Technology, Equity and Equality in Education

The Paradox in Education

If the future of education offers teachers, books, conversation, and critical thinking for some, and algorithms, robots, and screens for others, technology will not have closed educational gaps - it will have institutionalized them.

By Maria Mercedes Mateo-Berganza Diaz

Teachers and books for the rich, robots and screens for the poor?

When we talk about technology for education we think of tablets, laptops, robots or interactive platforms with which children learn new (coding) or traditional skills (mathematics) better or faster.

Raised like this, it seems inevitable to imagine that students or higher income schools have the most access to this type of resources.  But, what would happen if access to technology in the coming years is not a privilege, but the cheapest way to access educational services?

Thus began an article recently published in The New York Times: "Hypocrisy thrives at the Waldorf School of the Peninsula in the heart of Silicon Valley.  This is where Google executives send their children to learn how to knit, write with chalk on blackboards, practice new words by playing catch with a beanbag and fractions by cutting up quesadillas and apples.  There are no screens — not a single piece of interactive, multimedia, educational content. The kids don’t even take standardized tests(...)".

Surprising, isn’t it?

Latin America and the Caribbean is investing more and more in technological equipment and digital resources to close the skills gap in the labor market and the learning gap between high and low income students.

By contrasting these efforts with the New York Times description of how the most privileged learn, it is worth wondering whether technology, after all, could potentially increase inequality in skills and learning.

The lessons that matter the most

One of the core objectives of education systems is to promote learning that prepares children and youth not only for the labor market, but also to contribute to create more prosperous societies.  It is known that to access good jobs, a combination of technical skills and soft skills is required.  This is nothing new.  What is changing is the relative distribution of both.  Although cognitive skills are still strongly related to results in the labor market (in terms of participation and income), their importance has been falling in the last two decades, while returns to soft skills have been increasing.

This trend is not accidental: to survive in the world of automation, it is a priority to teach young people what machines cannot do, because jobs that require imagination, creativity and strategy are more difficult to computerize.

An interesting fact comes from a study conducted by Google in 2013 to understand if their recruitment strategy focused on "hard skills" in computer science was appropriate.  The results showed an uncomfortable reality: seven of the eight most important qualities shared by the highest-performing employees were soft skills such as being a good coach, communicating and listening well, knowing their colleagues well, empathy, critical thinking, problem solving, and connecting complex ideas.  The technical competences in STEM fields came in last.   

Learning while knitting: something more than a trend

Faced with this boom of soft skills, learning to knit, write with chalk or practice new words while playing with balls are activities that go beyond a Silicon Valley fashion.

This type of education becomes a strategy to innovate, as the article in the New York Times said: "While Silicon Valley's raison d'être is to create platforms, applications and algorithms to generate maximum efficiency in life and work (a "frictionless" world, as Bill Gates once put it), when it comes to their own families (and also developing their own businesses), the new masters of the universe have a different sense of what it takes to learn and to innovate: it is a slow and indirect process, it is necessary to meander, not run, allow failure and chance, even boredom."

To close the skills gap in the region, we cannot forget the fundamentals behind this approach, but without losing sight of the fact that technological change comes at a galloping pace and offers new possibilities for children and young people.

The New Frontier of Educational Inequality

Today, the question that opens this article is no longer a simple provocation.  The rapid expansion of artificial intelligence—capable of teaching, assessing, providing feedback, and personalizing learning at scale and at very low cost—is redefining what we mean by education and how it is delivered.

Educational technology is increasingly emerging as the most affordable and scalable way to provide educational services, especially in contexts marked by teacher shortages and limited resources.  Automated tutoring, adaptive platforms, and AI-based assistants promise to expand access and close learning gaps.  Yet this same promise carries a profound risk: that machine-mediated education becomes the norm for lower-income students, while more privileged settings continue to invest in deeply human educational experiences—rich in teachers, dialogue, critical thinking, art, philosophy, and time to learn without haste.

The paradox becomes clearer: the more sophisticated the technology, the greater the value of what is human.  And that value is not distributed automatically or equitably.  In a world where algorithms can deliver content, practice skills, and optimize learning pathways, the central question is no longer whether to use technology.  The question is what kind of learning we reserve for whom.  If technology is used to replace—rather than complement or enhance—the pedagogical relationship with teachers, vulnerable contexts risk drifting toward an even more stratified education system: automation for some, humanity for others.

The real challenge, then, is not to incorporate more devices, but to clearly define which learning experiences are non-negotiable for all.  Educational innovation is not about cutting costs through screens, but about ensuring that technology amplifies—rather than substitutes—what makes learning profoundly human.

