9:15
The Last Normal Year
vlogbrothers
Overview
This video challenges the idea of a specific 'last normal year,' arguing instead that the concept of normalcy is subjective and that 2016 marked a significant shift in our media environment. The speaker posits that the rise of algorithmic feeds, online advertising surpassing TV ads, and the increasing influence of AI in content recommendation fundamentally altered how we consume information and perceive the world. This shift, driven by the competition for attention, has led to a media landscape that often prioritizes engagement through emotional responses like fear and outrage, potentially eroding trust and leading to a less stable society.
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Chapters
- The notion of a 'last normal year,' such as 2026, is a compelling hook but likely inaccurate.
- Personal perception of 'normal' is often tied to individual life stages, like teenage years.
- There have likely never been truly 'normal' years, as every era presents unique challenges and changes.
Understanding that 'normal' is subjective helps us critically evaluate claims about societal decline and recognize our own biases in perceiving the past.
The speaker's own feeling that 1996 was the most normal year, while acknowledging this is tied to their personal experience of being 16.
- 2016 saw major shifts: online advertising exceeded TV ads, mobile internet surpassed desktop, and social media platforms adopted algorithmic feeds.
- YouTube's recommendation system began using deep neural networks, influencing content visibility.
- The demographic of older adults joining the internet and Facebook increased significantly in 2016.
- Misinformation and hyper-partisan content began outperforming mainstream news on platforms like Facebook towards the end of 2016.
These technological and platform changes in 2016 laid the groundwork for the current attention economy and the way information, and misinformation, spreads.
The observation that in the last three months of the 2016 US election, top-performing fake election stories on Facebook were viewed, shared, and commented on more than top stories from major news outlets.
- Institutions lost attention and trust as people increasingly engaged with algorithmic feeds.
- Upstarts and creators collaborated with algorithms to capture and hold attention, often by generating fear or outrage.
- The competition for attention incentivizes content that evokes strong emotional responses, making it more likely to spread.
- This dynamic can lead to a feedback loop where increased exposure to negative content erodes trust in people and institutions.
Recognizing how algorithms prioritize engagement helps explain the prevalence of sensationalized or polarizing content and its impact on societal trust.
Content that makes you feel moral outrage or fear is more likely to travel easily through online systems with less friction, reaching more eyeballs.
- Unlike the AI revolution, we are entering the current AI era with more awareness, though perhaps not agency.
- The initial perception of algorithmic recommendations was that they would simply show us what we like, but they often show us what keeps us watching, regardless of emotional impact.
- AI, not just Large Language Models, now controls what content we see across various platforms (YouTube, Threads, Twitter, Facebook, Instagram).
- The 'for you page' is not built brick-by-brick for the user; rather, the user is being shaped by the algorithm's choices.
Understanding that AI actively shapes our information consumption is crucial for regaining agency and critically evaluating the content presented to us.
The 'for you page' illusion: users may feel they curated their feed, but in reality, the recommendation system is actively constructing the user's preferences and worldview.
- We have entered a media revolution where machine learning algorithms significantly influence our perceptions and decisions.
- Our world is now a co-construction between human choices and algorithmic direction.
- There is a significant learning curve for how to navigate and live effectively within this algorithmically influenced environment.
- Giving away a large percentage of our attention to algorithms has led to a demonstrably different and potentially worse world.
Acknowledging that our world is co-created by algorithms highlights the need for conscious engagement and critical thinking to mitigate negative consequences.
The speaker's assertion that we gave away a huge percentage of our attention to machine learning algorithms 10 years ago, and we are now living in a significantly different world because of it.
Key takeaways
- The concept of a 'normal year' is subjective and often tied to personal experience, making predictions about future 'last normal years' unreliable.
- 2016 was a pivotal year where the digital landscape shifted dramatically with the rise of algorithmic feeds and the dominance of online advertising.
- Algorithmic content recommendation systems are designed to maximize engagement, often by prioritizing emotionally charged content like fear and outrage.
- The pervasive influence of AI in curating our online experiences means our perceptions and even our identities are increasingly shaped by these systems.
- A decline in trust within society is linked to the erosion of shared reality and the amplification of divisive content facilitated by algorithmic platforms.
- We are living in a media revolution, and developing critical media literacy is essential for navigating a world co-constructed by human choices and AI.
- The competition for our attention is a primary driver of the modern media environment, with significant consequences for individual well-being and societal cohesion.
Key terms
Normal yearAlgorithmic feedsOnline advertisingMobile internetDeep neural networksMisinformationAttention economyMoral outrageArtificial intelligence (AI)Recommendation systemsFor you pageMedia revolution
Test your understanding
- How does the speaker define 'normal' and why do they argue against the idea of a specific 'last normal year'?
- What were the key technological and platform shifts that occurred around 2016, and how did they impact the media landscape?
- Explain the relationship between the attention economy, algorithmic feeds, and the type of content that tends to spread online.
- How does the speaker suggest AI influences our perception of reality and our online experiences?
- What are the potential consequences for society when trust erodes, and how might algorithmic content curation contribute to this erosion?