Spark

The climate is changing. So are we. On What On Earth, you’ll explore a world of solutions with host Laura Lynch and our team of journalists. In 1970, 20 million people showed up to fight for the environment on the first Earth Day. More than five decades later, is it time for this much tamer global event to return to its radical roots? OG organizer Denis Hayes recounts how �

From the earliest musical instruments to the metronome, to vocoders, auto-tune and beyond, music creation has always been a collaboration between humans and machines. But now that generative AI is shaking up songwriting, have we crossed a new threshold where the distinctively human talent for music is no longer ours alone?

Strides in AI software are finding their way into physical robots. It's promising a new era of human-robot interaction, where robots can assist us, respond to our needs and to cues in the environment. Question is: are we ready for robots among us?

Like most of us, you probably only think about infrastructure when it doesn't work: the power goes off, the roads flood. But in the face of climate change and the increasing energy demands of our digital tech, how can we rethink what infrastructure looks like to meet our future needs?

One of civilization's oldest technologies, textiles have long been linked to money, power, and politics. Now, researchers are looking to produce novel, more sustainable textiles using organisms like yeast, fungus, and bacteria.

What does play mean in a digital age, when so much happens on our all-consuming phones, and tech erases the boundaries between work and play?

In an age of misinformation and generative AI, how do we know if anything we read or hear is even real anymore? From the latest trends in internet search to watermarking images to (re)establishing trust in journalism, we examine the role of proof in a post-truth world.

Digital twin technology is growing rapidly across multiple industries. From race cars to the human heart to the entire country of Canada, a look at how these virtual replicas use real-time data to model and predict the future.

We keep hearing that AI is going to revolutionize jobs. But what if the language of inevitable automation hides the ongoing need for distinctly human skills?

Along with huge advances in data-driven technologies like machine learning and digital health, there are troubling concerns about our data privacy in healthcare, and persistent problems with bias in artificial intelligence. So how do we get the tools we want with the ethics we need?