This chapter covers
- Understanding basic human–computer interaction principles
- Applying human–computer interaction principles in annotation interfaces
- Combining human and machine intelligence to maximize the strengths of each
- Implementing interfaces with different levels of machine learning integration
- Adding machine learning to applications without disrupting existing work practices
In the past 10 chapters, we have covered everything about human-in-the-loop machine learning except the vital component of the human-machine interface. This chapter covers how to build interfaces that maximize the efficiency and accuracy of the annotations. This chapter also covers the trade-offs: there is no one set of interface conventions that can be applied to every task, so you must make an informed decision about what is the best user experience for your task and your annotators.