# [[Personal Experience is the new Rare Earth Metals]] *May 24, 2025* ##### The abundance of generic data will make personal individual perspective as valuable as rare earth metals Recently I took a walk in the park when I spotted a guy in front of me with a big white backpack and an Apple Maps label on it. The backpack had a cooling fan and a 360 camera on a long pole sticking out from the top. As this cartographing man machine made its way through the weeds, the fan humming eagerly, I realized: this is what hunting for original data looks like today. It’s not some anonymous servers in Texas, but a bald guy in expensive sneakers with a weird camera rig right here on my daily route. Our technological ecosystem yearns for on-the-ground observations. Unmapped trails, unrecorded conversations, undocumented moments. They call it Small Data:[^1] Information that can’t be synthesized, only extracted. Information defined by scarcity, not abundance. Big Data was considered as precious as oil.[^2] How will Small Data lurking in the not-yet-commodified niches of our daily lives be valued in this current phase of AI-fueled digitalization? The small data that everybody hunts for will be our personal experience. We are as small countries being strip-mined for resources the world needs to keep its engines running. A natural blessing we trade away against crypto commercials and cat videos. Our personal experience is as valuable as rare earth metals, so we should start treating it as the precious resource it is: 1) **Cultivation requires care:** Having unmediated experiences is increasingly difficult with TikTok and others training us to be feed-addicted endorphin wrecks. Protecting the niches where we can grow our personal view on the world without excessive contamination by taste-defining algorithms is vital. The more a medium is exploring our experiences, the less will be left for us to discover. 2) **Extraction demands compensation:** Small nations in possession of rare earth metals will negotiate with corporations, to at least ensure the exploitation of their soil does not happen without some kind of compensation. What compensation do we receive when we share our original experiences online, essentially aiding the data collection of large corporations? 3) **Exploitation stays exploitation:** There is a limit for how much we can mine from our daily life before experience turns into performance. Everybody having written a diary knows the tension between actually writing for yourself and secretly assuming somebody eventually might read and appreciate your ramblings. When we are only living for sharing things, there is not much of value left to be shared. Greed is already here to get a hold on our personal observations, intuitions and memories. We should not let ourselves be fucked over. We might decide to share a part of our experience with corporations, but we should always do this in a mindful and deliberate way. Always question what we get back instead. And always consider if it makes sense to hold something back. Apple guy with his 360-degree cameras still walked in front of me. I slowed down a little bit, waiting for him to pass another corner through the bush before I turned onto an overgrown side path. Somehow, I did not want him to sneak into this favorite bit of my dog’s daily routine. Big or small, not everything needs to be data. [^1]: *„Our current approach to AI relies on statistical learning, which requires large amounts of data to identify patterns. However, this approach is less adequate when the available is insufficient in quantity or quality to enable machines to learn meaningful or accurate patterns.(…) On a practical level, **the ”small data” challenge remains a major obstacle due to possible high costs of data collection, curation and annotation.** Surveys indicate that 96% of enter- prises face data challenges, including issues with data quality and labeling, and 40% lack confidence in their ability to ensure data quality. Consequently, data scientists spend nearly twice as much time on data wrangling and cleaning as they do on model training, selection, and deployment.“* [The EPOCH of AI: Human-Machine Complementarities at Work (Loaiza, Rigobon) 2025](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5028371) [^2]: The widely used phrase "data is the new oil" is attributed to British mathematician and data science entrepreneur Clive Humby. While the phrase later has often referred to the general value of data, the original wording highlighted the importance of processing raw data to make it useable: *"**Data is the new oil.** It's valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc., to create a valuable entity that drives profitable activity; so data must be broken down, analyzed for it to have value."* https://www.theguardian.com/technology/2013/aug/23/tech-giants-data