objectives beyond revenue. Governments may want to incentivize local data storage, protect privacy/safety, or discourage importing services that harm domestic industry. A digital tariff is a blunt tool to achieve those goals when other policy options are limited.

    What digital tariffs can do well (the upside)

    • Raise revenue from non-physical value creation (digital advertising, platform services). This helped motivate many countries’ equalisation levies.
    • Encourage local investment or data localization when structured as a conditional levy (lower rates if data centers/local partners are used).
    • Offer policy leverage where international tax rules are slow to adapt — governments can act unilaterally to respond to public pressure.

    What they cannot replace in practice (limits vs. physical tariffs)

    • Border protection and industrial policy. Tariffs on goods change relative domestic prices, protect domestic producers from import competition and reshape supply chains in ways a digital levy cannot. You can’t “tariff” a foreign-made tractor the same way you tax a SaaS subscription — the economic levers are different.
    • Customs enforcement & provenance. Physical tariffs are enforced at borders where customs inspect shipments. Digital activity is less tangible, easier to route or relabel, and often falls under different tax/tariff legal frameworks.
    • WTO and trade-law realities. The WTO moratorium on customs duties for electronic transmissions has been repeatedly renewed, and it constrains multilateral acceptance of customs-style duties on pure digital transmissions — though that moratorium’s future is debated. Pushing a full replacement would require rewiring global trade rules.

    Real-world signs & recent moves (short snapshot)

    Several countries experimented with digital levies (equalisation levies, digital services taxes), but some jurisdictions are reversing or revising them as international tax frameworks and diplomacy evolve — e.g., India moved to remove its ad-targeted equalisation levy recently as it reshapes its approach. That shows the political and diplomatic balancing act these policies trigger

    Meanwhile, the OECD’s Pillar work (on reallocating taxing rights and minimum tax rules) has been the more multilateral route to address digitalisation’s tax challenges — not a customs-style tariff replacement.

    Political friction persists: unilateral digital levies have provoked threats of trade retaliation or countermeasures, so any broad replacement strategy risks escalating trade tensions.

    Key economic, legal and technical risks

    • Double taxation / diplomatic blowback. Unilateral digital levies can lead to disputes or retaliatory tariffs; they may also overlap with corporate income taxes creating double taxation.
    • Evasion and routing. Digital services can be restructured, routed through low-tax jurisdictions, or bundled in ways that defeat simple levies. That undermines both revenue and policy intent.
    • Measurement problems. How do you measure “use” or “consumption” reliably (users, clicks, compute hours, data ingress/egress)? Poor metrics produce inequitable rates and gameable incentives.
    • Fragmentation risk. If every country erects different digital tariffs, commerce will fragment, compliance costs will explode, and global digital supply chains will suffer — the exact opposite of the open network many economies depend on.
    • Conflict with trade commitments. Many trade agreements and the WTO framework assume non-discrimination and predictability; a wholesale shift to digital tariffs would require renegotiation of these commitments.
      White & Case

    How digital tariffs should be used — a pragmatic policy framework

    Rather than a “replace” strategy, think “complement and coordinate.” Here’s a balanced recipe:

    • Use targeted digital levies for specific objectives (revenue gap, consumer protection, data-localization incentives), not as blunt substitutes for goods tariffs.
    • Prefer tax-style instruments over customs-style tariffs where possible — e.g., place-based digital taxes that allocate taxing rights to user jurisdictions (the OECD approach) reduce trade frictions and legal risk.
    • Design clear metrics and thresholds. Only large multinational digital service providers should be in scope initially; exclude small cross-border sellers to avoid stifling SMEs.
    • Coordinate regionally and multilaterally. Work through blocs (EU, ASEAN, G20/OECD) to harmonize rules and avoid fragmentation. The WTO moratorium and OECD negotiations illustrate why multilateral paths matter.
    • Pair digital levies with domestic measures for fairness. If a levy raises prices for consumers, use part of the revenue to subsidize access, support digital literacy, or invest in local cloud/AI infrastructure.
    • Transparency & dispute resolution. Publish rules, use neutral metrics, and accept arbitration to avoid trade flareups.

