## [Why transformative artificial intelligence is really, really hard to achieve](https://thegradient.pub/why-transformative-artificial-intelligence-is-really-really-hard-to-achieve/): > Yet many people are optimistic that artificial intelligence is up to the job. AI is different from prior technologies, they say, because it is _generally capable_—able to perform a much wider range of tasks than previous technologies, including the process of innovation itself. Some think it could lead to a “[Moore’s Law for everything](https://moores.samaltman.com/),” or even risks on [on par with those of pandemics and nuclear war](https://www.safe.ai/statement-on-ai-risk). Sam Altman shocked investors when he said that OpenAI would become profitable by first inventing general AI, and then [asking it how to make money](https://youtu.be/ebjkD1Om4uw?t=355). Demis Hassabis described DeepMind’s mission at Britain’s Royal Academy four years ago in two steps: “[1. Solve Intelligence. 2. Use it to solve everything else.](https://youtu.be/d-bvsJWmqlc?t=203)” > **If it could automate the process of innovation** itself, [some economic growth models](http://dxie.people.ust.hk/OnlineMacro/jonesjpe1995.pdf) predict that GDP growth would not just break three percent per capita per year—it would accelerate. Bold assumption. If I could turn water into wine wouldn't that change things as well? If we could master transmutation wouldn't that change things? #### Constraints >Such a world is hard to achieve. As the economist William Baumol [first](https://pages.stern.nyu.edu/~wbaumol/OnThePerformingArtsTheAnatomyOfTheirEcoProbs.pdf) [noted](https://www.jstor.org/stable/1812111) in the 1960s, productivity growth that is unbalanced may be constrained by the weakest sector. To illustrate this, consider a simple economy with two sectors, writing think-pieces and constructing buildings. Imagine that AI speeds up writing but not construction. Productivity increases and the economy grows. However, a think-piece is not a good substitute for a new building. So if the economy still demands what AI does not improve, like construction, those sectors become relatively more valuable and eat into the gains from writing. A 100x boost to writing speed may only lead to a 2x boost to the size of the economy. > Our point is that the idea of bottlenecking—featured everywhere from Baumol in the sixties to Matt Clancy today—deserves more airtime.[[5]](https://thegradient.pub/why-transformative-artificial-intelligence-is-really-really-hard-to-achieve/#fn5) It makes clear why the hurdles to AI progress are _stronger together than they are apart_. AI must transform all essential economic sectors and steps of the innovation process, not just some of them. Otherwise, the chance that we should view AI as similar to past inventions goes up. > > Perhaps the discourse has lacked specific illustrations of hard-to-improve steps in production and innovation. Fortunately many examples exist. #### Transformative AI is unlikely [Transformative AGI by 2043 is <1% likely](https://arxiv.org/pdf/2306.02519.pdf) ## [Moore's Law for Everything](https://moores.samaltman.com/) > In the next five years, computer programs that can think will read legal documents and give medical advice. In the next decade, they will do assembly-line work and maybe even become companions. And in the decades after that, they will do almost everything, **including making new scientific discoveries that will expand our concept of “everything.”** Emphasis above is mine. I strongly disagree with this, *unless* we come up with fundamentally better explanations of creativity and how science is done. > 1. This revolution will create phenomenal wealth. The price of many kinds of labor (which drives the costs of goods and services) will fall toward zero once sufficiently powerful AI “joins the workforce.” > The technological progress we make in the next 100 years will be far larger than all we’ve made since we first controlled fire and invented the wheel. We have already built AI systems that can learn and do useful things. They are still primitive, but the *trendlines* are clear. This essay is riddled with prophesy. Trend lines are only guiding factors at best. --- Date: 20230708 Links to: Tags: References: * []()