Algorithms are all around us. From searching the web or finding your way to work, to falling in love online, algorithms are responsible for the legwork that helps us make decisions hundreds of times every day. Simply put, it’s a step-by-step list of instructions written by a programmer to make a computer solve a task. A bit like a recipe is an algorithm for solving the task of cooking.
Google’s PageRank algorithm, fraud detection, matchmaking sites, GPS, real-time ads, email spam filtering and personalised recommendations like those from Amazon and Netflix… each one works thanks to an algorithm that a programmer has coded.
Until recently, a programmer had to explicitly write out each and every step a computer needed to make, and crucially, he or she had to decide how the algorithm was going to tackle its particular task. Once the legwork was done by the computer, and the data was processed, the programmer needed to know which patterns to look for to achieve a particular goal.
However, a new breed of machine-learning algorithms have radically disrupted the status quo. These algorithms have the ability to iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed to look for specific patterns. They learn from previous computations, essentially their ‘experiences’, to produce reliable and actionable decisions. A class of algorithms called Artificial Neural Networks are loosely based on our understanding of how the brain works, and aim to emulate aspects of how decision making emerges from the interconnected neurons firing away in our brains.
What about creative algorithms? Surely that’s a paradox, right?... - algorithmic design isn’t aimed at replacing human insight but to transform the design process by serving up thousands of viable options…
What about creative algorithms? Surely that’s a paradox, right? Industrial designers have typically used software to draw and analyse their creative vision, however, more recently, computer programs have used genetic algorithms to generate the idea itself and then go on to actually develop the design – Autodesk is one of several examples. The entrepreneurs behind Autodesk claim that they can generate millions of iterations of the same chair in the time it would take a human designer to mock up just a single chair. Will this render designers obsolete? Not necessarily – algorithmic design isn’t aimed at replacing human insight, but to transform the design process by serving up thousands of viable options and automating the more tedious aspects of the design process.
Ghost in the machines?
How about algorithms writing the next hit musical? A step too far, surely. Algorithms – and by extension, computers – are typically seen as soulless, whilst writing a musical resides at the other end of the spectrum… full of human emotions and drama, carefully curated for aesthetic pleasure. Sky Arts’ mini-series brought together Europe’s leading data scientists for a world-first experiment: creating the first piece of musical theatre generated by computers, including the overarching story, characters, plot, setting, structure, music and even algorithmically-generated lyrics, which was highly original and dramatic (i.e., A girl is a carnival star that’s been born). A variety of different algorithms led to the birth of the musical, all overseen by award-winning writer-composer duo Benjamin Till and Nathan Taylor, who tied everything together into a final West End production. The end product was a fairly successful musical called Beyond the Fence, which was not quite in the Les Mis league, but not that far off either.
This also gradually marks the transitioning of algorithms, especially smart algos, moving towards shaping culture, which is likely to profoundly change the way we humans live and work, but also see ourselves as the only form of intelligent beings.
Evolutionary biologists have long argued that our thinking and development was partly shaped by the tools we used throughout prehistory. Algorithms started off as mere tools for us to use, but as they become more intelligent and capable of independent reasoning, they will seamlessly form part of the rich sociocultural tapestry of human society. The path is fraught with challenges in the immediate future, but there are limitless possibilities of not only increased efficiency, but also evolving what it means to be truly human.