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In my teens I read the classics of science fiction copiously–Clarke, Heinlein, Asimov, Le Guin. Among the many tropes (space travel, galactic empires, to a lesser extent time travel) common to those stories was what we now term Artificial Intelligence–though while that term initially applied quite narrowly (more for less things that might pass the Turing Test, and essentially appear to have sentience indistinguishable from that of a human) we now use it extremely broadly.

This fascination with artificial intelligence was what actually drew me to computer science in the 1980s–though the one and only unit on it I studied at university was an elective toward the end of final year, which. rather than focusing on sentient software and positronic brains, was all hill climbing algorithms and local maxima. Very disappointing.

In the decades since, AI has had its moments in the sun, and its long winters–though over the last decade, whole new approaches, enabled by enormous amounts of inexpensively available data, ever cheaper storage, increasing (and vastly cheaper) computing power (particularly GPUs), and new approaches to machine learning have lead to what is being called an AI spring.

Where this is having the most obvious impact is generative AI

algorithms that enable computers to use existing content like text, audio and video files, images, and even code to create new possible content

Generative AI Models Explained

It’s clear these approaches offer enormous opportunities–for their users, and also for building whole new categories of product. From code auto-complete tools like Co-pilot, to increasingly powerful and accurate speech to text services, applications that write fiction, or summarise new sources, not to mention software that will create images and even videos from text prompts.

And like emerging technologies so often do, these will challenge our legal and ethical frameworks, established economics, business models, whole industry sectors.

Opportunity. Challenge. Risk. All these are presented by the rise of these new systems.

There are many ways we might respond. Naively embracing the new and its opportunities (though hopefully we’ve learned form the last couple of decades that even the seemingly most benign and beneficial new technologies can have more challenging second order effects and unintended consequences). We might, like the Luddites (for whom I actually have quite a bit of sympathy and admiration) aim to minimise these technologies.

So, Web Directions Summit we’ve asked our good friend Mark Pesce, someone who thinks more deeply about issues like these than just about anyone I know, to explore the opportunities, challenges, threats, risks of AI today.

Years later people still talk about some of Mark’s keynotes at our conferences. I genuinely think this will be among the most valuable presentations you might ever see.