AI lab by information labs

🔍 In this TL;DR episode, Anna Tumadóttir (Creative Commons) discusses how the evolution of creator consent and AI has reshaped perspectives on openness, highlighting the challenges of balancing creator choice with the risks of misuse. Examines the limitations of blunt opt-out mechanisms like those in the EU AI Act, the implications for marginalized communities and open access, and explores the need for nuanced preference signals to preserve openness while respecting creators' intentions in the age of generative AI.

⏲️[00:00] Intro

⏲️[00:38] Q1-How has the conversation around creator consent and AI evolved in the past few years?

⏲️[05:42] Q2-How has the tension between openness and creator choice played out so far, and what lessons can be learned from this tension?

⏲️[11:02] Q3-can we ensure that marginalized or underrepresented communities maintain agency over their contributions to the commons?

⏲️[19:03] Wrap-up & Outro

🗣️ "When AI became mainstream, most creators couldn’t have anticipated how their works might one day be used by machines—some uses align with their intentions, but others do not."

🗣️ "Individuals want more choice over how their work is used, and without tailored options, some are considering paywalls or not publishing at all."

🗣️ "The EU AI Act’s opt-out mechanism is a blunt instrument—it’s just a 'no,' not a nuanced reflection of creators’ varied preferences."

🗣️ "Creators may object to large companies using their works for AI training but be fine with nonprofits or research-focused uses, showing the need for more nuanced tools."

🗣️ "We’re focusing on developing 'preference signals'—mechanisms that let creators communicate specific preferences for how their work is used in AI models."

🗣️ "Scientists and researchers who traditionally embraced open access are now reconsidering, fearing that commercial AI providers are exploiting their work."

🗣️ "Creators who once freely shared their work under CC licenses are now hesitant, either because they misunderstand AI training risks or feel exposed."

🗣️ "The worst outcome of this tension is less openness overall—creators retreating behind paywalls or choosing not to publish at all."

🗣️ "A perception persists in the open-source AI community that CC-licensed works are 'safe' to use, but creators’ motivations for sharing openly years ago don’t always align with today’s AI landscape."

🗣️ "To preserve openness while respecting creator intentions, we need mechanisms that enable a 'no unless' approach—minimizing restrictions while maximizing use."

🗣️ "Generative AI amplifies existing inequalities because it demands infrastructure like electricity, internet, and computing power—resources many regions lack."

🗣️ "Even if everyone had equal internet access, a one-size-fits-all approach to technology wouldn’t work due to local contexts and different needs."

🗣️ "Traditional knowledge should be exempt from broad data mining rights, allowing communities to explicitly give or revoke permissions for its use in AI training."

🗣️ "We need public AI infrastructures that ensure diversity and regional perspectives while maintaining communities’ agency over their contributions."

🗣️ "To prevent lopsided development, policies must go beyond tools like preference signals and address broader governance and societal frameworks."

🎙️ Anna Tumadóttir | Creative Commons

🌐 Article | Questions for Consideration on AI & the Commons

https://creativecommons.org/2024/07/24/preferencesignals/ 

🌐 Anna Tumadóttir 

Anna is the CEO of Creative Commons, an international nonprofit organization that empowers people to grow and sustain the thriving commons of shared knowledge and culture.

#AI #ArtificialIntelligence #GenerativeAI