    Distributional & development considerations

    For advanced economies, digital levies might be about fairness and revenue redistribution from large global platforms. For developing countries, digital tariffs could be tempting as quick revenue sources — but they risk scaring off investment or driving platforms to restrict services. Careful calibration and international support are needed so poor countries don’t pay the political or economic price for digital protectionism.

    Bottom line — the simple verdict

    Digital tariffs are useful tools, but they aren’t substitutes for traditional tariffs. They work on different economic levers and carry different risks.

    Policy mix is what matters. Use digital levies to capture digital value, protect users, or incentivize local investment — but retain traditional tariffs (and other instruments like subsidies, regulation and industry policy) for physical-goods protection and industrial strategy.

    International coordination is essential. If countries act alone, the result will be messy: trade friction, double taxation, and fragmented digital markets. The multilateral route (OECD, WTO, regional blocs) is slow, but it reduces blowback.

    If you want, I can:

    Draft a short policy memo (1–2 pages) that outlines how a medium-sized economy could introduce a targeted digital tariff while minimizing risks; or

    Build a one-page explainer comparing outcomes if a government replaced 25% of its goods tariffs with a digital levy (distributional effects, likely retaliation, revenue volatility); or

    Sketch two sample legislative clauses: one for a narrowly-targeted digital services levy, another for a carbon-adjusted import duty.

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daniyasiddiquiEditor’s Choice
Asked: 05/09/2025In: ,

will students return fully to physica ...

education
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    The Pandemic Shift That Changed Everything When the pandemic closed schools all around the globe, millions of students were overnight plunged into learning at home. What had been considered a backup or an experimental solution became the norm overnight. Homes became classrooms, teachers mastered vidRead more

    The Pandemic Shift That Changed Everything

    When the pandemic closed schools all around the globe, millions of students were overnight plunged into learning at home. What had been considered a backup or an experimental solution became the norm overnight. Homes became classrooms, teachers mastered video calls, and students learned both the flexibility and exhaustion of learning from home. This global trend set a large question: Was this only a short-term solution, or the start of a long-term shift in education?

    Why Remote Learning Isn’t Going Away Entirely

    Remote learning opened up new doors that are difficult to dismiss:

    • Accessibility: Rural students, or students with disabilities, suddenly had more access to education without the obstacle of traveling.
    • Flexibility: Older students in particular appreciated learning at their own pace—rewinding a taped lecture or doing assignments in flexible time slots—felt empowering.
    • Global Classrooms: An Indian student could take a coding workshop from a U.S. professor. That sort of borderless learning was not common before.

    For most, these advantages were a preview of the possibilities for education to be more inclusive and flexible.

    The Human Pull of Physical Classrooms

    But as classrooms reopened, another truth became clear: students missed each other. Education isn’t just about knowledge transfer—it’s about community, belonging, and growth through human interaction. In-person schools offer moments that screens can’t replicate: the chatter before class starts, group projects where creativity flows in real time, and the encouragement of a teacher’s smile when you’re struggling.

    Physical classrooms also give students structure. Students missed the structure, and many had trouble with focus, isolation, and motivation in remote environments. Schools are more than institutions to acquire knowledge—they are havens of safety where kids and young adults develop friendships, become resilient, and learn life skills.

    A Likely Future: Hybrid Education

    • Instead of an either-or solution, the future of learning could be a hybrid model. Schools could blend the best of both worlds:
    • Traditional classrooms for social interaction, collaboration, and personal guidance.
    • Online platforms for flexible assignments, supplementary lessons, and access to global expertise.

    For example, a high school student might attend math and literature in person but take an advanced coding or language course online from an international instructor. This blended model gives students a richer, more customized education.

    Challenges That Still Need Solving

    While the idea of hybrid learning is exciting, challenges remain:

    • Digital Divide: Not every family can afford laptops, high-speed internet or quiet learning spaces. If not addressed, remote learning could deepen inequality.
    • Screen Fatigue: Too much online learning can lead to burnout and health issues, especially for younger children.
    • Teacher Training: Educators need support to adapt their teaching methods for hybrid models, rather than simply transferring old lessons onto screens.

