I'm not certain whether James Taylor meant to predict the takeover of artificial intelligence and the death of our collective imagination in his 1970 song “Fire and Rain.” Still, somewhere a music teacher is saying to herself: “Called it.”

That teacher is Miss Molloy—a bowl-cutted, crochet-sweatered, denim-skirted woman of 23 or 53—who taught our third-grade music class. One autumn morning, after we sang “Fire and Rain” off mimeographed lyric sheets, Miss Molloy taught us what the song was about, which was the robot apocalypse. “Suzanne, the plans they made put an end to you” meant she had succumbed to the computer chip in her brain, as had all of humanity. This left Sweet Baby James the last remaining human, with the song he’d written her, but he “just can’t remember who to send it to,” because his own chip had been implanted and the surrender of his own consciousness had begun. Pretty chilling stuff for third graders, but we absorbed it, uncritically.

Fifteen years later, I was in a friend’s dorm room listening to “Fire and Rain,” and I said, “I love this song, as scary as it is.” My friend looked at me with concern. I continued, “With the robots and everything?” And then about four seconds later it hit me: I’m going to have to make up a pseudonym for that teacher, because she absolutely got high.

That assessment stands, but listen: It’s 2023, I have at least three pieces of wearable tech on my body at all times, and AI has come for my job. But the most insidious development is that robots that curate our choices, guiding us on what to read, watch, and listen to. When you open Spotify, dozens of playlists wait for you—none of which you or anyone you know created. We have surrendered our taste to the machine. And what’s worse, we’re starting to forget we lived a different way.

Miss Molloy’s interpretation of “Fire and Rain” is objectively bananapants. But was she wrong about the future?

There's a line in Nick Hornby's novel High Fidelity in which the record-store-owning main character says, “What really matters is what you like, not what you are like.” Twenty-eight years after the release of the book, Spotify has prompted new questions: What do we lose when we stop making our own playlists? If the algorithm decides what we like, then what are we like?

“There’s no way a Spotify playlist is as good as a mixtape, or at least mine aren’t,” Hornby tells me. “Because you had to do things in real time, you had the opportunity to think and hear. You were reminded of a lyric, a beat, a sound that would lead you to the next song.” You had to think about who you were giving it to and how you could change their world. “There’s no construction now. In the digital era, it’s just: Here’s some songs you might like.” What I miss—just enough to remember it, for now—is a well-curated jukebox, the way a dollar-bill-huffing machine with a 100-compact-disc capacity could express the personality of a place. My favourite was at the Boiler Room, a friendly, scruffy gay bar in the East Village. This was the ’90s, and we East Village gays shunned the mainstream, so the selection was just slightly to the left of it: Jon Spencer Blues Explosion, Stereolab, Cibo Matto. The exact right soundtrack for a room packed with guys who could fit into X-girl T-shirts. A curatorial ear and a hive mind.

Without curation, everything is also nothing.

I returned to the Boiler Room recently, and as most places have, it’s adopted an Internet-enabled jukebox. Every song that exists on streaming, at your fingertips. But without curation, everything is also nothing. The hive mind breaks down into individual bees. A proper jukebox, like a homemade mixtape, is already largely a memory.

And soon enough it won’t be. It will be a thing you forgot even existed in the first place, like decent mass-produced chocolate, like a flight that doesn’t end with a pitch for a credit card. Like the Boiler Room itself, which is closing later this year.

"The absence of curveballs in algorithmic playlists is noticeable,” Hornby says. “I don’t want something that sounds exactly like what I usually listen to, just like I don’t want recommendations for books in a similar vein to the ones I write.” Right around the time Hornby was writing High Fidelity, the best mixtape I ever got came from a college friend named Brady. It arrived in my P. O. Box just before I graduated and moved to New York City. There were pop songs, left-field disco tracks, and at the end of side 1, “Being Alive,” from Stephen Sondheim’s Company. I’d never heard it and It was a gut punch: the precise sound of my soul as I prepared to start my life. A reminder to be less aloof in the real world than I had been in college. An I see you from someone I didn’t know was watching. A life changer.