Because if the future of education offers teachers, books, conversation, and critical thinking for some, and algorithms, robots, and screens for others, technology will not have closed educational gaps—it will have institutionalized them.

Learning to learn again in the age of AI

In April 2025, the IDB released AI and Education: Building the Future Through Digital Transformation, a report that examines the role of artificial intelligence through the lens of what we already know from decades of digital education.

We invite you to explore the IDB’s latest report on Artificial Intelligence and Education, and discover how teachers across Latin America and the Caribbean are already integrating AI into their classrooms — based on new data from CIMA Note #37, drawn from the international TALIS 2024 survey. 

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The Good, Bad and Ugly Impact of Artificial Intelligence (AI), and Social Media on Humanity

 

The Expanding Influence of Artificial Intelligence (AI) and Social Media on Human Life and Culture

By Professor Gilbert Morris
Nassau, N.P., The Bahamas

LET’S STOP UNINFORMED NONSENSE; SOCIAL MEDIA AND AI ARE A THREAT TO HUMAN EXISTENCE!

How do sane people read this and compare it to the printing press or people’s fear of technologies?

That is mere duffus barking!  This is different.  It was possible to get away from those technologies.

No one became addicted to their wrench, sewing machine or their refrigerator or their lawnmower.  These technologies did not have the capacity to give some unknown person or system access to one’s life and nor have they capacities to manipulate one’s opinion on nearly every aspect of life.  The scale of the impact of the automobile, the telephone and the airplane was they they did not replace everyday repetitive or creative tasks; with the capacity to retain personal data.

Social media and Artificial intelligence are different in every respect and represent both opportunities to build a good society - as my colleagues Daniel Schmachtenberger, Tristan Harris and Audrey Tang are trying to do - and yet because of the power relations of our social, political and economic models, they pose a virulent existential risk; if only because we are stupid enough to misread the doltish pleasures it gives us - for now - whilst ignoring what it’s done already, what it’s doing and will do.

Social media was not designed by techies - who are often brainless about psychology and sociology - it was designed by cognitive neuroscientists and game theorists on the psychology of girls 13-27. (This is not new as sociologist Thorstein Veblen, Max Weber and Edward Bernays built the social and legal models for the Industrial Revolution).

Now at one end: it’s Peter Theil, Mark Andreessen and Curtis Yarin and at another Nick Bostrom, Josha Bach and the social media and AI Leviathans.

Why did they premise the psychology of girls and young women?  Because that demographic is the most powerful, most attractive, most consistent seekers of attention in human history.  Anything pitched to that demographic sells.

Mothers dote on them, fathers adore them…all men - even wicked ones - want them and they become promiscuous attention seekers almost naturally.

Get them to adopt a trend and it becomes a fad that is monetisable.

In the attention economy, they all get to act like celebrities talking bogus nonsense about “boundaries” and “my followers”, 80% of whom are BOTS!

At universities, we are seeing psychological derangements and dissonances…a child at 18 gets 25,000 followers for nothing; no talent, not gifts, no accomplishments.  She naturally thinks it’s her essence, when she has none!

One or two such “influencers” get “brand deals”, and lots more get meaningless package giveaways…and material greed merges with dopamine rushes to entice and enthuse these female youth into an obsession with social media, now powered by AI…not merely to engage…but to capture their psychologies and render than automatons for the social media companies.

This heralds two things in general:

1. For girls, every day there is another 10 million 18 years olds who awaken and are prepared to get naked in social media, so at least for a time, gaining popularity over the previous 18 year olds.  Moreover, social media is one massive dating site in which 80% of the women - convinced that they are 10 (tens) - their term, not mine - prefer only 3% of men, who want none of them, except for “hookups”; this generating unfulfillable expectations, leading to anxieties.

Additionally, take ONLYFANS.  Of the 10 million 18-25 year olds in America, over 1 million are on OnlyFans; so 10% of marriageable aged women, with 80% of the audience as white married males.

That means those marriages are suspect and also means, amongst many things a range of society that’s raising the next two generations of children are engaged in an anti-social building practice: Lawnmowers can’t do that.

These predilections have initiated new human protocols: young women awaken in the morning and go directly to social media and start speaking as if they are speaking to best friends or actual fans.  They engage with comments as if these BOTS/Followers actually care for them.

Imagine you live in a home with someone obsessed with and by social media: you do everything to make your home loving and peaceful.  But that person engaged with some unknown and probably unreal person OUTSIDE YOUR LIVES, brings the tensions and disagreements with that person or thing into your private life!  Think upon that: you private life is constantly subject to the nothingness of some unknown aliens interloper with the power to change the mood of our loved one…and alter the mood and focus of your home.

