How To Talk To Robots and Why You Should

A Girls' Guide To a Future Dominated by AI

Tabitha Goldstaub

• Publisher: Fourth Estate
• Year: 2020
• ISBN:
  9780008328221

’…an essential and fascinating manual for every woman who wants to understand equality within an ever-changing, modern world.’ Scarlett Curtis

1

WHAT IS AI?

And why should it matter to you?

Have you used a Snapchat filter to see what you’d look like as a baby? Is your inbox delightfully clear of spam emails? Are your photos on Facebook automatically tagged with the correct friends? Is the autocorrect on your phone so good you think it’s psychic, or so absurd that you text it to your best friend anyway? Have you had a full-blown conversation in French using one of the speech-to-speech translation apps? Are you guided – or bitterly disappointed – by Netflix’s film and TV viewing recommendations? If you answered yes to any of these questions, you are already interacting with artificial intelligence.

The AI that many people use every day is getting more accurate all the time. Take Google Maps. Originally, this app just got you from A to B. Then it helped you get from A to B with the least amount of traffic. Now it asks how busy your tube or bus ride was, then translates this information to let you know if there’s usually only standing space at particular times. Then Google Places appeared, showing you inside buildings, restaurants and points of interest across the world. It can make recommendations for where you might like to visit. If you use a Google calendar to record your dentist appointment, it will automatically personalise your map to include where your dentist is. It’ll even suggest when to leave your meeting in order to get to the next one on time. Last night, Google Maps dropped a pin when I parked my car to remind me where it was after I returned from dinner. Initially I thought this was spooky but then I was grateful because I always seem to forget. By the time you’re reading this, who knows how much more advanced the simple map will have become. We’ll discuss later the risks of relying too much on this new technology; we’ll also talk about who has access to this technology and who does not (and why that matters). For now, if you do use a smartphone, just hold in your mind all the ways that your day-to-day is being affected by tech in the palm of your hand.

AI is automating everyday tasks at an unprecedented pace. As we acquire and learn how to use more new digital devices, we’re also constantly upgrading our dependency on AI. Few people are oblivious to how this technology has firmly slotted into our lives, but most of us don’t appreciate that the rules of this tech are constantly shifting and evolving. We’re now living in an era where machines are taught to learn and adapt without human intervention, and this has some serious ramifications that we’ll explore over the course of the next few chapters.

The many functions of AI will continue to impact every aspect of our daily routines, but as well as helping us to avoid traffic or introducing us to new music, AI systems will detect disease, reduce energy consumption, decide which of us receives an approved loan, power vehicles to be autonomous and self-driving and both inform and control our news and advertising feeds. AI has the potential to unlock a future where humans live longer, healthier, happier lives. It could change the nature of much work: taking over many repetitive, boring tasks and freeing humans up to spend time on creative, fulfilling projects. This could dramatically change common conceptions of how much of our lives we need to spend on work, allowing us all to spend more time with each other and on our relationships, or on whatever it is that makes life worth living for you.

But there is a much scarier alternative. The flipside to this technology is that it could make life a lot worse for a lot of us, and especially the most vulnerable: it could widen the poverty gap, further increase inequality, reduce diversity and re-entrench many of the structures that keep some people down, no matter what they do. Anyone who tells you otherwise is not telling you the whole story.

The reality of AI, in its current state, is that it adopts the truths of its creators: humans. AI-driven machines learn from data that humans feed into their systems, meaning that they can also learn the social norms that many of us are desperately trying to escape or eradicate. For example, what if they are programmed to accept the existing pay gaps, or the idea that a woman’s place should always be in the home? If misogyny and unconscious or conscious bias is codified into the next wave of technology, we are all exposed to a less fair, less equal future. It gives me the shivers just thinking about it. So, although AI has enormous potential to improve our lives, there is the risk that rather than empowering women it may continue to compound existing stereotypes. And, as we’re going to see below, the evidence that we have suggests that the risk is already becoming the reality. We have to protect our rights and fight against oppressive gender constructs becoming codified, because if they are, then whatever progress women have made over the past century could very easily be wiped out. We need to do so much more than become merely competent responders to AI.

