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Who Speaks for Earth?
- Carl Sagan

New here?

Read the short summary below and then check out the inspirational material

Short introduction

Goals

1. To create a platform which maximizes the quantifiability of decisions and their outcomes by belief aggregation
2. To use that data to make better decisions
3. To have accountability in decisions and performance measurement in predictions
4. To be able to make "recommender" systems (which weight the beliefs on their performance)

Example usecases for basic goals

• Autonomous agents that act upon the data (stock market bots, chess bots, controlling DACs)
• Accountability for politicians and other people in power
• Credence calibration and verification
• Belief reports weighted with probabilities of being true (Using ML)

Extended goals

• Conditional predictions ("X will happen before T if Y has happened", where X is a future state and Y is another prediction)
  • Gives levels of depth in prediction which gives the ability for make more complex and precise (but also possibly more improbable) statements.