94. Divya Siddarth - Are we thinking about AI wrong?

94. Divya Siddarth - Are we thinking about AI wrong?

Author: The TDS team July 28, 2021 Duration: 1:02:44

AI research is often framed as a kind of human-versus-machine rivalry that will inevitably lead to the defeat — and even wholesale replacement of — human beings by artificial superintelligences that have their own sense of agency, and their own goals.

Divya Siddarth disagrees with this framing. Instead, she argues, this perspective leads us to focus on applications of AI that are neither as profitable as they could be, nor safe enough to prevent us from potentially catastrophic consequences of dangerous AI systems in the long run. And she ought to know: Divya is an associate political economist and social technologist in the Office of the CTO at Microsoft.

She’s also spent a lot of time thinking about what governments can — and are — doing to shift the framing of AI away from centralized systems that compete directly with humans, and toward a more cooperative model, which would see AI as a kind of facilitation tool that gets leveraged by human networks. Divya points to Taiwan as an experiment in digital democracy that’s doing just that.


While the active production of Towards Data Science has concluded, its archive remains a vital resource. Created by The TDS team, this collection captures a specific moment in the rapid evolution of data science and artificial intelligence. Each conversation pulls you directly into the room with leading researchers and practitioners who were shaping the tools and theories of their time. The discussions are not abstract lectures; they are grounded explorations of real-world problems, ethical dilemmas, and technical challenges that defined the field's trajectory. You'll hear experts dissect the implications of their work, from algorithmic fairness to the practicalities of deploying models at scale. This podcast served as a forum for nuanced debate, where complex ideas were unpacked with clarity and depth. Listening now offers a unique historical perspective, a chance to understand the foundational conversations that continue to influence where technology is headed next. The archive of Towards Data Science stands as a substantive record of insight, preserving the voices and questions from the forefront of a digital revolution.
Author: Language: en-us Episodes: 50

Towards Data Science
Podcast Episodes
87. Evan Hubinger - The Inner Alignment Problem [not-audio_url] [/not-audio_url]

Duration: 1:09:32
How can you know that a super-intelligent AI is trying to do what you asked it to do? The answer, it turns out, is: not easily. And unfortunately, an increasing number of AI safety researchers are warning that this is a…
86. Andy Jones - AI Safety and the Scaling Hypothesis [not-audio_url] [/not-audio_url]

Duration: 1:25:44
When OpenAI announced the release of their GPT-3 API last year, the tech world was shocked. Here was a language model, trained only to perform a simple autocomplete task, which turned out to be capable of language transl…
85. Brian Christian - The Alignment Problem [not-audio_url] [/not-audio_url]

Duration: 1:06:19
In 2016, OpenAI published a blog describing the results of one of their AI safety experiments. In it, they describe how an AI that was trained to maximize its score in a boat racing game ended up discovering a strange ha…
83. Rosie Campbell - Should all AI research be published? [not-audio_url] [/not-audio_url]

Duration: 52:37
When OpenAI developed its GPT-2 language model in early 2019, they initially chose not to publish the algorithm, owing to concerns over its potential for malicious use, as well as the need for the AI industry to experime…
82. Jakob Foerster - The high cost of automated weapons [not-audio_url] [/not-audio_url]

Duration: 54:07
Automated weapons mean fewer casualties, faster reaction times, and more precise strikes. They’re a clear win for any country that deploys them. You can see the appeal. But they’re also a classic prisoner’s dilemma. Once…
81. Nicolas Miailhe - AI risk is a global problem [not-audio_url] [/not-audio_url]

Duration: 56:03
In December 1938, a frustrated nuclear physicist named Leo Szilard wrote a letter to the British Admiralty telling them that he had given up on his greatest invention — the nuclear chain reaction. "The idea of a nuclear…