    Final Thought

    Remote learning isn’t a trend it will inevitably fade within the inevitable tides of time. Instead it is firmly securing a place in the future of education. But remote learning won’t entirely replace the classroom, because education isn’t just about knowledge-it’s also about connection and community. Classrooms tomorrow could be blended spaces where technology expands opportunities but in-person learning continue to shape their social, emotional lives.

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daniyasiddiquiEditor’s Choice
Asked: 05/09/2025In: ,

traditional classroom teaching, or si ...

aieducationtechnology
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    The Rise of AI in Learning Over the past several years, AI tutors moved from lab equipment to ubiquitous companions on bedroom floors and classroom desks. Devices that can immediately answer a mathematical question, learn a language, or accommodate a child's skill set are now within reach of tens ofRead more

    The Rise of AI in Learning

    Over the past several years, AI tutors moved from lab equipment to ubiquitous companions on bedroom floors and classroom desks. Devices that can immediately answer a mathematical question, learn a language, or accommodate a child’s skill set are now within reach of tens of millions of students. To most, they’re virtually wizardly: an on-demand teacher in one’s hand 24/7.

    What AI Does Extremely Well

    • AI teachers are best used in conditions where human teachers repeatedly fail on a time and quantity basis. They are able to:
    • Give immediate feedback on an individual basis.
    • Adjust teaching based on individual learning rates.
    • Display unlimited patience when one student repeats the same mistake.
      Speaking in several languages to prevent learning obstacles.
      For the night student having trouble with algebra, an AI teacher brings instant comprehension, something a typical classroom setting cannot.

    The Indispensable Work of Human Educators

    And that’s the truth: learning is not just information transfer. Great teaching is guidance, encouragement, and human contact. Teachers have a sense of what no computer program ever will: the little signals—a struggling student, a lack of confidence, the glint of interest in an eye—that can be the difference. They build not just minds but character, ethics, and social skills.

    A classroom is also a social setting. It’s where kids learn how to collaborate, feel for others, negotiate, and recover—skills that extend far beyond academic competence. No computer software, no matter how clever, can replace the reassurance of support from a teacher who believes in you.

    The Future: Cooperation, Not Replacement

    Instead of viewing AI as a replacement for educators, it is possible to view AI as an aide or co-pilot. Imagine a teacher utilizing AI to grade repetitive assignments, so they have more time for one-on-one mentorship. Or an AI system informing teachers that they need to provide special assistance to certain students so that they may react more effectively.

    In this manner, AI teachers would actually make instructors more human, removing the mechanical aspect of the profession and allowing teachers to concentrate on guidance, empathy, and creativity.

    Risks to Watch Out For

    Of course, we also have to be careful. Overuse of AI may:

    • Decrease critical thinking development if students rely on it for “answers” instead of learning.
    • Widen inequality if only rich families or schools will still be able to afford quality AI tutors in the future.
    • Cause burnout among teachers if they are being asked to compete with machines instead of being aided by them.

    Final Thought

    AI teachers are not here to replace educators—they’re here to boost learning. The future most likely holds is a hybrid approach, one in which AI provides customized advice, yet human educators continue to motivate, advise, and influence people in ways that no computer program ever could.

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daniyasiddiquiEditor’s Choice
Asked: 04/09/2025In: , , ,

digital goods and AI services, not ju ...

newstechnology
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    Alright, let’s get real—tariffs made sense back when the world was all about factories belching smoke and ships lugging boxes of stuff from one country to another. Picture crates of steel, heaps of car parts, mountains of T-shirts… slap a fee on ‘em at the border, and boom: your local industry getsRead more

    Alright, let’s get real—tariffs made sense back when the world was all about factories belching smoke and ships lugging boxes of stuff from one country to another. Picture crates of steel, heaps of car parts, mountains of T-shirts… slap a fee on ‘em at the border, and boom: your local industry gets a bit of extra oxygen and the government grabs some cash for its rainy-day stash. Simple. Material goods, physical borders, easy math.

