This week on The Digital Life, we talk about the future of work, the anxiety of the gig economy, and how we might re-imagine digital platforms, inspired by the essay “Do platforms work?” on Aeon.co. In the Gig Economy, work is an on-demand affair, driven by the needs of the moment, whether you’re an Uber driver, freelance marketing expert, or contract product designer. The temporary nature of this work — which is arbitrated by software which matches buyers and sellers — puts much power in the hands of the platform owner. For gig workers, earning a living is dependent on demand, reputation, and ultimately, the whims of a digital overlord. But what if there was a way for these workers to own a piece of that all important platform? Join us as we discuss.

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Do platforms work?

This week on The Digital Life we discuss the possibilities and perils of editing human genes in light of the news, earlier this week, that Chinese scientist He Jiankui of the Southern University of Science and Technology, claimed to have created the first gene-edited babies using CRISPR, the revolutionary gene-editing tool. The twin girls had the CCR5 gene deleted to make them resistant to HIV and other diseases. The scientist is now being investigated over whether the experiment was in violation of Chinese laws and regulations. This technology is particularly sensitive from an ethics standpoint because any changes will be inherited by future generations. What are the consequences that stem from this experiment, perhaps, the first gene-edited humans? Join us as we discuss.

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The era of human gene-editing may have begun. Why that is worrying
China suspends scientists who claim to have produced first gene-edited babies

This week on The Digital Life, we discuss the Productivity Paradox, inspired by the recent article in MIT Technology Review, “Advanced tech, but growth slow and unequal: paradoxes and policies”. While we’re experiencing an unprecedented boom in technology, the accompanying massive productivity boost that we might expect to see has failed to materialize. In fact, in many major economies, productivity growth is slowing. So, what’s the reason for this unexpected outcome? To begin with, our ability to absorb, integrate, and leverage technologies effectively — from mobile to artificial intelligence to the internet of things — has limits. While the technology might be present, it is not been distributed and utilized in ways that have yielded productivity gains in rapid fashion. Constructing the systems, workflows, and roles to take advantage of these new technologies will take time. And, in concert with these, it will be vital that, as a society, we develop policies that support and enable people to shift into new work roles and invest time in learning new skills. Join us as we discuss.

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Advanced tech, but growth slow and unequal: paradoxes and policies

This week on The Digital Life, we discuss emerging technologies and the self. What makes us ourselves, the way we take in information, the way we share, communicate, collaborate and interact with people has gone digital in a number of ways. In particular, we delve into the topic of virtual reality experiences and empathy, based on the article in Aeon, “It’s dangerous to think virtual reality is an empathy machine”. VR can change how we think about the world, helping us understanding different perspectives. For instance, the Virtual Human Interaction Lab at Stanford University created a simulation from the perspective of a cow, of being raised for the slaughterhouse. There are immersive VR experiences of becoming homeless and experiencing racism. But what is the true impact of these early experiments? Join us as we discuss.

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It’s dangerous to think virtual reality is an empathy machine
Stanford University Virtual Human Interaction Lab

This week on The Digital Life, we discuss the pitfalls of predicting AI. AI predictions range from the measured and meaningful to highly unrealistic and downright hysterical. But how can you tell the difference? In this episode, we dig into some rules of thumb for thinking through the AI predictions we encounter, as laid out in the article “The Seven Deadly Sins of AI Predictions” by Rodney Brooks, a founder of Rethink Robotics. From better understanding the properties of narrow AI to asking “how will it be deployed?”, questioning supposed magical properties without limit, to admitting, in the long term, we just don’t know, we’ll explore the many factors that counter the breathless hysteria of AI predictions. Join us as we discuss.

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The Seven Deadly Sins of AI Predictions