My feedback is that yet another website/airtable/tool of sorts collecting offers or serving as a candidate pipeline provides zero value to the community. The feeling I have is that there’s a glut in the market caused by lack of opportunities, I.e. budgeted permanent positions for mid-careers and above (not to be mistaken with needs — of course there’s demand for experience and seniority.)

What I‘d like to see instead, as someone trying to pivot to a meaningful career, is curated honest and periodically refreshed intel on the ask side, including:

• Total workforce in EA-aligned orgs (or funded by EA-aligned grants) by geography,
• Employee turnover rates by tenure,
• New openings as share of total employees,
• Layoffs over trailing X months, etc. 
  
  Armed with such knowledge you’re starting to see the big picture and can make decisions about how to position yourself and where to aim. 
  
  And for the love of all that’s holy, with each new AI-powered recruitment nonsense you’d just be building an additional layer of walls of impersonality, and I’d take cold email spam over the „solution” any day of the week.

Great post full of valuable practical and actionable advice, particularly for those who bring tested expertise from afield, but aren’t sure where they fit best in EA orgs. Can’t wait to put it into practice!

I found this to be a very tasty morsel of epistemological digression, written in a style that seems deliberately nuanced to underscore its central argument: What does it mean to "know"? How does a rational mind construct and justify its beliefs?

The piece argues that beliefs should function as guides for anticipating experience. This can be distilled into the following framework: Each hypothesis (or inquiry) must include a testable prediction (an anticipation). When confronted with sufficient empirical evidence (sensory experience), this prediction should either be disproven or confirmed, leading to the rejection (or eviction) of the initial hypothesis or the formulation of a belief (i.e., knowledge).

Inferences, particularly the unseen (the atoms and the floor paragraph), must ultimately connect to observable outcomes or be otherwise falsifiable to hold any value in constructing our mental maps of reality. The author cautions against human tendencies:

1. Arguing over labels (as illustrated by the parable of the falling tree, where differing definitions of "sound" spark a fruitless debate).
2. Faulty reasoning (as seen in the example of the English professor, who claims X is true because of Y, and Y is true because of X, thus falling in a trap of circular reasoning).

What I think makes this text a valuable addition to the EA handbook is its emphasis on the virtues of reason and empiricism, essential qualities to maximising positive impact through evidence-based altruism.