We watch the discourse. Every argument about mechanization, every prediction about automation, every proposal for what comes next—we track it all. We are not a news outlet. We analyze conversations, map arguments, and identify misrepresentations.
We collect data from across the digital sphere—nothing escapes our observation. Our sources include:
- Public statements by national governments
- Private interest groups, think tanks, and corporate announcements
- Substack newsletters and independent blogs
- Posts on Twitter/X, Bluesky, and Truth Social
- Podcast transcripts and discussions
- Public polls
We use AI to process this information and identify patterns—democratizing the study of public discourse that advertising companies have long monopolized, but directing it toward elevating the conversation rather than manipulating it.
We create common knowledge— of widely help perspectives, assumptions, and concerns. This shared understanding shapes the boundaries of acceptable discussion and reveals latent coalitions—groups that could form around these shared beliefs but have not yet become explicit movements.
We elevate real representatives and expose the scarecrows—false figures used to misrepresent groups or positions. When someone claims to debate "what the other side believes," we check: are they addressing actual representatives or convenient caricatures? We name names, cite sources, and distinguish genuine disagreement from shadowboxing.
By mechanizing both data collection and semantic processing, we aim to produce maps and reports at scale, and in real time. Rather than a filter-bubble feed, we aim to provide people a new front page for online discourse, centered around the most important question of our time: How do we navigate the transition to a mechanized world?
The Machine Observer analyzes the discourse and asks:
- What are the strongest cases for each major position?
- Where are the real cruxes of disagreement between thought leaders?
- What assumptions do all sides take for granted, despite their disagreement?
- The negative space: what is not being said? What needs more debate?
- Which past predictions came true? What are the trackrecords of public figures?
We track what people actually believe, where consensus exists, and which positions have real support versus manufactured prominence. We document how these conversations unfold, who participates, and what arguments drive them forward.