I believe in deep listening to those about whom we care, but don’t think I could bear listening to the digital rubbish from some social media ghetto and not think the person trying to explain it to me has lost their cotton picking mind!

Worse,when the fake digital crowd leaves the obsessed for the next batch of 18 year olds…they crash psychologically…and depending on what they’ve done online, they may recover only in their mid-30s, now having emptied their youth for nothing without learning, practising or developing proper social skills.

2. For young men, because social media actively promotes a false sense of value for women, young men are bereft of meaningful female interaction, or they face imperious arrogance fuelled by social media delusions.  Now that’s changing?  Why? Because - whilst many of their fathers are on onlyfans - AI is building sexual companions - both online and as robots - and these young men are adopting these fake relations and preferable because they satisfy a single urge in an unlimited manner.

In one episode, a company made a sex robot with docile and “grape” settings.  The latter was preferred.  This makes for a society where young men from 16-27 may learn their basic sexual interaction for interactive porn and robots…which makes for a dangerous world for actual women.

All these modes are fed and feed from clinically tested additive processes deliberately manipulated by social media companies, in addition to colonialising private data, to a point that will make democracy and the nation-state impossibilities.

These are not - by any measure - and not by orders of magnitude anything like ANYTHING we’ve ever known.  Beyond these personal psychological corruptions is broad structural catastrophe that is underway already.

For those who say, but AI would generate new jobs - part of the daft unthinking galloping nonsense oft repeated - think sensibly, a job is a value or earning proposition: if humans make new jobs after AI takes their job…AI would just take the new jobs too, since that maximises income.

Why would AI companies allow humans to earn money when they could and AI could make new AI to take any new job ‘ad infinitum’!

Let’s stop talking nonsense and recognise existential threats to our civilisational models. 

Finally, social media has been successful in dividing humans through psychological manipulation and the undermining of facts.  Keyboard Idiot barkers argue with research professors and think themselves informed by google searches and confirmation biases; which they can’t grasp even when explained.

Yes, we all know social media allows one to connect with cousins, old school friends and to see whether one’s high school love has gotten old and fat.  Meanwhile AI has made stupendous medical advances.  But actual knowledge teaches us the gradient logic of the “double edged” sword: just the energy demand and AI business model will mean:

1. It undermines the labour/wage economic models

2. Even as its makes medical and educational advances

3. Therefore, if you’re jobless, you get nothing from those advances

4. Those advances are distributed to a new super elite class, as the wealth gap widens and political systems become more useless than they are now.

It’s astonishing how people convince themselves that society will suddenly do a good it’s never done, because technology has the capacity for that good.

LISTEN: nearly 90% of AI will aim at building surveillance, control, and weapons.

Why?

Because those generate power…and power grants dominant status…and despite the Old and New Testament and all the loving talk and wisdom books of history…..power and dominant status - I tell you - have been the only sustained ambitions of humankind! 

Governments should have begun 5 years ago to take emergency measures through high level technical task forces: social media and AI impacts are not collateral to national well being…they are central.  The world is being divided…and countries that lack control over their digital architecture, social media, AI deployment, systems construction and maintenance will become digitally colonised.

There is zero option now for partnering with tech giants….since they are already richer than 80% of the world’s nations.  Countries like China, Estonia, India, Singapore and Norway are the last best hope to gain a ready-made solution that does not compromise national security completely.

A hint to the wise!

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How Could Artificial Intelligence (AI) Make a Rewardingly Productive Difference in Infrastructure in Latin America and The Caribbean?

Artifical Intelligence (AI) as An Efficient Driver of Development in Latin America and Caribbean

By Alexander Riobo - Maria Pfeifer

The critical infrastructure sectors in Latin America and the Caribbean (LAC) face growing challenges that threaten their efficiency and sustainability.  Roads, power grids, water systems and public transportation networks show signs of aging and obsolescence, increasing maintenance costs and reducing the quality of services.

Against this backdrop, the Inter-American Development Bank (IDB) is exploring how artificial intelligence (AI) can be applied to infrastructure.  For example, in public transportation, route optimization algorithms are helping reduce travel times and congestion.  In water and sanitation, predictive models make it possible to detect leaks and anticipate outages in distribution networks.  In energy, AI is used to forecast demand and facilitate the integration of renewable energy at scale.

These advances and lessons are covered in the IDB’s publication “AI from the Ground Up: Challenges and Opportunities in the context of Latin America and the Caribbean”, which presents real-world cases, recommendations, and practical guidelines on how AI can become a key tool to strengthen the region’s critical infrastructure.

