Is Artificial Intelligence changing what it means to be human?
(Illustration: Saurabh Singh)
MADHUMITA MURGIA IS an immunologist who became a journalist more than a decade ago, specialising in Artificial Intelligence (AI). Her career in the technology beat coincided with the miraculous rise of unknown or undervalued startups to the ubiquitous entities they have now become. So, it is fair to say she chronicled upfront a grand period when the world changed faster than ever before in the history of mankind. When she started writing for the Financial Times (FT) around 2012, she was goggle-eyed about the pace of growth in life-changing, user-friendly technologies, the majority of them in AI. In her own admission, she was an “inveterate techno-optimist”.
The Indian-origin author now sees more shades of grey in this growth story. After all, the power in this sector is concentrated in the hands of a few. This explains why she wrote Code Dependent: Living in the Shadow of AI to highlight people with nuanced relationships with advanced technologies, including generative AI. Unsurprisingly, Murgia, the first AI editor at the Financial Times who writes for Wired as well, didn’t want to tell the story of AI’s impact from the viewpoint of hot shots at Big Tech, but through select, interesting tales of professional AI users from across the world. Her aim: capture the global impact of AI through people working in various segments, from gig jobs to public health and surveillance to education. She writes in the introduction to the book, “Each of the lives you will encounter charts the unintended consequences of AI on an individual’s self-worth, on families, communities, and our wider cultures. Through their experiences, I hope to answer the question I started out with: how is Artificial Intelligence changing what it means to be human?”
The link between these people whose stories we read in the book—who are from different geographies and cultural contexts—and AI is that it is algorithms that often determine their lives and there are, without doubt, concomitant uses and biases. For instance, in India, as she went around looking for AI companies that made a difference and then pursued people who used them, she found a physician who treated her patients using Qure.ai, an AI company committed to making healthcare affordable and accessible. The gains AI brought in this case were largely momentous. In the US, Murgia zoomed in on UberEats, a unit of the company that first spawned the whole genre of gig economy on a large scale. She met with a technology- and ethics-obsessed crusader who took UberEats by its horns over its lack of accountability to its employees by creating an app called UberCheats, an algorithm-auditing tool that allowed couriers to track the accurate distance they had covered—information that UberEats hid from their workers ostensibly to underpay them.
A gifted storyteller, Murgia is on the shortlist of the inaugural Women’s Prize for Non-Fiction, which will be announced in June. She deserves praise for writing a book on AI that is global by nature because after all, the impact of AI, as she states, is different in different regions of the world. Unlike many others who go for tokenism, she has cast the net wide, narrating in style the experiences of her interactions with AI users from her home in London to Latin America to Asia to Africa and beyond. In the process, she addresses several key topics that are often swept under the carpet, including the agency of users or employees of an AI company, and how AI can dramatically alter certain sectors, especially healthcare and education.
Besides familiarising the reader with the works of technology scholars who are far from the mainstream, the author delves deep into the lived experiences of people whose stories rarely make it to newspaper headlines although they are highly relatable for any reader. The key takeaway here is that we may not know it and are not interested in AI, but AI is interested in us.
In India, Murgia’s book features how Ashita Singh, a physician working in a small village in western India, found AI a boon in the face of scarce resources, a shortage of staff and a lack of awareness. The author is however worried about the automation bias that typically sets in when the use of the technology becomes widespread. She asks this question of Singh who replies that affordability—to the extent of treatment being free—is what interests her, and that she sees the risk of AI being the master only if the practitioner is not grounded in “good medicine”.
It is not that Madhumita Murgia is any less optimistic about the uses of technology than she used to be, but code dependent suggests that she is more cautious about the lack of empathy and nuance in leaving everything to AI
It is not that the author is any less optimistic about the uses of technology than she used to be, but her book suggests that she is more cautious about the lack of empathy and nuance in leaving everything to AI.
Armin Samii’s struggle to make UberEats accountable and pay adequate wages to its workers is worth noting in this context. Through his efforts, he was able to bring together a group of gig workers from across the world to find hacks and use algorithms to their advantage besides letting the public know about the opacity of various AI-based work platforms. The author narrates how a heightened level of awareness is “springing up resistance movements” from the UK and US to Kenya and elsewhere. Couriers and riders have come together in the recent past to share their bad experiences. The author discloses, “My interviews with a dozen or so gig workers across four countries are a drop in the ocean of work being done on algorithms and work rights.” Things are still not looking bright for the workforce and uncertainty looms as we ponder the future of work— amidst high chances of loss of jobs.
There are occasions when people who work towards making the world a safer place regret the use of their products and services for super-surveillance of their citizens by states that are vindictive towards protesters and dissidents. American entrepreneur and academic Karl Ricanek is one such early pioneer who had several decades ago helped the US Navy with AI technology. Murgia says in her book that “as the technology steadily improved, Karl began to develop experimental AI analytics models to spot physical signs of illnesses like cardiovascular disease, Alzheimer’s or Parkinson’s from a person’s face.” Ricanek tells Murgia that he had imagined inventing “a mirror that you could look at each morning that would tell you (or notify a trusted person) if you are developing symptoms of degenerative neurological disease”. Ricanek, an African American, founded a company called Lapetus Solutions to help insurance firms predict life expectancy, and his systems were used to crack crimes. In one case, police used his technology to ‘age’ a gangster and identify him based on how he looked as an adult. But then 9/11 changed everything, and the technology was used for other purposes, from stifling opposition to tracking civil-rights protesters. Ricanek argues that facial-recognition technologies have a race bias, resulting in the over-policing of vulnerable groups such as African-American males. False positives too are a major cause for concern for him, the author reveals in her interviews.
Coming back to the question of maintaining individual or collective agency in a world dominated by powerful corporations, the author comes up with what she describes as a checklist of guiding questions, “to empower and help reclaim some agency in the use and control of AI”. It comprises 10 questions. “They are what I have been asking myself every time I encounter an AI tool. And they’re for you, whoever you are, whether you’d like to use, protest or simply understand AI technologies better,” Murgia writes.
This book is a must-read and a manifesto for AI users because of two reasons: the author’s stories focus on what happens when AI goes wrong; and then because she argues that however exceptional an AI tool is, it has utility only when it preserves human dignity.
Ullekh NP 