This chapter examines the fiduciary duties of for-profit managers in modern liberal society. To arrive at the right “mix” of these duties, it compares the fiduciary duties implied by a standard descriptive model of our society with two competing normative models: Lockean libertarianism on the “right” and neo-classical republicanism on the “left.” This comparison shows that all three versions of liberalism, even the one with a Lockean night-watchman state, require far more extensive duties than we now expect, including a professionalization of management itself. And it shows that the version of liberalism with the most expansive state, neo-classical republicanism, requires the most appealing set of for-profit fiduciary duties. More basically, it concludes that what makes this latter set most appealing is that we ourselves are evaluating it from the perspective it recommends for for-profit managers: What is best, by our own best lights, for society as a whole.

Why you care: Running A/A tests is a critical part of establishing trust in an experimentation platform. The idea is so useful because the tests fail many times in practice, which leads to re-evaluating assumptions and identifying bugs.

As discussed in Chapter 1, running trustworthy controlled experiments is the scientific gold standard in evaluating many (but not all) ideas and making data-informed decisions. What may be less clear is that making controlled experiments easy to run also accelerates innovation by decreasing the cost of trying new ideas, as the quotation from Moran shows above, and learning from them in a virtuous feedback loop. In this chapter, we focus on what it takes to build a robust and trustworthy experiment platform. We start by introducing experimentation maturity models that show the various phases an organization generally goes through when starting to do experiments, and then we dive into the technical details of building an experimentation platform.

This chapter instills an appreciation for the powerful effects (both positive and negative) of performance pay on employee behavior. It opens with a performance-pay success story, namely a field experiment by Shearer (2004) in which the piece-rate compensation of Canadian tree planters was changed. It then develops some examples of the darker side of performance pay, including the Wells Fargo employees who opened false accounts to meet a quota. Section 9.2 provides visual representations of performance pay in which the pay graph has a positive slope (i.e., it increases when the worker’s performance measure increases), sometimes linearly as with piece-rate pay and sometimes nonlinearly as with bonuses. The chapter emphasizes the incentive and sorting effects associated with performance pay as well as its prevalence. Workers’ attitudes towards risk (of earnings fluctuations) and how risk affects performance pay is covered, along with performance measurement, various drawbacks of performance pay, and how to design performance-pay contracts. Readers will finish the chapter with an understanding of the advantages and disadvantages of performance pay and when it can be effectively used.

Why you care: Understanding the ethics of experiments is critical for everyone, from leadership to engineers to product managers to data scientists; all should be informed and mindful of the ethical considerations. Controlled experiments, whether in technology, anthropology, psychology, sociology, or medicine, are conducted on actual people. Here are questions and concerns to consider when determining when to seek expert counsel regarding the ethics of your experiments.