    But now? The whole thing’s basically turned into some weird digital Hunger Games. Everything’s in the cloud. Apps, Netflix binges, AI doodads—hell, people are dropping cash on pixelated sneakers and meme cats (yeah, NFTs, if you want to get technical). Meanwhile, the rules? Still stuck in the Stone Age, shuffling paperwork for things you literally can’t hold in your hand.

    So, why even mess with digital tariffs? Some folks are convinced it’s the only way for the “little guys” to stand a chance. Imagine you’re this plucky AI startup in Brazil, just trying to make rent, and then Google or Microsoft rolls in and wipes the floor with you. A digital tariff might actually slow the big guys down, give you a fighting shot. There’s also the whole “hello, pay your fair share” angle—giant tech firms hoover up profits from every corner of the map, but local governments? They’re lucky to find pocket change. A digital tax could actually make them cough up.

    And yeah, let’s not forget data sovereignty. Countries want a say over where their people’s data goes. Taxing cross-border data or foreign AI services? That’s one way to yank back a little control.

    But, come on, it’s a minefield. Jack up the price of cloud tools and suddenly college kids, indie devs, and tiny businesses are paying extra just to keep the lights on. Not exactly the dream. Plus, it could totally mess up the open, collaborative vibe the internet’s got going—coders building stuff across continents, scientists teaming up online… that could get ugly real fast. And if countries start lobbing digital tariffs at each other? Congrats, now you’ve got yourself a virtual trade war. Spoiler: lawyers win, everyone else loses.

    Some brainiacs—sorry, “industry experts”—say digital service taxes might work better. Rather than whacking everything with a fee, you just tax profits or usage. Feels a bit less like using a sledgehammer to swat a fly. Or maybe, wild idea, the world’s rule-makers could actually update the rules. The WTO, OECD, whoever—somebody’s gotta step in before it’s total anarchy.

    But, end of the day, this isn’t just about spreadsheets. It’s about real people. Imagine a tiny animation studio in India, hustling to sell their work in Europe. Smack them with digital tariffs and they might just pack up shop. But if you let the tech titans have free rein, they’ll squash everyone in sight, homegrown talent included.

    So yeah, digital tariffs: are they a necessary evil, or just innovation’s latest buzzkill? How do you protect the underdogs without nuking the whole system? No clue, honestly. But one thing’s obvious—the old-school playbook has officially expired. Someone’s gotta cook up a new one, and fast.

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daniyasiddiquiEditor’s Choice
Asked: 03/09/2025In: , ,

the gap between rich and poor nations

aitechnology
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

     The Hope vs. The Fear Artificial intelligence has been called "the great equalizer" and "the great divider." On the one hand, it holds the potential to provide every individual with internet connection access to knowledge previously reserved for the elite—medical advice, legal advice, business planRead more

     The Hope vs. The Fear

    Artificial intelligence has been called “the great equalizer” and “the great divider.” On the one hand, it holds the potential to provide every individual with internet connection access to knowledge previously reserved for the elite—medical advice, legal advice, business planning, even high-end tutoring. On the other hand, creating and deploying these AI systems takes enormous data, capital, and computing power, resources in the possession of a few successful nations and firms.

    So will AI close the gap or increase it? The answer is nuanced—because it will depend on how AI is designed, shared, and regulated.

    How AI Could Level the Playing Field

    Envision a physician at a rural clinic in Kenya using an AI assistant to diagnose illness without the need for pricey lab equipment. Or a Bangladeshi business with access to AI marketing strategies on par with those of multinational firms. Or a student at a village far from a city in India doing math with an AI tutor that adjusts their learning speed.

    • AI can cause knowledge and proficiency to be more evenly spread:
    • Education: AI instructors can possibly provide tailored instruction to millions of those who lack access to quality schools.
    • Healthcare: Telemedicine and diagnostics based on AI could be extended to remote areas.
    • Entrepreneurship: Small enterprises of poorer countries could compete with the world using AI without large budgets.

    This way, AI can potentially bypass infrastructure deficits—just like mobile phones enabled developing countries to bypass the costly installation of landlines.

