When it comes to work, workers, and jobs, much of the angst of the modern era boils down to the fear that we're witnessing the automation endgame, and that there will be nowhere for humans to retreat as machines take over the last few tasks. The most recent wave of commentary on this front stems from the use of artificial intelligence (AI) to capture and automate tacit knowledge and tasks, which were previously thought to be too subtle and complex to be automated. Is there no area of human experience that can't be quantified and mechanized? And if not, what is left for humans to do except the menial tasks involved in taking care of the machines? At the core of this concern is our desire for good jobs--jobs that, without undue intensity or stress, make the most of workers' natural attributes and abilities; where the work provides the worker with motivation, novelty, diversity, autonomy, and work/life balance; and where workers are duly compensated and consider the employment contract fair. Crucially, good jobs support workers in learning by doing--and, in so doing, deliver benefits on three levels: to the worker, who gains in personal development and job satisfaction; to the organization, which innovates as staff find new problems to solve and opportunities to pursue; and to the community as a whole, which reaps the economic benefits of hosting thriving organizations and workers. This is what makes good jobs productive and sustainable for the organization, as well as engaging and fulfilling for the worker. It is also what aligns good jobs with the larger community's values and norms, since a community can hardly argue with having happier citizens and a higher standard of living.1 Does the relentless advance of AI threaten to automate away all the learning, creativity, and meaning that make a job a good job?