Dear Future You Can Keep The Change – Ronee Hulk

The apprenticeship model of the PhD, for instance, is already breaking under the loss of teaching assistant roles.50 What remains, increasingly, will be experiential and project-based learning, conducted in small, hybrid hubs or online ecosystems, while AI busily handles knowledge transfer. In this world, ‘college’ ceases to be a physical place for most students and becomes a service: on-demand, personalised, and globally accessible.

Whether this reinvention is liberation or decline remains uncertain, but the one certainty is that the university of 2035 will be unrecognisable to any graduate alive today. And what holds true for universities will, in time, hold true for every institution built to teach. Such reinvention signals a broader transition across global education systems, raising urgent questions about access, fairness, and control. The United Nations Educational, Scientific and Cultural Organization (UNESCO) has warned that the rapid rise of AI in education must not deepen inequality.51 In its guidance on digital education, it warns that without careful planning, AI risks entrenching the very divides it promises to heal.52 Well-funded schools will buy the best tutors and devices; whilst others fight for bandwidth.

Students attending so-called wealthy schools will see the benefits of personalised tutors far earlier than their underfunded counterparts. This is a moral problem as much as it is technical. A child in rural Yorkshire must have the same level of access as the child in tech-heavy hotspots like Seoul or San Francisco; any plan for reform must have equitability baked in from the start, or we risk replacing one broken system with another. And so, this brings us to the idea of a new education charter.

If we were to design education from the ground up today, what principles would guide it? Presumably the charter wouldn’t begin with rigid curriculums, and it certainly wouldn’t insist on the rows of desks facing an authority figure barking out information. Rather it would start with the child. Understanding strengths, finding where there are gaps in knowledge, identifying challenges with learning.

It would take into consideration identity and define their emotional support needs. It should be able to guarantee that every student attains a strong grounding in critical literacies but would also ensure there is space for discovery and finding new passions.

Foreword: Before It’s Too Late It began with curiosity; we taught machines to think. Now, the student has learned too well. AI will upend every system we’ve built: work, relationships, wealth, purpose. Each will be unsettled. The question is: what does it leave still standing? Introduction: Ghost in the Code What is AI? Intelligence no longer sits in one place but moves through everything we touch.

From machine learning and LLMs to AGI and ASI, let’s untangle the acronyms, define the layers of intelligence we’ve built, and see how each fits into the larger story of machines that think. 1. Of Minds and Machines From factory floors to living rooms, automation has become the heartbeat of a redundancy wave that will dismantle not just industries, but identities too. The machines aren’t just coming for our jobs, they’re coming for our relationship with work itself.

When everything we do can be done better by code, what’s left for us to do at all? 2. The Efficiency Trap We built systems to make life smoother, faster, smarter. Efficiency was meant to free us, but instead it traps us in endless refinement, where purpose becomes process and meaning dissolves into data. We were promised freedom, but we’ve been delivered a cage. Is there any way out? 3. Behind the Curtain Invisible code now conducts the orchestra of our lives, deciding what we see, hear, and believe.

It selects our news, our feeds, even our outrage, shaping a world that feels chosen by us, but isn’t. Algorithms have become the unseen guiding hand of modern thought; the question is no longer what we think, but who’s doing the thinking. 4. The Cost of Perfect Health Medicine promises lives that may stretch across centuries. Robots will run wards, algorithms will diagnose before symptoms appear, as precision health replaces human touch.

We will save and extend more lives than ever before, but in doing so, will human compassion become the rarest treatment of all. 5. Chalkboards & Chatbots Education stands on the brink of its greatest transformation. Personalised AI learning promises to optimise every lesson, every child and every outcome. It is the triumphant end of one-size-fits-all schooling and the dawn of lifelong, data-driven learning.

But as machines take the lead in teaching us, is there an unseen cost? 6.

This is a short excerpt from the opening of “” by Unknown, quoted for review and introduction purposes. All rights belong to the copyright holders.

Book Information

• Unique ID: 9dd83cbdd8f1490f
• File Extension: .pdf
• File Size: 3,938,646 bytes (3.756 MB)
• Title: –
• Author: Unknown
• Pages: 137
• Language: English (en)

Reading & Word Statistics

• Estimated Reading Time: 232.72 minutes
• Total Words: 46,545
• Total Characters: 296,395
• Average Words per Page: 339.74
• Average Characters per Page: 2163.47

Most Frequent Words

one (140), now (124), https (118), new (114), systems (108), even (106), human (95), like (90), still (85), world (82), already (82), time (82), every (80), www (79), without (78), yet (77), com (75), first (75), rather (73), it’s (67), system (65), longer (64), learning (59), itself (59), become (58), real (57), something (56), question (55), whether (55), tools (53), value (52), machines (51), built (51), machine (51), work (50), technology (50), far (50), control (49), also (49), people (49), between (47), data (46), power (46), education (45), point (45), need (45), see (44), make (44), life (43), intelligence (42), progress (42), much (42), models (42), way (41), feel (41), beyond (41), across (40), becomes (39), long (39), many (38), future (37), perhaps (37), likely (37), begins (36), money (35), find (35), within (35), moment (35), change (34), shift (34), risk (33), able (33), around (32), less (32), automation (31), care (31), idea (31), often (31), isn’t (30), algorithms (30), cost (30), next (30), global (30), line (30), today (30), model (30), another (30), little (29), act (29), cannot (29), think (28), code (28), feels (28), digital (28), create (28), creative (28), place (27), begin (27), quickly (27), know (27).

PDF Download