Think Artificial Intelligence (eBook)

Chapter One –

CAN MACHINES THINK… WITH US?

Do Androids Dream of Electric Sheep?

Covered In This Chapter

• Meet Jerry: Your Guide to AI
• I, Karel the Robot
• Potential of AI-powered Automation
• Building Trust in AI
• Collaboration Between Humans and AI

Here we go

The day my dad walked in with an IBM PC in 1982, that’s when things got serious. That PC was more than just a computer; it was my ticket to a whole new universe. I cut my teeth on BASIC. I’d be there in our living room, typing away, turning code into commands, and watching my ideas come to life on that screen. It wasn’t just coding for me; it was like opening a dialogue with a new friend who spoke a language made of code and pixels.

Prompt: … Vintage-style illustration of a boy and robots collaborating at a desk with an IBM PC, circa 1982.

Hi, I’m Jerry. That’s a generated image of me, and those robots—well, I guess you could suppose they’re my parents or something like that. Considering my lifelong obsession with technology and everything digital, that’s likely how I perceived them back then.

I will be your guide for this book. Welcome aboard!

I once heard a wise saying: “The past is behind, so let’s learn from it. The future lies ahead, so let’s prepare for it.”4 With that as our inspiration, I’ll begin by examining the past, starting with the events that led to my role as your guide today. You see, by sharing my background, you’ll hopefully gain an understanding why the subject of this book both excites and holds great significance for me.

Following that, we will prepare for the future by meeting various colleagues of mine (some real, some fictional), each offering a unique perspective on AI.

Let’s begin.

Jerry.AI

I’m an engineer and a frequent user of generative AI (GenAI) – I’d estimate about 12 times a day, and that number is rising. It’s incredibly useful for completing tasks and kick-starting projects. Take coding, for example. It’s been some time since coding was a direct part of my job, but being able to converse in code with my developer colleagues is invaluable. Well, thanks to AI code assistants looking over my shoulder, I can make Python dance and sing to my tune.

Back in those early PC days, artificial intelligence was already a recognized discipline in some universities. Still, it wasn’t until grad school that I acknowledged its significance and truly became a student of AI. Call it AI or something else, the experience of getting computers and software to perform unexpected and practical tasks was incredible. These moments typically followed a predictable coding pattern: utilizing logic to sift through data, making informed choices, and gradually refining the process. On the better days, it felt like the software was genuinely thinking and learning. Yet, on the more challenging ones, I’d sometimes sense a hint of malice in it, as if it was intentionally working against me. I’d often ask in frustration, “How can I trust this code when it seems to have a mind of its own today? For Pete’s sake, please just do what I’ve coded you to do… please!”

My (robot) parents did well teaching me the difference between right and wrong and being accountable for one’s actions. While software can be highly intelligent, it lacks the capacity for malice. Thus, the ethical responsibility for software’s actions rests squarely with its creators. My philosophy is simple: the more trustworthy the software, the more it gets used. After all, what’s the point in writing software if no one will use it?

So, throughout my career, I’ve made it a point to focus on creating software that’s not only trustworthy but also boosts both creativity and productivity. This approach allows people to dedicate more time to what truly matters. The shift towards AI-driven systems offers a chance for effective collaboration between human ingenuity and machine intelligence, each complementing the other. I believe AI should enhance human capabilities, not replace them, and trust in this relationship is key. If I were to frame this concept in the form of a formula, it might look something like this:

Trust(Human + AI) = Amazing.

In this (somewhat geeky) context, ‘Trust’ is applied to both ‘Humans’ and ‘AI,’ resulting in something ‘Amazing.’ This theme is a recurring focus throughout this book, and we’ll revisit it several times before we conclude, but for now, let’s return to my story. After sharing more of my personal experiences, I’ll link them to the broader principles and historical progress of AI in the upcoming chapter. So, where were we? That’s right, next up: Robots.

I, Robot

Robots have always been an interest of mine and my gateway to AI. As a kid, they were the coolest thing imaginable – a blend of imagination and the future right in front of me. It all started, really started, with Isaac Asimov’s famous book, I, Robot. Did I finish it? Well, no, I got about three-quarters of the way through. But what I did read opened my eyes to a world where robots weren’t just machines but beings with dilemmas and decisions.

Asimov’s Three Laws of Robotics articulated in I, Robot are: 1) A robot may not injure a human being or, through inaction, allow a human being to come to harm. 2) A robot must obey the orders given to it by human beings, except where such orders would conflict with the First Law. 3) A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.6 Asimov’s vision, intertwining safety, obedience, and self-preservation in robotics, mirrors the crucial elements of trust and responsibility integral to AI development today.

Reflecting on I, Robot, I realize it laid more than just a foundation for AI ethics. It opened my eyes to how ethics and trust are crucial for the widespread adoption of AI, much like the EU’s 2023 ethical AI regulations, which you’ll find referenced in a forthcoming chapter.

Karel the Robot

My initial curiosity about robotics and AI was brought to life with Karel the Robot: A Gentle Introduction to the Art of Programming by This book was not just another step in programming; it was my first genuine experience with what seemed like intelligence within a machine. Karel made quite the impression, as it provided me, a teenager then, with a powerful tool to explore robotics and AI through programming. It marked the start of an exciting adventure where I could apply my programming skills to bring intelligent behavior to life.

Prompt: ... Karel the Robot navigates a grid with simple decision-making as illustrated in this code example {insert code example}

Karel was a simple robot in a grid world, and the programming language used to control it was straightforward, yet it opened up a world of possibilities. The moment that truly captivated me was when I wrote a program where Karel had to escape a maze. It was the simplicity of the IF statement, the robot’s ability to ‘check’ its surroundings and make a decision, that felt to me like the first glimpse of intelligence. Here’s a version of what that program looked like:

Code: DecisionBasedNavigation.kl

Prompt: ... Karel the Robot script for decision-based navigation with procedures for turning and movement, including comments for guidance.

Karel consistently monitors its immediate environment in the program, which can be found on GitHub via the source reference above. If it could turn right, it would. If not, but it could move forward, it would proceed. Otherwise, it would turn left. This simple decision-making process, driven by IF statements, was my introduction to the idea of a computer making choices based on its environment. It was a revelation – the realization that even with a few lines of code, I could make Karel ‘think’ in an elementary way. This ability to ‘check and decide’ brought a sense of intelligence to the code, however rudimentary it might have been.

As I eventually transitioned from Karel’s simplistic yet profound logic to more advanced languages like Lisp and Python, I witnessed firsthand the power of these tools in shaping AI. They were not just languages but the very building blocks that enabled us to communicate and expand the boundaries of machine intelligence. Thank you, John McCarthy. If you don’t already know of John, I’ll introduce you to him shortly.

Freeing the Code from the Box

During college, my curiosity about programming took a more adventurous turn. I wasn’t content with just making things happen on a computer screen. I wanted to break free from the digital confines and make an impact in the...