Challenges for Our Infrastructure

Infrastructure in the region faces challenges such as aging physical structures, accelerated urbanization, population growth, and the impact of climate events.  The consequences include disruptions in essential services and rising costs of use, which lead to unequal access.

However, technology can help reverse these trends.  IDB estimates suggest that a 15% reduction in infrastructure service costs through the efficient use of digital technologies could increase the GDP of Latin America and the Caribbean by 6% over the next 10 years.

How AI Can Make a Difference in Infrastructure

Although more than 40% of public agencies in transportation and energy in LAC lack a clear digital transformation strategy, any entity can implement AI-based projects.  In critical infrastructure sectors, the implementation of machine learning models is already within reach for many governments and organizations.

Some concrete examples show this potential in the region across three areas:

• Energy: AI systems predict consumption patterns and help balance supply and demand, facilitating the integration of intermittent renewable energies such as solar and wind.
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• Water and sanitation: Predictive models supported by smart sensors allow detection of invisible leaks and anticipation of pipe ruptures, reducing water losses and maintenance costs.
• Transportation: Traffic optimization algorithms help reduce congestion and improve route efficiency in urban public transport.
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Effective AI Adoption

The report offers the following recommendations to unlock AI’s potential in critical infrastructure sectors:

• Adopt agile methodologies that include proof of concepts, prototypes, and minimum viable products.  These tools make it possible to experiment with AI-based solutions before scaling them.

•  Establish organizational structures that drive AI adoption, ensuring that teams have the necessary technical skills.

• Data quality determines the success of AI projects.   Building high-quality data requires identifying sources, designing efficient data flows, and ensuring adequate architectures for storage and processing.

• Evaluate infrastructure requirements from the outset, especially storage and computing capacities needed for AI models.

• Ensure that AI models address specific and measurable problems, based on data quality, computing capacity, explainability, and performance.

• Incorporate ethical principles from the design stage, addressing privacy, security, and transparency to build trust in solutions.

AI as a Driver of Development

We invite you to explore these recommendations in detail in “AI from the Ground Up: Challenges and Opportunities in the context of Latin America and the Caribbean.”

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Energy is the impediment that will drive the geopolitics behind enterprise tech and AI dominance

There isn’t enough power in the developed world for deployment of these new technologies for even 50% of population, much less AI countries

REMARKS: H.E. Ambassador Professor Gilbert Morris at Bahamas Diplomtic Week Forum on AI and Development

I have only just returned from 10 weeks of lectures and seminars on “AI and the Human Future” in China, Singapore, London, Panama, Mexico and California; which included touring the facilities of the companies and engaging with the individuals who are designing the human future, together with those financing them.

The aim was to both to gain and to explain the actual state of affairs of the coming techno-centric human future:

It’s necessary to state hard facts that are beyond mere opinions or positive or negative perceptions:

1. Only 7% of world’s nations produce any AI tech.  This means 93% have little to no say in AI architecture, design or deployment.  Our definitions of “keeping pace with innovation” usually means someone else’s innovations!

2. In today’s world, that “someone else’s” will be increasingly a non-state actor: Google’s “Gemini” or Anthropic’s “Claude” - Facebook or NVIDA are all larger that 90% of the worlds nations in valuation terms and there is nothing small states can do to get them to alter their technologies for our benefit.

3. Of the 93% of nations left, about 1/3rd are role model states - Denmark, Netherlands, Sweden, Finland, New Zealand etc - with exceptions like India, Singapore and Estonia.  These states don’t manufacture enterprise technology, but they have the means to acquire and manufacture components of enterprise tech, which gives them leverage.

4. The rest are spilt in two; neither of which has leverage: first are mere consumers of tech, whose systems and infrastructure will change to conform to the tech they commune.  Second is the abject “digital divide” where they they will have to make do with dregs and second-hand tech.  They will - by current structures - live off the scraps.

5. ⁠The Promised Balance is Eroding: AI has had diagnostic breakthroughs in health and public-facing innovations in immigration and eGovernment in Singapore and Estonia, for instance.  But the innovations are outpacing the very concept of the nation state, as technology is developing faster than societies, economic and legal systems can adapt.

6. ⁠Social Media now enhanced in impact and speed-of-spread by AI, is producing distortions of reality and neuro-cognitive atrophies; which has reached crisis levels amongst young people and crisis levels in schools and universities.  More than 2 dozen nations have banned social media access for children at school or between 7pm and 7am; with China limiting social media to 2 hours per day for children.

7. ⁠At the heart of social tech is personal identity: Estonia solved this by declaring that a citizen is now the unity of one’s Biological and Virtual self; a unified identity.  Estonia also made internet access a Human Right in their Constitution; additionally, Estonia held their last 8 General Elections online for 1.3 million people.  In Estonia, AI does not replace people but is structured and used to enhance human life and social systems.