The first step here is to accept that to thrive we must learn to live and work alongside machines. I don’t want women to be more at risk of losing their jobs to a machine because there wasn’t enough material out there to prepare them for using it. But don’t worry, as you’ll read time and again from some of the women interviewed here, this does not mean we have to become coders, statisticians, designers, or engineers. On the flipside, we certainly can do all these things and in fact, many of the pioneering early coders were women.

No one will be unaffected by AI. Are you at school deciding what work experience to do? Are you in university and making plans to enter the world of work? Are you in an office or in retail? Maybe you work in a hospital as a nurse or a porter or a doctor. Or are you a banker, an accountant, an advertising executive? Are you a part of the gig economy? AI technology, as you perhaps know all too well, is already permeating your workplace. The challenge now is to work out how to make sure it helps you rather than undermines you.

It’s widely publicised that only 13 per cent of engineers and data scientists working in the West are women, and so I hope some of you go on to change this shocking statistic. But what this book is really about is inspiring you to get interested in tech, feel comfortable working alongside it, leverage it, use it, be enabled by it, know how to be heard and have a stake in how technology is built and deployed. It’s a pragmatic guide for the uninitiated.

There are ways that you can be instrumental to the building of the AI systems. Just think about how many different steps there are when building a product. Companies are going to need people who love languages to give AI a voice; historians and philosophers to give AI context; designers and artists to give AI personality and an interface; and product managers to ensure the AI is fit for purpose. The number of non-technical roles will become crucial as we try to build machines that think and act like humans. AI should be democratised not professionalised. All this power should not lie in the hands of the few, nor should it stay only in the hands of men who currently make up the dominant percentage of the tech workforce.

OK, sounds good, but what exactly is AI?

In order to answer this question, I called on Karen Hao. Karen is a journalist, storyteller, engineer and for the past few years she’s been the woman who has explained complicated concepts to me via the MIT Technology Review magazine. She has made what hundreds of other people have tried to explain to me before just click into place. She’s always been good at finding novel ways of communicating: as well as an AI expert, she’s also passionate about the environment and as an undergraduate, launched a fashion show entirely made of rubbish! She’s a woman after my own heart in more than one way.

What are the fundamentals of AI that everyone should understand – and why does it often seem confusing?

Well, in the broadest sense, AI refers to a branch of knowledge that strives to recreate human intelligence within machines. In the ideal realisation of this goal, such machines would be able to learn, reason and act for themselves, mimicking the ways we as humans, or a pet dog, might do so. They would take in information from the rapidly evolving world, process it and then figure out how to respond based on prior experience – and they would supposedly be able to do so much faster and on a far greater scale than any individual human could.

Karen Hao

This is the dream of artificial intelligence: to make these super capable machines that can put their ‘minds’ together with ours to solve some of the world’s most complex problems: climate change, poverty, hunger – things we haven’t been able to wrap our heads around on our own. I like to think of this dream as Janet from NBC’s comedy series The Good Place. She’s a kick-ass, fully autonomous and highly intelligent agent that helps her human counterparts be better versions of themselves.

Part of the reason why AI gets confusing is because the term can often feel like it refers to two completely different things. We now know one of them – the vision of the field, which evokes something closer to what we see in science fiction. But as you’ve already intuited, today’s AI systems are nothing near the clever, autonomous agents that I just described. They’re simpler and less capable, able only to perform specific tasks such as adding dog ears onto your Snapchat photo, ranking your content on Facebook or recommending new songs on Spotify to match the genre you like.

In the field, these two versions of AI have been given different names. The dream is often called ‘artificial general intelligence’, or AGI, while the reality is sometimes referred to as ‘artificial narrow intelligence’. People usually call artificial narrow intelligence AI. But these definitions are often combined into one in popular culture, causing people to think that the AI we have today is far more advanced than it really is.

There is another element that complicates the whole thing further. Because AI researchers are constantly pushing the boundaries of the technology, the definition of present-day AI also changes over time. What might have been considered AI thirty years ago is no longer really considered AI today. And what we know as AI today has only been the working definition for less than a decade. Certainly, among experts there’s a considerable amount of debate about what constitutes AI and what it will be capable of in the future. In fact, one of the fiercest debates is about whether AGI is even possible!

When you add all that up, it goes without saying that the notion of AI is constantly being tweaked, debated, probed and refined. Don’t let that overwhelm you. Instead, take it as an invitation: what AI is and where it’s going is ultimately shaped by people. That means you can have a role in influencing the technology, which I hope you find as hugely exciting as I do.

