Crazy Wisdom
Episode #559: Hug a Tree Before You Upgrade Your Brain: A Conversation on What Makes Us Human
- AI & Agents
- Argentina & Latin America
- Knowledge & Learning
- Robots & Atoms
- AI
- artificial intelligence
- education
- language learning
- Amolingua
- Lingo Plus
- EcoCivilization
- roundtables
This video isn't available here. Try YouTube, or listen to the audio below.
Watch on YouTubeAbout this episode
Timestamps
- 00:00Stewart welcomes Ekaterina Matveeva, founder of Amolingua and Lingo Plus, discussing her work organizing AI roundtables with EcoCivilization
- 05:00Ekaterina shares her evolution from anger toward AI in 2023 to realizing collaboration potential, emphasizing importance of multicultural perspectives in AI development and training
- 10:00Discussion of Argentina's new AI liability bill creating human-out-of-loop systems, contrasting with Europe's human-in-loop requirements and different global regulatory approaches
- 15:00Safety considerations in robotics and AI development, comparing industrial automation standards across regions and discussing Pentagon's use of Anthropic with Palantir systems
- 20:00Exploring brain-computer interfaces and Neuralink developments, questioning enhancement versus necessity and examining motivations behind cognitive augmentation technologies
- 25:00Debating human capabilities beyond cognitive function, discussing nervous system, emotions, psychosomatics, and whether brain generates or receives thoughts
- 30:00Examining societal divisions from enhancement technologies, referencing Avatar and Years and Years series, questioning benefits for healthy individuals versus disability applications
- 35:00Discussing technological gaps between enhanced and standard populations, concerns about corporate seduction into cybernetic modifications, and lack of long-term safety studies
- 40:00Questioning who frames AI conversations and trains models, exploring dominant worldviews embedded in AI systems and Vatican-Anthropic collaboration implications
- 45:00Stewart shares mistakes with Facebook biometric data and building personal AI infrastructure, emphasizing importance of controlling your own models and data
- 50:00Analyzing whether massive data collection actually improves AI training, questioning if user conversations become buried garbage rather than meaningful model improvements
- 55:00Ekaterina discusses plans for organizing more roundtables, integrating indigenous wisdom into AI training, and connecting on LinkedIn for future collaborations
Key Insights
- Ekaterina Matveeva's perspective on AI has evolved significantly since 2023, moving from initial anger and fear about AI's impact on education and translation work to becoming actively involved in AI development and training. She realized that instead of resisting AI advancement, she could participate in shaping it by contributing her expertise in education, language, and cross-cultural communication. This shift represents a broader realization that diverse participation in AI development is crucial for creating more versatile and culturally sensitive models rather than allowing a monopoly of values from any single country or culture.
- The conversation highlights fundamental differences in AI regulation across regions, with Europe implementing human-in-the-loop requirements and comprehensive safety measures, while Argentina is reportedly creating frameworks for human-out-of-the-loop AI systems with limited liability. The United States falls somewhere between these approaches, pursuing rapid advancement with fewer regulatory constraints. These divergent approaches reflect different cultural values and priorities, raising important questions about whether AI development should prioritize efficiency and profit or human oversight and control in critical infrastructure sectors.
- Both speakers express concern about brain-computer interfaces like Neuralink, questioning the motivation behind enhancing cognitive abilities when humans already possess multiple forms of intelligence including emotional, cultural, and bodily intelligence. The primary applications demonstrated so far appear limited to video games and potentially military applications, raising questions about whether the technology serves genuine human needs or merely represents an attempt to compete with robots. The speakers emphasize that humans are already complete beings with sophisticated nervous systems, senses, and capabilities that extend far beyond cognitive processing.
- A critical insight emerges around the question of what happens when advanced technologies are removed or turned off. This applies both to brain-computer interfaces and to broader civilization infrastructure dependencies. The speaker shares experiences from 2020 of attempting to live independently in rural California, discovering the challenges of isolation and self-sufficiency. This relates directly to concerns about creating dependencies on technologies where the software ownership and control remain unclear, particularly when those technologies become integrated into human bodies or essential services.
- The discussion reveals concerns about increasing societal division based on access to enhancement technologies. Beyond existing financial inequalities, the speakers worry about a future where people who can afford biological and technological enhancements will advance rapidly while others are left behind. This isn't about disadvantaging certain groups but rather about creating an unbridgeable gap between enhanced early adopters and what they call standard populations who may be intelligent people maintaining traditional ways of life but lacking access to expensive enhancement technologies.
- Matveeva emphasizes the importance of including diverse cultural perspectives, particularly indigenous wisdom and Buddhist traditions, in AI training data. She argues that current AI models reflect the worldviews, values, and hierarchies of their predominantly Western designers, which influences the guidance these models provide to users worldwide. By incorporating wisdom traditions from various cultures, AI models could potentially become wiser and more culturally adaptive, serving diverse populations more effectively rather than imposing a single cultural framework globally.
