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Wages have been spreading out across workers over time – or in other words, the 90th/50th wage ratio has risen over time. A key question is, has the productivity distribution also spread out across worker skill levels over time? Using our calculations of productivity by skill level for the United States, we show that the distributions of both wages and productivity have spread out over time, as the right tail lengthens for both. We add Organization for Economic Co-Operation and Development (OECD) countries, showing that the wage–productivity correlation exists, such that gains in aggregate productivity, or GDP per person, have resulted in higher wages for workers at the top and bottom of the wage distribution. However, across countries, those workers in the upper-income ranks have seen their wages rise the most over time. The most likely international factor explaining these wage increases is the skill-biased technological change of the digital revolution. The new artificial intelligence (AI) revolution that has just begun seems to be having similar skill-biased effects on wages. But this current AI, called “supervised learning,” is relatively similar to past technological change. The AI of the distant future will be “unsupervised learning,” and it could eventually have an effect on the jobs of the most highly skilled.

This paper uses a laboratory experiment to examine the effect of accountability pressure as a monitoring control tool to mitigate subordinates' propensity to create budgetary slack. The results suggest that budgetary slack is (lowest) highest when accountability pressure is (present) absent under a private information situation. The results further reveal that accountability pressure is positively associated with subordinates' perceived levels of honesty, which in turn is negatively associated with budgetary slack creation. The findings of this paper have important theoretical and practical implications for budgetary control systems design.

To facilitate innovative software development, more and more software development teams (SDTs) turn to agile methods. Such agile methods develop both extensive and efficient software responses to a client’s requirement change. However, the antecedents of successful agile software development are poorly understood. The authors goal is to propose a model of how power asymmetry and paradoxical leadership interact and affect agility in SDTs, which in turn affect their capacity to innovate. By leveraging insights from research on individuals’ cognition, the authors argue that developers with relatively higher power evaluate their contributions to their teams more ambivalently, which increases their delay or postponement of their contributions to their teams’ tasks. As a result, power asymmetry is negatively related to software teams’ response extensiveness and efficiency. Second, and drawing on leadership studies on behavioral complexity, the authors consider the moderating role of paradoxical leadership that a team receives as an important moderating factor to this effect. The authors argue that, when team leaders exhibit paradoxical leadership behaviors, high-power individuals’ ambivalence is less likely to emerge; hence, transforming power asymmetry to an asset for the enhancement of agility in the SDT.

This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human–Computer Interaction. This matrix of applications from each perspective offers a framework to guide designers in creating ITTSs.