     How AI Might Widen the Gap

    • There is, however, another aspect to the coin: AI craves energy. It needs to be trained on:
    • Ginormous computing resources (supercomputers, power, and state-of-the-art chips).
    • Massive amounts of data, usually controlled by giant tech companies.
    • Expert ability, which in return tends to group in rich countries.
    • This raises the possibility of AI colonialism: where rich nations create, own, and benefit from AI systems, and poor countries are passive receivers. For instance:
    • If large corporations in the US or China own AI, poor countries can “rent” but cannot develop their own.
    • Language and cultural bias in AI systems may silence Global South voices.
    • Those with inadequate digital infrastructures may be left behind completely.

     The Transition Dilemma

    And as with work, there is even an issue of timing here. Rich countries are leading the charge, and poor countries are trying to get into the game of bringing in AI. This disparity can have the possibility of creating new dependency—where poorer countries are depending upon AI systems they may not even own, just as many are presently depending upon drugs or technology brought in from abroad.

    What May Make the Difference

    • Whether AI will bring us together or tear us apart will be determined by decisions being made today:
    • Open-Source AI: If big models stay open, smaller countries can adapt them to their specific needs.
    • Global Cooperation: Global institutions can make AI a global right, and not pay-for.
    • Local Innovation: Developing local AI firms in Africa, South Asia, and Latin America could create solutions contextually appropriate.
    • Digital Infrastructure: Power, internet connectivity, and investment in education is a necessity for any country to realize the advantages of AI.

     The Human Element

    To an individual in Silicon Valley, AI is a productivity tool. To a teacher in Nigeria, it might be the sole means of teaching in classes that have 60 students. To a farmer in Nepal, a weather forecast generated by AI may mean the difference between a profitable harvest and a whole season lost.

    That’s why this isn’t just geopolitics—it’s whether technology will be for the many or the few.

     So, Which Way Will It Go?

    If things go on as they are, AI is going to exacerbate the gap in the short run because already wealthy countries and companies are racing far ahead. But with proper policies, collaborations, and open innovation, AI can turn out to be a great leveller, as mobile technology revolutionised the reach of communications.

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daniyasiddiquiEditor’s Choice
Asked: 03/09/2025In: , ,

replacing jobs faster than new ones

aicompanytechnology
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    The Battle Between Opportunity and Fear Whenever there is a powerful new technology entering society—whether it's electricity, the steam engine, or the internet—it always poses the same question: Will this replace jobs, or will it create new ones? With AI, the issue appears more acute because the teRead more

    The Battle Between Opportunity and Fear

    Whenever there is a powerful new technology entering society—whether it’s electricity, the steam engine, or the internet—it always poses the same question: Will this replace jobs, or will it create new ones? With AI, the issue appears more acute because the technology isn’t just about robots doing brute labor, but also about computer software doing things thought to be uniquely human—like writing, designing, interpreting data, or even making decisions.

    Work Being Replaced—The Reality Check

    • Artificial intelligence is actually replacing certain forms of work at a faster pace than most expected.
    • Repetitive office tasks—data entry, calendaring, reporting—are increasingly automated.
    • Customer service jobs are being done by AI chatbots that don’t need sleep.
    • Creative sectors—content writing, image-making, video editing—are being shaken up because AI software can spit out drafts in seconds.

    For most employees, it’s rug-pulling, not from under their feet, but from right out from under them. Contrary to the industrial revolution, where physical labor was forced out but “thinking” work wasn’t hurt, AI is entering both physical and mental space. That’s why the disruption is coming so abruptly and overwhelmingly.

     Creating New Jobs—The Unseen Side

    • And here’s the less apparent reality: AI is creating new types of work altogether.
    • AI trainers and ethicists—individuals who train models to act responsibly.
    • Prompt engineers and workflow designers—jobs that did not exist a few years ago.
    • AI oversight and governance experts—assisting businesses and governments to ensure that AI is being used responsibly.

    Hybrid careers—where an individual works side by side with AI, like doctors working in collaboration with AI to detect very subtle patterns in scans, or teachers working with AI to tailor their teaching.

    Just as the internet developed careers we could not have envisioned in the 1990s (say, social media directors or app engineers), AI is developing industries still in their infancy.

