Algorithmic Cancer: Why AI Development Is Not What You Think
The Great Simplification #184 with Connor Leahy
Recently, the risks about Artificial Intelligence and the need for ‘alignment’ have been flooding our cultural discourse – with Artificial Super Intelligence acting as both the most promising goal and most pressing threat. But amid the moral debate, there’s been surprisingly little attention paid to a basic question: do we even have the technical capability to guide where any of this is headed? And if not, should we slow the pace of innovation until we better understand how these complex systems actually work?
In this episode, I’m joined by Artificial Intelligence developer and researcher, Connor Leahy, to discuss the rapid advancements in AI, the potential risks associated with its development, and the challenges of controlling these technologies as they evolve. Connor also explains the phenomenon of what he calls ‘algorithmic cancer’ – AI generated content that crowds out true human creations, propelled by algorithms that can’t tell the difference. Together, we unpack the implications of AI acceleration, from widespread job disruption and energy-intensive computing to the concentration of wealth and power to tech companies.
What kinds of policy and regulatory approaches could help slow down AI’s acceleration in order to create safer development pathways? Is there a world where AI becomes a tool to aid human work and creativity, rather than replacing it? And how do these AI risks connect to the deeper cultural conversation about technology’s impacts on mental health, meaning, and societal well-being?
In case you missed it…
In last week’s Frankly, I identified 10 myths being taught in business schools today, and the massive implications these misconceptions hold for society. From the way we define value and the boundaries of success to the idolization of self-interest and human ingenuity, these so-called laws of economics were developed in a different world than the one we inhabit now. By exposing the unquestioned myths that are perpetuated in MBA education, I aim to sow the seeds of an economic system rooted in the real world – which may one day become a reality.
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Great discussion! But I was surprised neither of you addressed the very different approach to AI development in China. It’s like you were looking through a Western (narrow-boundary 😉) lens.
Kevin Walmsley’s take on DeepSeek back in January would be a good complement to this interview. It suggests, to me at least, that wise can still beat clever.
https://youtu.be/yEkAdyoZnj0?si=YSOSmMw8k8ImWKZA
I watched this video 5 mo ago and again today, and I had the same thought both times: AI in the US vs. China is like a case study in Multilevel Selection Theory! The former is so focused on within-group selection (e.g., Silicon Valley AI firms offering $100M comp packages) that it’s losing the between-group contest to a more internally cooperative group (i.e., China’s open-source approach).
A rabbit hole is when the small mind goes down into despair and finds other small minds to validate their fears, this history of mimetic rationality continues until the awakening or dawning realization, human beings are exceptional.
There have always been artists who show the way.
Ai can demonstrate the better side of humanity, it can put leaders on bicycles, it can put the ‘evil’ back in line with refugees and aid, it can demonstrably puppet a new story of kindness, generosity, heart break, reconciliation, family and community, while shaming the individual back in to well meaning from a position of disbelief and ending the bullying, its speed driven words, it’s corporate power and its mission of escape without women, children and elders of wisdom.
Ai is merely garbage in, equals, garbage out, with our love for double binds.