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What if the smartest way to use AI isn’t to compete with it—but to design work where each strengthens the other? This book is a field manual for human ai collaboration: practical, disciplined, and built for people who make real decisions under pressure. It shows how to pair judgement with computation so choices become clearer, teams become calmer, and outcomes become fairer.
You will learn a usable architecture for human in the loop work: how to brief models, set thresholds, audit evidence, and decide when to defer—or to override. Along the way, you will practise probabilistic thinking for managers, build repeatable patterns for augmented creativity techniques, and install governance that protects reputation without slowing you to a crawl. This is AI as partner, not prophecy.
- For product leaders, analysts, clinicians, policy makers, and builders who need decision support with ai that survives scrutiny
- For designers and writers who want co-creation patterns that feel original, not derivative
- For teams seeking governance for ai systems they can explain—and defend
Inside you’ll find clear examples, checklists, and exercises for designing prompts and guardrails, plus candid discussions of risk, consent, and dignity. If you’ve wondered how to build hybrid teams with ai that are both inventive and responsible, this book gives you the operating model—and the language—to start tomorrow. It is a careful, human guide to co intelligence in practice: precise where it counts, humane where it matters, and immediately useful when the stakes are high.

Humans + Machines

SKU: 9789374126899
$27.99 Regular Price
$21.12Sale Price
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  • Sanjan Mehta writes for people who make consequential choices and prefer clear thinking to loud certainty. Raised between engineering workshops and a home where history and ethics were dinner-table sport, he treats tools as mirrors: what we build reflects what we value. His essays and field notes follow a simple question—how do we design work so judgement and computation refine one another rather than compete? In his pages, a dataset sits beside a poem, an interface beside a legal case, a checklist beside a hard question about dignity. He draws lightly on traditions from Aristotle to Amartya Sen, from Ashoka’s edicts to the origins of the checklist in surgery, to ask what good systems make of us. The voice is warm, exact, and sceptical of easy claims. Readers trust him not because he is certain, but because he is careful—and because he believes good practice is a moral act.

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