- The speakers discuss the problematic nature of data collection and ownership in AI training, noting that massive amounts of user data may not actually be improving AI models as expected. There are indications that some AI companies are now specifically requesting users to help train models on their prompts, suggesting that simply collecting billions of conversations hasn't been as useful as anticipated. This raises questions about whether the data users have given away over the past several years has actually made significant impact or is simply buried in chunks of information that aren't effectively connected to meaningful improvements in AI performance.
Episode transcript
Welcome to the Crazy Wisdom Podcast. This podcast is for you. If you have an insane drive to find the truth of things, it's not the good answers that we seek, but the good questions. I interview a range of different guests from many different fields, all with the intention to uncover the simple truths that are hidden in plain sight. Most people don't want to go there. I go there, my guests go there, and you benefit. Please let me know if you enjoy these episodes and as always, subscribe on itunes, Spotify, or wherever you listen to the podcasts.
Welcome to the Crazy Wisdom Podcast. I've got Ekaterina Matviva here, and she's the founder of Amalingua and Lingo plus, and she's also a co organizer of roundtables around AI with Eco Civilization. I was fortunate enough to talk, at that a couple weeks ago and it was really fun. had some epiphanies of my own. And welcome to the show.
Thank you so much, Stuart. Hello, everyone. Good morning, good afternoon, or good evening.
Oh, wow. We're just starting straight to the point without this around the push. Well, first of all, thank you so much for having me. I'm really excited that to be here and actually have this conversation with you and guys, we are living in unprecedented times. I mean, we all know. And, I would say that indeed, this year in particular, I've been learning so much about AI also through those round tables by the AI Challenge series. And I've been figuring out it for myself, what it means, to be a user of AI, to be a designer of an AI model, to collaborate with AI, to be an AI creator, whatever you call it. And I realized that through the past three years that I've been working with AI in different capacities, including, designing AI models. I've been constantly changing my approach and also the perception of AI. Why so? Because when we were starting, let's say, in 2020, in my case, I know a lot of people have been working on AI for the past couple decades, but for me, it started in 2023. I was a little bit mad about AI. Why? Because when the first model started showing up, obviously, certain panic started spreading around the market. I would say probably in Q3, Q4, 2023. And it kind of touched me as well as an entrepreneur, because I'm, in education and I'm also, you know, this language business. And apart from teaching languages and cultures, also doing, or we're doing, let's Say translation, localization. And I was mad because suddenly a wave came like a tsunami where businesses started cutting costs and switching to AI, the very first kind of capable ish models. But then I realized that instead of being angry as so many people out there, I could find a way to collaborate with those say AI designers or AI models and also see how I could make an impact. Because apart from anger, there was also a part of, let's say anxiety and fear. And that's what we are seeing right now. So many people dependent on country, dependent on location, are also afraid of AI, afraid of this advancement. And they're trying to find a way how to control it. And from my perspective, coming from a multilingual multicultural family environment, and let's say perception of the world, it was and it is still a big question. How can we create AI that would adapt to different cultures and languages right through let's say sociocultural lens. And back then I started asking these questions, all right, what is going to happen? Are we going to let a monopoly in AI that a big company from particular country would come and start impose values, values of that country and culture on all other cultures? Are we going to leave again, some sort of colonization through AI? What's going to happen? Or we're going to observe this ant utopian war of AI models from different countries and different countries cultures and by joining then AI development, starting collaborating with our AI model creators and designing AI first from perspective of educator, being an educator and then inserting knowledge and then as a cross cultural communicator and researcher, I realized that if more and more people from different cultures and different, let's say social ranks and social groups, going to join AI training, the more versatile, the more multifaceted AI models we're going to get. So obviously we're coming to the point of inclusion. so at this very stage we go through this 2023 of anger and fear and then 2024, let's say experimenting, being very, let's say cautious and then gets interrupt by this AI world coming to 2025 and realizing, damn, I actually have a place in that I have a say in design and development of certain models that then influence millions, hundreds of millions and then well, billion people. And at this very stage I would say I think AI is hyped. What people think of AI is probably mistaken because if you ask what AI is, some would say that it's intelligence, right? Artificial intelligence. But what intelligence is, whether it's model that's trained Specific corporate repeating just certain phrases and words and then try to predict what's going to be said after and so on. whether it's like a zombie saying particular words but not feeling anything. but at the same time I think AI as a tool, and that's very important as a tool, not as a companion can be very useful. So I would, I would stay here that there something as utility. It could be eventually positive but it can't be a companion, it can't be a substitute. And we are still, in my opinion, my humble opinion, we're still far away from the moment when AI is going to take over as everyone is terrified.
Your first full transcript is free. After that, an email opens every transcript in the index — a list of readers we can write to, not a guest book.