This is a brief conclusion arguing that the direction forward is clear, even if the path is not. The time for assuming away problems is past. We should begin with a paradigm that reflects all the ways that polling can go wrong and then identify, model, and measure all the sources of bias, not just the ones that are easy to fix. Much work remains to be done, though, as these new models and data sources will require much evaluation and development theoretically, empirically, and practically. The payoff will be that survey researchers will be able to remain true to their aspirations of using information about a small number of people to understand the realities about many people, even as it gets harder and hear from anyone, let alone the random samples that our previous theory relied on.

This chapter presents the intuition behind why nonignorable nonresponse can be a problem and how it can arise in many contexts. With a foundation that explicitly centers this possibility, we can better reason through when the problem may be larger, how to diagnose it, and how to fix or at least ameliorate it. Section 5.1 describes qualitatively when nonignorable nonresponse may be likely. Section 5.2 works through the intuition about how and why nonignorable nonresponse undermines polling accuracy. Section 5.3 presents a framework for modeling nonignorable nonresponse and culminates by describing Meng’s (2018) model of sampling error. Section 5.4 raises the possibility that nonignorability varies across groups, over time, and even across questions.

Polling has become very difficult. People do not respond, and pollsters use methods that are far removed from the random sampling tools that built the field. This chapter introduces the book by outlining the main challenges facing polling today, how conventional tools fail to fully meet these challenges and how a new paradigm and new methods can more directly take on the full spectrum of nonresponse bias given contemporary polling practices.