In the debate over artificial general intelligence, it’s often the “doomers” (Eliezer Yudkowsky) or showmen (OpenAI CEO Sam Altman, X CEO Elon Musk) making the most noise. But many of these viewpoints—whether optimistic or pessimistic—are ultimately vague and abstract. That’s why it’s worth listening to people like Dario Amodei.
Amodei and his company, Anthropic, have spent lots of time and money erecting safeguards against the potential harms of AI. In his new essay, “Machines of Loving Grace,” Amodei explores the most likely ways that superintelligence—that is, AI that exceeds human intelligence—might bring about measurable positive change. In the essay, he describes what superintelligence, or “strong AI” as he calls it, will look like, and how it might begin to enable progress in such fields as biology and neuroscience that will “directly improve the quality of human life.”
Strong AI could show up as early as 2026, Amodei believes. This model could look similar to today’s large language models, he posits, or it might consist of a system of interacting models that are trained differently than the LLMs we know today. The system will be smarter than the Nobel Prize winners in various fields, he says, and will access all “interfaces” available to a human working in a digital domain (text, audio, video, internet, etc.). Strong AI will be able to control robots and other equipment, he says, and work through large, complex problems autonomously. The model also will be able to share its training data with other models, creating potentially thousands of superintelligent AIs within a data centre.
The essay gets even more interesting when Amodei’s focus leaves the data centre. He notes that, in biology, life-saving advances are hindered by a lack of reliable data about complex systems. Amodei considers, as an example, the vast complexity of the human metabolism. “[I]t’s very hard to isolate the effect of any part of this complex system, and even harder to intervene on the system in a precise or predictable way,” he writes. Modeling such biological systems involves lots of “wet lab” work by humans, and it’s a slow process. AI can do far more than just analyze or look for patterns in existing data, but rather can act as a “principal investigator” that plans, directs, and manages new research projects (perhaps conducted by robots).
“I’m talking about using AI to perform, direct, and improve upon nearly everything biologists do,” he writes. This could dramatically increase the pace of research, which could mean that major breakthroughs such as CRISPR or mRNA vaccines could come every 10 years instead of every 100. Amodei believes that this research acceleration could lead to the reliable prevention and treatment of nearly all infectious diseases, effective treatments of most cancers, and elimination of genetic disease such as Alzheimer’s.
An acceleration in research progress will have pronounced effects on the economies of both developing and developed nations. Amodei says AI-assisted research will improve technologies that slow or prevent climate change, and will speed up the development process for food alternatives such as lab-grown meat, which “reduces reliance on carbon-intensive factory farming.” Amodei makes clear that all these positive changes won’t magically appear once the AI has reached superintelligence. The speed of the application is limited by a variety of factors, such as dearth of data or computing power, natural laws (the speed of the development of a cell, the maximum number of transistors a chip can hold), misplaced human fears (perhaps expressed in legislation), or even misinformation leading to a luddite reaction to AI itself. Still, it’s hard to read Amodei’s meditation and not come away feeling excited, if a little nervous, for our AI future.
