Discussion: The original web was about information. Web 2.0 was about making it social. The next huge transformation of the web, enabled almost entirely by the intimacy and ever-presence of mobile devices and AI-agents, may be toward personalization – the Personal Web. Everybody talks about “big data”, but its most powerful potential will be to focus the broadest capacity of the Internet down to serving individual needs, hopes and dreams. Many pundits predict that very soon humans won’t even look for direct connections to the Internet – that each of us will have squadrons of AI-agents surfing, harvesting, creating and acting there for us.
523 Inspiration: The massive personalization potentials of the Personal Web will be realized with mobile devices acting as mediators between the Internet, social networks, a personal cloud, communications systems, and the affordances of the everyday world. It will be the first universal engine for learner-centred education.
The Personal Web offers exciting possibilities by shifting education toward highly personalized learning ecosystems. With AI-agents capable of scaffolding study habits, tailoring resources, and even predicting challenges, students could gain unprecedented levels of support and independence. However, the same tools that promise empowerment also carry serious risks. Over-reliance on algorithms may narrow exposure to diverse perspectives, turning learning into an echo chamber. The constant collection of personal data raises troubling privacy concerns, especially for young learners. While the Personal Web could make education truly learner-centred, without strong ethical safeguards it may do more to control students than to empower them.
This frontier is powerful because it presents a major shift in how the Internet will serve people. Instead of searching and navigating on our own, AI agents could soon filter and organize the entire online world to meet our individual needs, goals, and interests. This level of personalization is exciting for society because it could make daily life more efficient by helping people manage work, health, and communication in specific, tailored ways. At the same time, it raises important questions about privacy, ownership of data, and how much control individuals should hand over to automated systems.
In education learners would have access to fully customized resources, adaptive pathways, and supports that adjust to their unique strengths and struggles. Teachers could use these tools to design learning that is more flexible and student-centered, with mobile devices serving as bridges between the online and physical classroom. This frontier aligns with the vision of learner-centered education by putting each student’s needs at the core of how knowledge is accessed and applied.
During my MET journey, one of the most intriguing ideas I have come across is the concept of digital colonialism and the way our data is constantly being used to construct consumer profiles that are then sold to advertisers. I see this phenomenon as part of a continuum of concepts explored in Naomi Klein’s 1999 book No Logo, where she examined the rise of branding in the 1990s. I believe the ideas Klein developed in that book (that corporations sell lifestyles instead of products) have reached their fullest expression in today’s tribalistic social media paradigm, driven by algorithms.
Our current web already feels so personal that I am curious and fearful about what it could look like in the future. This frontier intrigued me due to the significant changes in priority the web has made. The advertising and algorithms used to capture my interests are addictive and I worry about the ways that personalization can continue to be exploited. I especially worry about our young learners with developing brains, who are more susceptible to be manipulated by the web. Continuing to teach students critical thinking skills is crucial going forward.
Personalization is one of the frontiers that stands out to me. The introduction of AI and ChatGPT has made it much easier to create personalized chatbots that help students engage with learning materials. This personalization capability is especially powerful in large classes or MOOCs, where it is difficult for instructors to provide individualized feedback to students.
For example, Ng (2018) suggests that providing personalized, performance-related feedback can enhance students’ motivation by engaging brain regions like the striatum, which is involved in processing feedback and rewards. This engagement not only boosts motivation but also positively influences students’ attitudes, potentially leading to better long-term educational outcomes.
However, personalization can also raise concerns about surveillance. For example, when I conducted a small experiment with ChatGPT, I noticed that in order to generate highly personalized responses, it seemed to rely on analyzing my past interactions more extensively than I felt was necessary. For those who are curious about the experiment, you can take a look at the blog post here https://dreamsanatomy.com/spotting-biases-and-blind-spots-in-generative-ai/
Reference:
Ng, B. (2018). The Neuroscience of Growth Mindset and Intrinsic Motivation. Brain Sciences, 8(2), 20. https://doi.org/10.3390/brainsci8020020
Disclaimer:
Although the ideas are my own, I used ChatGPT-5 to improve sentence structure, grammar, and flow. I proofread the output after incorporating ChatGPT.