A City on Mars: Can We Settle Space, Should We Settle Space, and Have We Really Thought This Through?
Zach Weinersmith, Kelly Weinersmith
Earth is not well. The promise of starting life anew somewhere far, far away—no climate change, no war, no Twitter—beckons, and settling the stars finally seems within our grasp. Or is it? Critically acclaimed, bestselling authors Kelly and Zach Weinersmith set out to write the essential guide to a glorious future of space settlements, but after years of research, they aren’t so sure it’s a good idea. Space technologies and space business are progressing fast, but we lack the knowledge needed to have space kids, build space farms, and create space nations in a way that doesn’t spark conflict back home. In a world hurtling toward human expansion into space, A City on Mars investigates whether the dream of new worlds won’t create nightmares, both for settlers and the people they leave behind.
Award History
1 wins · 2 total
| Award | Year | Result | Category / Notes |
|---|---|---|---|
| Royal Society Science Book PrizeMajor | 2024 | Winner | Secondary source |
| Los Angeles Times Book Prize for Science and TechnologyMajor | 2023 | Finalist | Secondary source |
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies
This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.
01 Central figures
None extracted with sufficient confidence.
02 Central places
None extracted with sufficient confidence.
03 Suggested argument
No argument inferred with sufficient confidence.
This suggestion did not meet the normal display threshold and is more likely to be wrong.
Space settlement may be progressing, but humans lack the knowledge to support long-term life and governance in space without creating conflict and harm at home.
Model confidence 58%
04 Reading orientation
35 / 100 academicSerious trade
An estimate of intended readership and scholarly apparatus—not quality or importance.
Confidence percentages are the model's own estimates. Profile confidence: 74%.