Record funding, historic firsts redefine DepEd under PBBM and Sec. Angara

Wazzup Pilipinas!? 




MAKATI CITY, 30 January 2026 - Long-identified reforms in basic education are now moving into full implementation as the Department of Education (DepEd) rolls out structural changes backed by its largest budget in history, under the administration of President Ferdinand R. Marcos Jr. and the leadership of Education Secretary Sonny Angara.



With the start of fiscal year 2026, DepEd is implementing reforms that had long been recommended but repeatedly delayed, enabled by a P1.3-trillion national allocation for the education sector—equivalent to 4.36% of gross domestic product and the first time the Philippines has exceeded global benchmarks for education spending. The 2026 allocation also represents the biggest year-on-year increase for education, with DepEd’s budget rising by about 30%.

“We will continue building on the progress that we have made and strengthening our efforts so that all Filipino learners receive the quality education that they deserve and that they rightly expect,” President Marcos said as he received the EDCOM II Final Report on Thursday.

Under Angara, several long-pending reforms moved into implementation for the first time, including the expansion of the School-Based Feeding Program (SBFP), which increased from P3.3 billion in 2022 to P25.7 billion in 2026. The increase enables the first universal feeding coverage for all Kindergarten and Grade 1 learners nationwide, institutionalizing nutrition as a core education input.


Learning recovery has likewise shifted from emergency response to system-level intervention through the Academic Recovery and Accessible Learning (ARAL) Program, implemented nationwide in School Year 2025–2026 with a focus on reading. Within three months, ARAL posted measurable gains in reading readiness across Grades 3 to 10.


To sustain these gains, P8.93 billion has been allocated for the ARAL Program in School Year 2026–2027, supporting the training and compensation of more than 440,000 DepEd and non-DepEd tutors and reaching an estimated 6.7 million learners in reading and mathematics.


Teacher career reform has also moved at scale through the Expanded Career Progression (ECP) System, a long-awaited policy aimed at clearing promotion backlogs and recognizing classroom excellence. Under the current rollout, more than 16,000 teachers have already been promoted, with an additional 41,000 applications under processing. DepEd is targeting the promotion of around 100,000 teachers this year, marking a historic milestone in teacher career advancement.


The 2026 budget allocation also reflects the Marcos administration’s commitment to address the country’s classroom gap. Angara pushed for flexibility for classroom construction to be undertaken by local government units and civil society organizations, reflecting an all-hands-on-deck approach to strengthening basic education infrastructure in support of human capital development. Meanwhile, funding for the Last Mile Schools Program doubled to P3 billion in 2026 from P1.5 billion in 2022, prioritizing geographically isolated and disadvantaged areas.


In addition, DepEd, for the first time, has adopted a 16-year-old executive order on the procurement of bamboo-made school furniture, supporting faster classroom equipping, cost efficiency, and local manufacturing.


Alongside education reforms, the administration has strengthened school-based access to health services through expanded YAKAP caravans of DepEd and PhilHealth, bringing primary care services closer to learners and school personnel, particularly in underserved communities.


“Ang mahalaga ngayon ay tuloy-tuloy ang pagpapatupad. Hindi na ito plano lamang—nasa silid-aralan na ang reporma, ramdam ng guro, at may malinaw na epekto sa pagkatuto ng bata,” Angara said.


The reform agenda builds on priorities set early in President Marcos Jr.’s term and aligns with the EDCOM 2 Final Report, which highlighted the depth of the learning crisis and the need for sustained, long-term action beyond political cycles. Recommendations on learning recovery, nutrition, teacher support, and infrastructure are now being translated into funded programs and operational reforms.

The Automation–Augmentation Paradox in the Age of AI

Wazzup Pilipinas!? 

From Augmentation to Automation—or Amplification?

We are living through a moment that will be studied the way we now study the Industrial Revolution—not just for what it changed, but for what it revealed about who we are.

Artificial intelligence is no longer a distant promise or a speculative threat. It is already woven into our work, our creativity, our decisions, and increasingly, our sense of self. And yet the conversation around AI remains trapped in a narrow binary: augmentation versus automation.

Either machines help us do our jobs better—or they take our jobs away.

But this framing misses something crucial.

There is a third path emerging, quieter but far more consequential: amplification. Not AI that merely assists us. Not AI that replaces us. But AI that magnifies what makes each of us irreducibly human.

That distinction is not semantic. It is existential.

The Automation–Augmentation Paradox

Recent large-scale research analyzing millions of job postings exposes a startling contradiction at the heart of AI’s impact on work. The roles most empowered by AI are also the ones most threatened by it. In fact, there is a 0.87 correlation between jobs experiencing the strongest automation effects and those experiencing the strongest augmentation effects.

The same roles. The same tasks. The same skills.

Skills most exposed to automation saw demand drop by 16%, while skills most exposed to augmentation saw demand increase by 7%. Tasks are vanishing and intensifying simultaneously, inside the very same jobs.