The algorithm can’t be Brady. It can give you what it knows you want. But without human insight, it cannot give you what you need. It will not encourage you to evolve, because it cannot work as well if you do. The algorithm can know you. Scarily well. But it cannot love you. Commit an act of rebellion today: Make a playlist for someone. Assemble it with care. Throw in some curveballs. Choose a song or two that will make them feel seen, give it a clever name, text it to the person. Do it right now, before the chip takes hold of your brain.

I want to find Miss Molloy. I want to tell her I remember. All I have to do is find her. Anybody got an extra ticket to Burning Man?

Illustration By Matt Mahurin

Originally published on Esquire US

Having dedicated my career to funding, building, and growing new technologies, I’ve been present for many disruptions. In the post-dot-com bubble pop era, we witnessed the revolution of communications, online payments, marketplaces, advertising, and media by companies like Skype, Amazon, Uber, Google, and Netflix. These companies leveraged new technologies to build new business models or digitise ones that, in some cases, had existed for hundreds of years. Long after Facebook became a verb, we witnessed the eruption of Web3 and the eruption of evangelist techbro social media influencers shilling their special brew of lifestyle grandstanding and NFT minting.

But, as a former venture capitalist, I’ve yet to see a nascent technology so wholly and rapidly evangelised outside of its own circles of investors, builders, and users as Artificial Intelligence. It’s almost as if Steve Jobs rose from the grave to deliver a keynote on the potential of AI. So, out of curiosity for Steve’s insights on the topic, I tasked OpenAI’s ChatGPT tool with bringing him back to life and introduce AI in the style of one of his famous keynote speeches:

Good morning everyone, and welcome to this exciting keynote on artificial intelligence.

Today, I want to talk about a revolutionary technology that has the power to change the world as we know it. It’s a technology that’s been around for decades, but it’s only in recent years that we’ve seen its true potential start to unfold. I’m talking, of course, about artificial intelligence.

AI has the power to automate many of the tasks that we do every day, freeing us up to focus on the things that matter most. It has the power to make our lives easier, more efficient, and more connected. But more importantly, it has the power to solve some of the world’s biggest problems.

Think about it. With AI, we can tackle issues like climate change, poverty, and even the spread of diseases. The possibilities are truly endless, and the potential for impact is massive.

At the same time, we need to be mindful of the potential risks that come with this technology. We need to ensure that AI is developed in a responsible and ethical way, and that it serves the interests of humanity as a whole.

So let’s get to work. Let’s harness the power of artificial intelligence to build a better future for all of us. Thank you.

AI Steve Jobs Speech generated by ChatGPT

As AI Steve highlighted above, AI itself is not new. Prior to the release of tools like DALL-E, we saw AI leveraged for specific use cases across most major industries such as marketing, cybersecurity, and even CGI / animation in media. We’ve been using the technology for decades to classify, analyse, and create data (including text and images) for narrow sets of tasks, which is why it’s referred to as “Artificial Narrow Intelligence”. In contrast, new models allow for many use cases with no additional training or fine-tuning. This evolution from the previous generation of AI to today’s Generative AI models underpinning applications such as ChatGPT, DALL-E and others has been driven by advances in computing power, cloud data storage, and machine learning algorithms.

Unlike Web3, AI has already demonstrated its usefulness and potential beyond theoretical adoption. Also, unlike its predecessor in the timeline of popular new technologies, it doesn’t require mass adoption of a new protocol or regulatory approval. There are two possible applications of AI: the optimization of existing digital processes and the digitization of human tasks.

Generated with DALL-E | Prompt ‘Dubai in the style of Edward Hopper’

Optimization increases the speed and reduces the need for human input into existing algorithms. A straightforward example would be chatbots, which had their moment in the latter half of the 2010s and are making a comeback, armed with better-trained algorithms. Chatbots trained with existing customer care data sets will replace notoriously difficult-to-navigate FAQ pages on websites and costly call centres. The result will be a lower cost to do business and improved satisfaction.

