
Hello World: Being Human in the Age of Algorithms
4.5 4.5 out of 5 stars | 2,212 ratings
Price: 19.95
Last update: 01-31-2025
About this item
Shortlisted for the 2018 Royal Society Investment Science Book Prize
A look inside the algorithms that are shaping our lives and the dilemmas they bring with them.
If you were accused of a crime, who would you rather decide your sentence - a mathematically consistent algorithm incapable of empathy or a compassionate human judge prone to bias and error? What if you want to buy a driverless car and must choose between one programmed to save as many lives as possible and another that prioritizes the lives of its own passengers? And would you agree to share your family’s full medical history if you were told that it would help researchers find a cure for cancer?
These are just some of the dilemmas that we are beginning to face as we approach the age of the algorithm, when it feels as if the machines reign supreme. Already, these lines of code are telling us what to watch, where to go, whom to date, and even whom to send to jail. But as we rely on algorithms to automate big, important decisions - in crime, justice, healthcare, transportation, and money - they raise questions about what we want our world to look like. What matters most: Helping doctors with diagnosis or preserving privacy? Protecting victims of crime or preventing innocent people being falsely accused?
Hello World takes us on a tour through the good, the bad, and the downright ugly of the algorithms that surround us on a daily basis. Mathematician Hannah Fry reveals their inner workings, showing us how algorithms are written and implemented, and demonstrates the ways in which human bias can literally be written into the code. By weaving in relatable, real world stories with accessible explanations of the underlying mathematics that power algorithms, Hello World helps us to determine their power, expose their limitations, and examine whether they really are improvement on the human systems they replace.
Top reviews from the United States


If you’re less familiar with algorithms, data products, and machine intelligence, this will likely be an interesting read.
A few places I really appreciated were Fry's friendly writing, good examples, and obvious understanding.






The fact that we tend to blindly encode our old behavior into systems and assume them to be now be somehow superior because of their improved consistency or accuracy does not exclude the fact that we are encoding our prior biases and mistakes into an automated system. Many such examples of where this can go horribly astray are listed although there is a refreshing amount of content describe the positive benefits, both actual and projected, of using these systems.
I definitely recommend as a light read to those in-the-know with machine learning to reify the importance of recognizing and combatting bias but also to the layperson who wants a better understanding of what modern day advances in machine learning are doing, where they are still struggling, and how they still need improvement.