AURORA INSIGHTS
AURORA INSIGHTS
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Never Neutral: How Anthropology Can Shape the Future of AI
AI is a cultural force, deeply intertwined with the human experience. Despite decades of technological advancements, one constant remains—humans and the cultures they bring.
Drawing on the groundbreaking research of Dr. Diana E. Forsythe1, an anthropologist who studied AI labs in the 1980s and 1990s, this article explores how cultural and social dynamics shape AI development and why anthropology is essential for creating better, more inclusive systems.
Introducing the Human Collective Intelligence Alignment Problem: Say Hi to HI
We must remember that just as AI is not alone in the universe, neither are we.
We are all part of a human collective superintelligence that, whilst far greater than our own, depends on the intelligence, agency and values of us all.
Youth Safety and AI: Preparing for the AI Revolution
Most teenagers admit that they use AI to help them with their homework, which has raised a lot of concern from parents and teachers about how they are learning.
In light of all this, we must ask ourselves a crucial question—how are we preparing our youth for a future dominated by AI?
Evaluating Low-Risk AI Systems: A Responsible Adoption Approach
Among its various branches, generative AI stands out for its ability to empower organizations and individuals in daily tasks. The integration of AI across diverse functions is becoming standard practice, with enterprise adoption significantly influencing its acceptability. Approximately 85% of AI systems are anticipated to be classified as low-risk or no-risk, yet trust in these systems remains a critical challenge.
DeepSeek: Smaller, Cheaper, Better?
With the cost of over $100 Million for training GPT-4, not many enterprises can compete at this budget level. But what if there was a model that cost under $6 Million to train that matches GPT-4o’s performance? Enter: DeepSeek.
Dreamscapes & PNGS: Why AI Art Feels Like a Portal to Forgotten Dreams
The Earth without ART is just EH. Generative AI proves that artistry lives in all of us, waiting to be unlocked. Because let’s be real, there’s no better feeling than looking at something and saying, “Yeah, I made that.”
Building in Mid-Air: 2024 In Review with Catherine McMillan and Noah Frank
In Boston, over coffee and whiteboards, we decided to act. This year, that action took form in our Aurix’s first major experiment: Aurora Insights. We are pleased at how this medium has truly become a space amplifying emerging voices at the cutting edge of AI research, governance, and strategy, featuring contributions on ethical AI frameworks and innovative applications in education and healthcare. Thank you to all who made this possible!
Synthetic Data and Privacy: The AI Glow-Up We’ve All Been Waiting For
Synthetic data isn’t always sunshine and rainbows. If the real data used to generate synthetic versions has biases (like hiring patterns that favor certain groups), those bad notions might sneak into the AI’s synthetic learnings. So, we have to ask: Are we bias-proofing these systems?
Regulating AI Not by Fear, but for Common Sense
Many believe that artificial intelligence should not be regulated, fearing it would lead to government censorship. I disagree. While it's true that humans, even in judicial bodies, can make mistakes that harm others, machines are not exempt from this. On the contrary, automated learning systems often inherit biases from their human creators.
What’s Next for AI? 3 Policy Moves Expected from Trump’s Return
In this special edition of Aurora Insights, we explore the possible future of AI regulation in the U.S. by tracing back to Trump’s first term for clues on what might come next.
Big Tech in The White House, a Step or a Leap in the Right Direction?
Big Tech has a problem. In fact, Big Tech has multiple problems. With regulators implementing compliance rules that offer limited data privacy, outsourcing content moderation overseas, and cybercriminal activity on platforms like Telegram remaining rampant, the tech sector has a lot of room for growth when addressing digitally-based sexual violence and exploitation.
Pricing LLMS: The True Cost of Compute
After browsing through the technical paper of Llama 3.1, I came to the conclusion that LLMs are “Larege Luxury Models.” The cost to train these models has increased exponentially over the years and the performance seems to be peaking, it raises the question: is there a more efficient way forward for LLM innovation?
Writing Still Matters
The piece you are currently reading was entirely created by a human. I’m not a betting woman, but I’m willing to bet that you can tell, from these first few sentences, that what you’re reading has not been AI-generated. Humans speak and write with accents. So does AI.
The Balancing Act: Collective Learning in the Age of AI
Over the weekend, I finished Thomas Malone’s landmark Superminds, a deep exploration of collective intelligence in today’s AI-driven landscape. Even though the book was released a few years ago, its core insights around collective intelligence, AI, and organizational dynamics are nothing if not prescient today.