\cleardoublepage \part{What It Does to People} \setbookpart{What It Does to People}

Part III: What It Does to People

Part II described the systems. This part asks what they do to the people they manage, and whether they deliver what they promise to the organisations that deploy them. It is the part of the book where the arguments are sharpest and the evidence most contested. Researchers, unions and workers report loss of autonomy, unexplained decisions, constant monitoring and harmful pace. Employers, vendors and some economists report more consistent decisions, less favouritism, safer allocation of work and gains in productivity. Both sides cite studies, and both sides are sometimes right.

The chapters in this part are therefore written as constructive debates, in the form AI Threat used for its threat chapters. Each chapter states the case for concern and the case for calm at their strongest, in the words and with the evidence of those who hold them; identifies where the positions meet; sets out what workers, managers, employers, workers' representatives and public authorities can do; and ends with a verdict labelled observable, expected or speculation. Effects on people are described by what the studies measured, in whom, over what period and by what method, and what a source reports is kept apart from what it is taken to mean.

Chapters in this part:

  • Chapter 11, Autonomy, Dignity and Control: Being Managed by a Machine, examines what research shows about discretion, meaning and respect at work when direction comes from a system, and whether the loss is inherent or a matter of design.
  • Chapter 12, Fairness, Bias and the Appeal That Never Comes, examines discrimination in scoring and allocation, the comparison with biased human managers, and the absence of a person to whom a worker can appeal.
  • Chapter 13, Surveillance at Work and the Chilling Effect, examines what monitoring measures and infers, its effect on voice and collective organisation, and the prohibition of emotion recognition in the workplace.
  • Chapter 14, Health, Pace and Burnout: Occupational Safety Under Algorithmic Direction, examines the evidence on injury, stress and burnout under algorithmic pace, and the employer's duty of care under the Framework Directive.
  • Chapter 15, Does It Work? Productivity, Quality and the Evidence for Algorithmic Management, examines the evidence that the systems deliver, over quarters and over years, and what the answer means for the thesis.

Management functions in this part. Chapter 11 concerns chiefly M1 Direction and M5 Care; Chapter 12 M2 Evaluation and M3 Consequence; Chapter 13 M2 Evaluation and M5 Care; Chapter 14 M1 Direction and M5 Care; Chapter 15 all five, and especially M4 Development, whose long-term effects are hardest to measure and easiest to lose. Every chapter names the functions it concerns in its opening and its Summary.

The thread from Part II. Part II showed that delegation to the AI boss is widespread and often implicit. Part III weighs the consequences. It also tests the thesis of Chapter 1 against the evidence that could refute it: if fully automated consequence decisions prove fairer than human decisions with records and appeal, or algorithmic direction without human leadership sustains performance and wellbeing over years, the chapters say so. The verdicts of Part III set the requirements that Parts IV to VI answer.

What you will learn in this part:

  • What the evidence says, and does not say, about autonomy, fairness, surveillance, health and productivity under algorithmic management
  • How to read a study of management and work: what was measured, in whom, over what period
  • Where those who fear the AI boss and those who welcome it agree
  • What each party at work can do, starting now

Part IV turns the question around: what happens when people become the managers and the team is software.