Some examples of different kinds of resolution criteria for forecasting questions: Personal mechanisms “If we choose this HR provider, will I think it was a g

Some examples of different kinds of resolution criteria for forecasting questions: Personal mechanisms “If we choose this HR provider, will I think it was a good idea in two month’s time?” “Each day I’ll write down whether I want to leave or stay in my job. After 2 months, will I have chosen ‘leave’ on >30 days?” “Will volunteering abroad make me all-things-considered happier?” “Will I judge that AI was a major topic of debate in the US election?” Objective proxies “Will our user satisfaction rating exceed 8.0/10?” “Will Our World in Data report that >5% of global deaths are due to air pollution by 2030?” “Will I still be discussing my fear of flying with my therapist in 2024?” Experts Consider only actually asking an expert on ¼ of the questions you generate, chosen randomly, to keep your accuracy incentive and get feedback on your predictions, but minimise the cost of consulting experts or mentors. “Will my mentor agree that pivoting now was the right choice?” “Will the rest of the team prefer this redesign to the current layout?” “Will anyone on the animal advocacy forum share evidence that convinces me that abolitionist protests are net-beneficial for the movement?” “On December 1st, will Marco, Dawn, and Tina all agree that the biosecurity bill passed without amendments that removed its teeth?” Crowds “Will >80% of my Twitter followers agree that I should keep the beard?” “Will a Manifold market on this question trade at >90% YES in two weeks?” “Will social media posts about our product be more positive than negative in the first month after launch?” “If I survey 40 random Americans through Mechanical Turk, will our current favourite name be the most popular?”