URGENT PRIORITIES:

1. We need humane technologies that prioritises humans and enhances human living systems rather than render humans useless.  Some sociologists argue that we are too divided for to generate the needed solutions.  But I find that people are not divided: “they are being divided” for the benefit of a few tech companies.

2. ⁠Social mapping, Economic Mapping, Health and Payments tech, Plurality Systems aimed at enhancing political participation are the best uses for AI and enterprise technologies.

3. ⁠The problem - AGAIN - is, small nations in the 93% don’t create this tech and it’s being designed by those creating it for human control rather than human enhancement.

4. ⁠Small nations must urgently align and cooperate to ensure tech deployment at a pace of social absorption, without the ill-effects of limbic-colonialism or dopamine lust!

5. ⁠Small nations must convene a global congress aimed at setting new rules that will change our economic models across the world more in the next 3 years than the last 1,300 years.

6. ⁠But there are additionally two main crucial matters:

a. Even if managed well, AI will induce massive labour destabilisation.  It’s not enough to say it will create jobs because AI companies will create AI to take those jobs too.  Some advise a switch to Universal Basic Income (IBI).  But UBI can’t be universal: manufacturing nations would have no UBI whilst non-manufacturing nations would have it, so as to create a market for transactions.  This needs to be mapped out immediately.

b. There isn’t enough power in the developed world for deployment of these new technologies for even 50% of population, much less al countries.  Energy is the impediment that will drive the geopolitics behind enterprise tech and AI dominance. 

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The power of ChatGPT in revolutionizing the way we produce and manage knowledge, especially in public policy - from initial ideas to final briefs and project implementation

Artificial Intelligence (AI) and machine learning are at the forefront in our world of advancing technology

Leveraging the power of ChatGPT to produce innovative public policy

By Marcello Basani

The world of technology is advancing rapidly, and Artificial Intelligence (AI) and machine learning are at the forefront.  The Inter-American Development Bank (IDB) strongly believes in the advantages of using cutting-edge technologies such as AI, machine learning, deep learning, and transformers to enhance efficiency and productivity, increase inclusivity, and reduce emissions in infrastructure.  In Latin America and the Caribbean, these technologies enable countries to analyze data more effectively and automate manual processes, resulting in better decision-making and services.

The infrastructure sector already applies technologies that reduce water and electricity losses, automate pavement and signage analysis, diagnose road safety features, and automate satellite imagery inspection to estimate solar power generation, detect water and sanitation assets, and create inventories of unpaved roads.

AI can revolutionize the water sector by providing innovative solutions to complex challenges.  It can be used to analyze data from multiple sources (sensors, satellites, and social media) to identify water quality issues and predict trends.  Thus, water managers can respond to contamination events quickly and accurately.  AI can optimize water resource management by predicting demand, identifying leakages, and optimizing treatment processes.  It can predict flood and drought events based on weather, soil moisture, and water level data analysis and help managers take preventive measures.  Finally, it can even identify wastage in homes and businesses and suggest ways for consumers to conserve water and reduce their bills.

One of the most exciting developments in this field is the rise of OpenAI’s language model: ChatGPT, a cutting-edge technology that can revolutionize the way we produce and manage knowledge, especially in public policy, from initial ideas to final briefs and project implementation.  This language model relies on a massive dataset of millions of web pages to generate text that is almost indistinguishable from that written by a human.

With ChatGPT, knowledge producers and organizations looking to create high-quality content can produce policy briefs, reports, and other written materials in a fraction of the time it would take to do so manually.  For example, in the case of renewable energy, ChatGPT can quickly generate a list of potential initiatives, as well as outline the pros and cons of each one.  Knowledge organizations can quickly and efficiently explore complex issues, provide in-depth analysis, and evaluate different scenarios and ideas from other fields to provide valuable insights and guide decision-makers in the development of more effective policies. 

Policy experts could also use ChatGPT to: 

• Generate summaries of large amounts of data, making it easier to digest and understand the information. 
• Create data visualizations and interactive reports, adding language descriptions and explanations of the data, trends, and patterns, making it easier for stakeholders to understand the information presented. 
• Simulate scenarios and assess the impact of different policy options, leading to the creation of better-informed and more effective public policies. 
• Produce insightful reports with in-depth analysis of the impact of policy initiatives on the defined field. 
• Quickly analyze large datasets and produce concise and actionable insights that can guide decision-makers. 
• Understand the needs and perspectives of stakeholders, and provide recommendations and insights based on this information. 
• Streamline the policy development process.

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