This brings us to the frightening or exciting – depending on who you ask – scenarios where AI leads to the replacement of human roles. Short-term, this could range from copywriting, software engineering, art, animation, business analysis, and journalism. But, again, this isn’t a futuristic dream pontificated by the Silicon Valley elite on their three-hour podcasts; this is happening today. For example, Buzzfeed recently announced that it would start using ChatGPT to write journalistic pieces after technology journalism outlet CNET was found to use the same tool to write personal finance articles.

Readers should consider that despite the countless applications of AI, there is no cause for alarm when it comes to making the human worker redundant. The evolution of technology is an inevitability and we are better served by preparing for it rather than resisting it. Many pundits draw comparisons to the widespread fears of the industrial revolution replacing jobs. In the short term, these fears are unfounded. So long as the models underpinning applications exist in a state of ANI, even the most advanced tools will require human input and oversight. However, these tools will complement and augment human work by replacing menial, repetitive tasks in creative and technical fields. For example, this article was reviewed using Grammarly to check for spelling and grammar mistakes. 

Although we’re progressing beyond ANI, there’s still quite the journey ahead of us and little consensus on when we might reach our destination. Some scientists estimate that we’re decades away from progressing to the next state of Artificial Intelligence: Artificial General Intelligence (AGI). AGI would offer capabilities such as sensory perception, advanced problem-solving, fine motor skills and even social and emotional engagement. There’s quite a distance to travel from writing Shakespearean sonnets about lost socks in the dryer to developing a personality like that of Samantha, the protagonist’s AI companion in the 2013 film Her. It’s impossible to predict how soon we could begin to describe AI as AGI; estimates on timing range from a decade or twenty, if ever.

When it comes to Arabic, language models need to catch up. Today’s models are predominantly trained on content publicly available on the internet: webpages, Reddit, and Wikipedia make up approximately 85% of ChatGPT’s training data set, for example. Considering that approximately 60% of written content online is in English and less than 1% in Arabic, the inputs necessary to achieve the same quality outputs in the latter are nonexistent. It’s no secret that English is the lingua franca of Middle East business. Still, we should ask ourselves whether this will further subdue the use of Arabic in such settings. The impetus to ensure the development of the Arabic language in technology and business settings lies both in the private and public sectors in wealthy Gulf countries.

While there are reasons to celebrate AI’s coming of age, we need to keep our feet on the ground. The limitation on the applications of AI is compounded by questions of ethical standards, reliability, accuracy, and truthfulness raised by academics such as Gary Marcus, a leading AI sceptic. Even Mira Murati, the CTO of OpenAI (creators of the models underpinning DALL-E and ChatGPT) is arguing for regulatory oversight of AI. Questions remain on how to solve topics such as moderating offensive model outputs, intellectual property infringement, policing disinformation, and academic honesty to name a few. 

“How do you get the model to do the thing that you want it to do, and how do you make sure it’s aligned with human intention and ultimately in service of humanity?” 

Mira Murati, CTO, OpenAI

Make no mistake, AI is beyond the point of no return, but that doesn’t mean we can’t harness its power to empower our workforces and transform our lives. Although the excitement surrounding AI’s potential is justified, the challenges of its usage and misuse are much more significant than those of previous generations of technology and should not be taken lightly. We have at our disposal an incredible new tool; however, we must balance our eagerness to watch with mindfulness of the risks and implications and careful regulation. 

Rayan Dawud is a former venture capitalist who has held senior roles at Careem and Outliers Venture Capital in Dubai. He’s currently on a career break in London, where he’s exploring Artificial Intelligence.

Featured image generated using DALL-E with prompt ‘android from the film Ex Machina in a Hopper painting’

Originally published on Esquire ME