     The Timing Gap—Where the Pain Lies

    • The issue isn’t whether AI will eventually balance job loss with job gains—both will happen—it’s the timing disparity.
    • Jobs currently being lost are evaporating today.
    • New positions that are being created need new capabilities that the majority of employees currently don’t possess.
    • This makes for an uncomfortable period of transition during which some get left behind while others jump ahead. For instance, a factory worker whose position is taken over by machinery can’t overnight just turn into an ethicist for AIs without retraining. That retraining involves time, work, and capital that not everyone possesses.

    Human Adaptability—The Real Advantage

    History attests to humanity’s incredible ability to adapt. Every technological advancement has always ultimately led to a greater economy, greater range of occupations, and greater levels of living. The critical point has always been training and support mechanisms:

    • Those nations that spent on retraining in previous revolutions were better positioned to make the jump.
    • Those who accepted life-long learning survived while the rest became obsolete.
    • AI isn’t something to be afraid of—it can be a very powerful ally if we go at it with curiosity rather than fear.

     The Human Side of the Debate

    It is easy to lose track of numbers, but the heart of this issue are real people—a call center agent worried about paying bills, a student wondering what profession to pursue, a parent worried about where their child will end up in life. The alarm is real because employment is not just about salary; it is about identity, self-worth, and purpose.

    That is why how the society reacts is important. If AI adoption is accompanied by social safety nets, retraining programs, and smart regulation, it can elevate human beings to new levels. Without these, it threatens to exacerbate inequality and disillusionment.

     So, Is AI Replacing Jobs Faster Than It Creates Them

    Today, yes—replacement is driving creation. But it does not have to be doom. If we use AI as a means of augmenting human capacity rather than simply reducing costs, and if governments and businesses invest in individuals, the future is far better than today’s fears indicate.

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mohdanasMost Helpful
Asked: 03/09/2025In: , ,

patients, hospitals, or tech companie

aicompanydigital health
  1. mohdanas
    mohdanas Most Helpful

    Who Actually Owns Your Health Data? Spoiler: It’s Complicated Every time you see your doctor, get a blood draw, or even just strap on your Fitbit, you’re tossing more health data out into the universe. You’d think, “Hey, it’s my body, so that’s my data, right?” Ha. Not so fast. Your hospital’s got aRead more

    Who Actually Owns Your Health Data? Spoiler: It’s Complicated

    Every time you see your doctor, get a blood draw, or even just strap on your Fitbit, you’re tossing more health data out into the universe. You’d think, “Hey, it’s my body, so that’s my data, right?” Ha. Not so fast. Your hospital’s got a stash of your records, labs have their own pile, and Apple or Google probably knows more about your heart rate than your cardiologist does. It’s like a tug-of-war over who really gets to call your info theirs.

    Gatekeepers in White Coats

    For ages, hospitals have acted like the bouncers of your medical history. You wanted your records? Good luck—maybe they’ll fax you a copy if you beg (and pay). Now, with electronic health records, sharing is technically possible, but let’s be real: the hospital still guards the vault. You’re often left feeling like a peasant asking the king for access to your own castle.

    Tech Bros and Data Hoarding

    Then you’ve got the tech companies. They’re quietly sitting on Everest-sized mounds of your personal stuff—steps, sleep, DNA, you name it. Most of the time, you don’t even realize how much you’ve handed over. And they’re cashing in on it, too—selling “insights” or training their AI, all based on your biometrics. Is it still your data if it’s being chopped up and sold to the highest bidder? Who knows.

    The Patient: Alleged Owner, Actual Bystander

    You’d think patients would be the boss here. After all, it’s literally your blood, sweat, and tears (sometimes all three). But, honestly, most people can barely get a full copy of their own health record, let alone control who sees it or uses it. “Ownership” is a cool idea, but it’s mostly just a buzzword right now. In practice, patients are sitting on the bench while everyone else plays ball.

    Why Should You Even Care?

    Because it’s not just about paperwork. If hospitals lock up your files, switching doctors becomes a nightmare. If someone leaks your private info, your dignity (and maybe your job) is on the line. And hey, sharing health data can lead to wild breakthroughs—AI that finds cancer earlier, new treatments—but if nobody asks your permission, it’s just another way to get screwed.

