Review of Madhumita Murgia’s Code Dependent — Living in the Shadow of AI: Being human in an AI world

Madhumita Murgia’s debut book, shortlisted for the inaugural Women’s Prize in Non-Fiction, maps the growth of Artificial Intelligence through the lens of human actors

If you have ever asked Alexa to play a song, Siri to make a call, or Google to map a route, then you have engaged with an artificial intelligence (AI) system. These are just a small subset of everyday activities people do with their AI-powered products.

Madhumita Murgia’s Code Dependent lifts the veil hanging over humans that are building the base for AI’s super structure to stand on. Most of them are unaware that the very system they are building would soon gobble up their very livelihood.

Her book offers a cross-section view of tech’s bedrock — labelled data, humans building it, and the influence of automated systems on people. She throws light on the real AI stack, which has humans right at the bottom of the pyramid, without whose inputs, the current crop of AI tech wouldn’t stand.

Over the past decade, tech devices and software have become more intuitive, creative and powerful. Underpinning their advance is a confluence of four major forces: Big Data, algorithmic recommendation systems, innovation in chip design, and cash-rich Big Tech firms.

This potent mix is redefining the way people interact with technology and is bringing humans much closer to machines than they were ever before in recorded history. Of these four powerful forces, Big Data is the most crucial ingredient in concocting a powerful AI system.

Lumps of data mean nothing unless someone slices and dices them down to manageable parts. And that act of cutting datasets down to specific parts can be done only after categorising and labelling content.

If a self-driving car adjusts its steering wheel after noticing a sign post, that means it was trained on a dataset that contained labelled information on roads and signposts. This labelling makes the car’s advanced driver-assistance system (ADAS) adept at manoeuvring diverse terrains. The process of labelling parts in a dataset is called data annotation.