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Restless Grounds

Restless Grounds

Podcast society
🔄 Data last refreshed 4 hours ago
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Ratings
N/A
Episodes
5
Cadence
0.1 ep/wk
Latest episode
7 months ago
🎁 Free analysisfor Restless Grounds

💡 Facts

📤Posts about 0.1× per week.

👥 Audience demographics

Estimated

Modeled from this creator's niche, platform & region — a planning estimate, not connected analytics.

Gender split
Male 51% Female 49%
Age · peak 18-24
13-178%
18-2435%
25-3429%
35-4418%
45+10%
Top geographies
  • United States34%
  • India11%
  • United Kingdom8%
  • Brazil6%
  • Indonesia5%
Likely interests
EntertainmentLifestyleTrending

💚 Brand affinity

Estimated

Brands Restless Grounds's audience is most likely to respond to — from detected sponsorships in this niche.

Keeps Coinbase Robinhood NordVPN Incogni Shopify BetterHelp Webull Raycon G FUEL

About

This series is part of the Slow AI project, a collaborative research initiative that emerged from a growing discomfort with the ways artificial intelligence is transforming our world and how quickly it is being developed and implemented, while its extractive, colonial histories remain largely unacknowledged.From image generation and chatbots to facial recognition and predictive policing, AI systems are shaping what we see, how we remember, how we make decisions, and eventually who we become.Rather than trying to fix or limit these technologies, Slow AI asks how we might relate to them differently. It is not a technical solution, but a shift in orientation: toward care, collectivity, and refusal.Each episode features a conversation from our research group, comprising artists, writers, and researchers working at the intersection of theory and practice. These conversations emerge from our Material Playgrounds: experimental sessions that explored algorithmic technologies through artistic research, speculation, and collaborative inquiry.Messy, curious, and sometimes unresolved, this podcast invites you to imagine these technologies otherwise.This podcast is part of the Slow AI project, initiated by Mariana Fernández Mora and supported by the Visual Methodologies Collective (AUAS), the Algorithmic Cultures Research Group (Sandberg Institute), ARIAS Amsterdam, and funded by the Centre of Expertise Creative Innovation (CoECI).

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