    The Models: Pick Your Poison

    – Old School (hospital-based): Hospitals hold the cards, and you need their blessing for access.
    – Tech Takeover: Apps and gadgets hoard your data, usually without much oversight.
    – Patient First (the dream): You get the keys—view, share, delete your records. Some countries are actually trying this, believe it or not.

    A Better Way: Stewardship, Not Ownership

    Maybe it’s not about “owning” your data, but about who you trust to watch over it. You should be in the driver’s seat, deciding who gets a peek and why. Hospitals ought to keep it safe; tech companies should stop being so shady and actually ask before using your stuff. “My body, my data”—sure, but with some grownups making sure it doesn’t get lost, stolen, or misused.

    Bottom Line

    Right now, hospitals and tech giants are running the show, but the only real owner of your health info should be you. The trick is building systems where you get easy access, know exactly what’s happening with your data, and can actually say “nope” to anything you don’t like. Otherwise? It’s just business as usual… and you’re still on the outside looking in.

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mohdanasMost Helpful
Asked: 03/09/2025In: , ,

diagnostics outperform doctors, or sh ...

  1. mohdanas
    mohdanas Most Helpful

    The Wild, Weird Future of AI in Medicine Alright, let’s cut to the chase—AI’s been storming into medicine like it owns the place lately. These code-wizards? They chew through scans and spit out stuff even the sharpest docs would miss. Tumors, oddball patterns, “hey, your heart’s acting up”—all thatRead more

    The Wild, Weird Future of AI in Medicine

    Alright, let’s cut to the chase—AI’s been storming into medicine like it owns the place lately. These code-wizards? They chew through scans and spit out stuff even the sharpest docs would miss. Tumors, oddball patterns, “hey, your heart’s acting up”—all that jazz. It’s wild. Seriously, no human’s chugging through data at this pace. For patients, it’s a complete level-up: fewer twiddling-your-thumbs-in-waiting-rooms, answers before you even knew you had a question, the whole shebang.

    Doctors vs. Robots: Not the Showdown You Think

    Here’s the thing, though. Just because a computer can detect a lump in a nanosecond, that does not mean you’re going to be getting your next diagnosis from a talking toaster. Docs possess that sixth sense—you know, intuition, gut instincts, the things you can’t program. AI says “hey, this blob is weird,” but your doc puts the pieces together: your cough, your past traumas, the breakdown about your cat last Tuesday. It has nothing to do with being the robot who’s always right; it has everything to do with being the human being who understands.

    Where AI Absolutely Crushes

    Scanning pictures, day in and day out—radiology, pathology, whatever. AI never gets distracted or misses a pixel.
    Acting as alarm system—cancer, diabetes, eye disease, name it. Sometimes before you even feel off at all.
    Repetitive, dull tasks—AI thrive on the stuff that makes people want to scream.

    It’s not that the robots are so smart, they just never get tired or have a hissy fit during shift time.

     Where Humans Still Rule

    – The dirty stuff—actual patients don’t read from the script, believe me.
    – Delivering the bad news, soothing freak-outs, figuring out when to shut your mouth and listen. Luck with teaching an algorithm bedside manner.
    – Ethics. Do we attack full bore with treatment, or is comfort care the way? AI regurgitates numbers, but human beings understand what counts.

     Dream Team, Not Mortal Enemies

    Seriously, it’s not a war. AI is not going to swipe your doctor’s white coat—it’s the world’s most compulsive intern, checking twice, flagging suspicious activity, but the doc’s still in charge. Team, baby. Fewer caught errors, less human mistake, better outcomes for you.

    Don’t Bow Down to the Algorithm

    But seriously, let’s not make AI some robot messiah. Bad data? The AI simply amplifies the screw-ups. Doctors questioning their own judgment? That’s a trainwreck. And when the tech fails—whose fault is it? Yeah, that becomes awkward.

    Medicine Requires Actual Humans

    Bottom line: AI’s not booting doctors out, it’s giving them superpowers (well, almost). People want a human talking to them, not just a screen spitting out diagnoses. But if a bot can spot something your doc missed? Use both, why not?

     

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