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Artificial intelligence is changing higher education at a remarkable pace.

In a recent opinion piece for Times Higher Education, Bruce Hood argued that as AI becomes increasingly capable of producing polished written work, universities must rethink how they develop and assess one of the most important graduate attributes: the ability to communicate knowledge effectively to other human beings.

For decades, universities have focused primarily on written communication. Essays, reports, dissertations and examinations have been the traditional ways students demonstrate understanding. But the emergence of generative AI raises an uncomfortable question: if a machine can help produce convincing written work, how can employers, educators and society distinguish between possessing knowledge and simply presenting it?

The answer may lie in a skill that has often been overlooked within higher education: spoken communication.

Communication Beyond Writing

The ability to explain complex ideas clearly has always mattered. Whether presenting research, pitching a business proposal, explaining technical concepts to clients, or leading a team, professional success often depends on communicating knowledge effectively.

Employers recognise this. Across multiple surveys, verbal communication consistently ranks among the most sought-after graduate attributes. Yet many students complete their degrees having received relatively little formal training in public speaking, audience engagement or persuasive communication.

This is particularly surprising given that communication is not simply the transmission of information. Effective speakers must think on their feet, respond to questions, establish credibility, build trust and adapt to their audience in real time. These are deeply human skills that AI cannot easily replicate.

Knowledge Is Not Enough

Good communication begins with understanding.

One concern is that AI may allow students to engage less deeply with the material they are studying. If students rely on AI to generate essays and reports, they may miss the intellectual struggle that often produces genuine comprehension.

But even deep knowledge is not sufficient on its own.

Many graduates possess considerable expertise but struggle to explain it to non-specialists. Anyone who has attended an academic conference knows that expertise and communication ability do not always go hand in hand.

Communication is a skill that requires practice, feedback and repetition. Like any complex ability, it improves through deliberate effort.

Why Three Minute Thesis Matters

This is one reason the Three Minute Thesis (3MT®) competition has become such a global success.

Developed by the University of Queensland and now adopted by more than a thousand institutions worldwide, 3MT challenges doctoral researchers to explain years of work in just three minutes using language that a general audience can understand.

The challenge is deceptively difficult.

Researchers must identify the core message of their work, strip away unnecessary jargon, construct a compelling narrative and connect with an audience that may know nothing about their field.

In doing so, they develop precisely the communication skills that employers, policymakers, journalists and the public increasingly value.

The Problem of Visibility

Yet there is another challenge.

Every year, thousands of students participate in competitions, public engagement events, conference presentations and research showcases. These experiences develop valuable communication skills, but the evidence often disappears once the event concludes.

A presentation may be uploaded to YouTube, buried within a university playlist, and never seen again.

The achievement itself becomes difficult to discover, verify or showcase.

Why My-Thesis?

My-Thesis was created to address this problem.

The platform provides a searchable index of research presentations, enabling graduate researchers to make their talks more discoverable and giving audiences a way to find research by topic, institution, researcher or keyword.

But the platform is about more than research visibility.

At its core, My-Thesis recognises communication as an academic achievement in its own right.

A successful presentation demonstrates not only what a researcher knows but also their ability to explain, persuade and engage. These are increasingly important skills in a world where information is abundant but understanding remains scarce.

Looking Forward

Artificial intelligence is undoubtedly transforming education. Universities will continue to debate how best to assess knowledge and maintain academic integrity in an age of AI-assisted learning.

However, one consequence seems increasingly clear.

The graduates who thrive will not simply be those who possess knowledge. They will be those who can communicate it effectively, authentically and persuasively.

The ability to stand in front of an audience and explain an idea clearly may become one of the most valuable skills a graduate can possess.

And that is precisely why platforms such as My-Thesis matter more than ever.

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Kurzgesagt

Kurzgesagt (German for "in a nutshell" or "said shortly") is an organisation that generates animated educational videos to make scienitfic, philosophical, political and psychological content more understandable. It started out as a passion project by founder Philipp Dettmer in 2013 with the launch of their YouTube channel and is now one of the most popular. 

It is noteworthy that the paths of Kurzgesagt and My-thesis have become aligned as we both confront the threat of a AI dominated educational space. For example this recent video "AI Slop Is Destroying The Internet" explains how the internet is increasingly flooded with low-effort, AI-generated content designed purely to capture attention. Because attention is the currency of the online economy, bots now generate fake reviews, fake traffic, synthetic news sites, AI-written books, AI music, and entire YouTube channels producing multiple long-form videos per week with AI voices, scripts, and thumbnails. Around half of all internet traffic is already automated, much of it destructive.

As Kurzgesagt point out, the deeper concern is not just aesthetic decline — it is epistemic collapse. Generative AI is trained on vast quantities of human creative work, often without consent or compensation. But beyond issues of creative theft lies a more corrosive risk: AI makes it increasingly difficult to determine what is true.

To demonstrate this, Kurzgesagt describe their own rigorous research process: scripts are built from primary sources, peer-reviewed papers, and expert consultation. Fact-checking alone takes around 100 hours per video. When large language models appeared, they seemed like a powerful research assistant. Initially, outputs looked impressive — comprehensive outlines, structured summaries, plausible references.

But deeper scrutiny revealed a major flaw: while roughly 80% of the information was accurate and traceable, the remaining 20% contained fabricated or extrapolated “facts.” These weren’t obvious errors — they were plausible, detailed, and confidently presented inventions. Even domain experts flagged the same suspicious claims.

This illustrates a systemic problem: AI models optimize for coherence and user satisfaction, not truth. They “hallucinate” to fill gaps, much like a journalist embellishing a story to make it more compelling. Worse, some of the AI’s cited sources turned out to be AI-generated articles themselves. With over a thousand confirmed AI-run news sites publishing misinformation, AI can end up citing other AI outputs, forming a self-reinforcing loop.

The danger is recursive contamination. Once fabricated information is published — for example, in a viral YouTube video — it becomes a legitimate-looking source. The next AI model trained on that data treats it as evidence. Misinformation becomes self-validating. Over time, distinguishing original knowledge from synthetic fabrication may become nearly impossible.

Take peer-reviewed research. One study analysing language used in scientific papers,  shows measurable linguistic shifts towards more sensationalists terms following the rise of large language models, suggesting widespread unacknowledged AI assistance. Some researchers have even embedded hidden prompts in white text to manipulate AI reviewers into giving favourable evaluations. As AI use spreads carelessly, the reliability of the “library of human knowledge” deteriorates.

The central problem is that AI appears trustworthy. It is fluent, confident, and often correct enough to inspire confidence — yet it lies subtly and repeatedly. There is no understanding behind the words, only probabilistic pattern completion. Despite this, we increasingly allow AI systems to contribute to knowledge production.

Kurzgesagt argue that AI should remain a tool — like an alignment feature in design software — not a replacement for human creativity and judgment. They commit to maintaining human research, expert consultation, and creative integrity, even if it is slower and more expensive.

The final message is pragmatic: in an attention economy dominated by cheap, automated content, sustaining high-quality human work requires deliberate support. The future of trustworthy knowledge may depend on whether audiences value and fund it. At my-thesis, we are working with the universities, colleges and higher education institutions to ensure that human content and original research is protected from AI slop!