This is not a transition—it’s a compression.

AI is not slowly replacing work; it is restructuring work from the inside out, hollowing some parts while supercharging others. And because augmentation feels helpful, productive, even empowering, it can quietly escort us into automation without resistance.

Nowhere is this clearer than in creative work.

Studies show that generative AI boosts individual creativity. Stories written with AI assistance score higher on creativity metrics. Output increases. Quality improves. Productivity jumps—by as much as 25%, with perceived value rising 50%.

And yet, something disturbing happens at scale.

Those same stories begin to look eerily alike.

What we gain in individual polish, we lose in collective diversity. A creative convergence emerges where everyone becomes slightly better—and tragically more similar.

Efficiency, it turns out, has a shadow.

When millions of people outsource ideation to the same models, trained on the same datasets, optimized for the same engagement metrics, guided by similar prompts, we are not amplifying human creativity. We are homogenizing it.

The danger is not that AI makes us worse.

The danger is that it makes us average.

The Algorithmic Self

The deepest impact of AI may not be economic at all. It may be psychological.

As AI systems increasingly summarize, interpret, and reflect our behavior back to us, a new identity is taking shape: the algorithmic self. A digitally mediated version of who we are, shaped by patterns, predictions, and feedback loops.

Consider Spotify Wrapped—an annual ritual where millions eagerly await what the algorithm will reveal about their personality, mood, and taste. The machine’s summary often feels more authoritative than our own memory.

This is not harmless fun. It is a cultural shift.

We are beginning to trust algorithmic interpretations of our desires, emotions, and identities more than our own lived experience. What starts as insight becomes abdication.

This is not augmentation.

This is surrender.

Amplification demands something far more demanding—and far more human. It requires using AI to deepen self-knowledge rather than replace it, to expand expression rather than narrow it, to scale what is distinctive rather than what is derivative.

To do that, we must anchor ourselves in four dimensions of identity that AI cannot own—only reflect or distort.

The Four Dimensions of Amplified Humanity

1. Aspirations (Purpose)

At the core of amplification is purpose.

Research from MIT highlights traits like hope, vision, and moral direction as uniquely human capabilities—fundamental to leadership and meaning, and fundamentally beyond AI’s reach. These qualities were long dismissed as “soft skills.” In an AI-saturated world, they are survival skills.

AI cannot pursue a cause against the data.

It cannot persist when probabilities say “quit.”

It cannot initiate a vision with no precedent.

Most importantly, AI cannot inspire other humans to commit to something bigger than themselves.

As task-based identity erodes under automation, grounding professional identity in intrinsic purpose rather than output becomes existential. When AI can do what you do, only your why remains defensible.

2. Emotions (People)

Human connection is not just social—it is neurological.

When we interact with other humans, the brain lights up far beyond social cognition networks. Emotion, memory, intuition, and bodily awareness all activate. There is something happening that cannot be simulated, no matter how convincing the interface.

This makes “artificial emotional intelligence” a dangerous illusion.

AI-powered journaling tools, mood trackers, and therapeutic chatbots can offer structure, prompts, and reflection. Used wisely, they can deepen awareness. Used carelessly, they shift the locus of interpretation away from the self.

Exploration becomes reliance.

Reliance becomes dependency.

Dependency becomes agency decay.

When users begin trusting algorithmic summaries of their inner lives more than their own felt experience, augmentation quietly turns into replacement—not of labor, but of self-understanding.

Amplification keeps interpretation human.

3. Thoughts (Pursuit)

Knowledge work is being transformed—but not evenly.

Certain cognitive capacities still resist automation: imagination, ethical judgment, humor, improvisation, and the ability to synthesize distant ideas into something genuinely new. These are not inefficiencies. They are sources of originality.

Ironically, over-reliance on AI can narrow thinking. Once an AI-generated idea is accepted, it becomes harder to think beyond it. The mind fixates. Alternatives collapse.

Yet human value lies precisely in what algorithms smooth away: contradictions, tangents, irrational leaps, unfinished thoughts that spark breakthroughs.

In an AI-driven world, cognitive depth becomes scarce—and therefore precious.

4. Behavior (Practice)

Ultimately, intention only matters if it becomes action.

How people relate to AI shapes how they behave—and who they become. Those who treat AI as an unquestioned authority lose agency. Those who treat it as a deliberately controlled tool retain it.

Your behavioral signature—how you approach problems, how you recover from failure, how you collaborate, how you choose restraint over speed—becomes more visible and more valuable against the backdrop of AI’s standardization.

As machines converge, humans must diverge.

From Better to Meaningful

AI can make us faster.

It can make us better.

It can make us more productive.

But productivity without purpose is hollow.

The real question is not whether AI will augment or automate us. It already does both. The real question is whether we will allow it to flatten us—or whether we will use it to amplify what cannot be automated: our purpose, our emotions, our imagination, and our agency.

In the end, the future of work is not about what AI can do.

It is about who we choose to become while using it.