So what do you think the most common misconceptions are about AI?

One of the biggest things that confused me when I first began covering the field is the difference between robots and AI. The two are clearly interrelated, yet they are not the same thing. As it stands now, AI specifically deals with software. Robotics, by contrast, deals with hardware. Think of it as your brain versus your body. Your body relies on instructions from the brain to move, but your brain also relies on your body to experience and sense its surroundings so it can learn about the world.

Of course, as mentioned in the introduction, AI doesn’t always come physically embodied in a robot. More often than not, it exists as a hidden algorithm on your favourite websites or apps. Similarly, robots aren’t always powered by AI. Instead, their actions could be dictated by software that executes a series of hard-coded rules. In those instances, the robots can neither learn nor adapt to unexpected circumstances, so they are usually confined to perform rote tasks in unchanging environments such as a manufacturing floor.

When AI and robots combine, that’s when the interesting stuff happens. It’s no longer only about efficiency but breaking new ground as well. Self-driving cars, for example, are a product of this union.

What happens if we rely too much on AI?

The most popular products we use are developed and implemented by tech corporations with profit motives. That’s why social media and streaming platforms can be so addictive: the machine-learning algorithms are all pushing us to stay on these platforms for just a little longer. That’s also why ads can sometimes turn predatory: the algorithms get so good at knowing our weaknesses that we end up spending more money than we should have. As algorithms learn more and more about you, implications regarding privacy become a serious concern.

It’s important, therefore, every once in a while to think through how algorithms are impacting your life. What do you like about how they’ve changed it? What do you not? Ultimately, you are in control of the way you interact with them. You could choose to abstain from them entirely: Facebook, for example, gives users the option to turn off automatic photo-tagging. Or you could learn to hack it so that it does different things: if YouTube is showing you too many similar videos, purposely watch some radically different ones to reteach the algorithm about what you want.

What’s your one piece of advice for the reader?

Command algorithms; don’t let them command you! And you’re already one step ahead of the game because you’re reading this book.

As Karen has explained, AI has been around for a lot longer than it first appears. The next chapter takes a closer look at the history of AI. It might not be what you’re expecting …

2

A POTTED HISTORY OF AI

One of the many fascinating aspects of AI is that although it still seems super futuristic, its roots lie in classical thinking. Since we humans have always been partial to making things easier for ourselves, we’ve long been pretty adept at designing machines to increase efficiency. Combine that disposition with some killer mathematics and it’s little wonder that AI has been a twinkle in our eye for quite some time.

The quest for artificial intelligence as we know it began over seventy years ago with the idea that computers would one day be able to think as humans. As so much of the history of AI stems from early computers, we’ll start off by looking at where it all began. You’ll soon notice that early AI was influenced by many different disciplines – yes, mathematics and engineering play their part, but so do biology, game theory, psychology and philosophy. AI is not just the domain of computer scientists. It has always been, and will continue to be, an arena that explores what it means to be human and how we live our lives.

AI’s interdisciplinary nature means that there are many ways to trace its history. This chapter is one way and is not exhaustive. Instead, I wanted to focus on some of the major moments and shine a light on some of the women who’ve been so chronically overlooked along the way. There is a long tradition of women translating or communicating science, partly because of being excluded in some way from the mainstream of conducting it. In fact, I’ve searched far and wide for all the women who played a role in the development of AI, but many were simply never recorded in the archives. This is why I’ve called this chapter a potted history: because I’ve chosen the accounts that most inspired me. Consider this just one way of telling a very complicated story. A historian of science at the University of Cambridge, Patricia Fara, summarised this perfectly when she said to me: ‘Broadening what counts as science’s history entails recognising and crediting women’s involvement.’

I’ve ordered this chapter as a timeline of individuals, but it’s really important to note that the history of AI, as any history of innovation, is never that straightforward. The history of computing in particular is often documented as a series of male geniuses appearing one after another, which simply isn’t the case. So often when history is told as ‘a series of geniuses’, women, particularly women of colour, are erased from the narrative. Among the many reasons for this is the big one: traditionally, the people writing history are the same people who hold the power – white men. When new inventions or ideas shake up our way of thinking or doing, it’s always a result of many people working together, forming communities and pushing things forward – not just one individual, inspired though they may be. So please remember as you read this that it’s ...