This is one of his arguments for listening to AI-generated music, studying how computers do maths and…gazing at digitally produced paintings: to understand how advanced machines work at the deepest level, in order to make sure we know everything about the technology that is now built into our lives.
Harris, J. (2019). Could robots make us better humans? The Guardian.
Putting aside the heading that conflates “robots” with “AI” there are several insightful points worth noting in this Guardian interview with Oxford-based mathematician and musician, Marcus du Sautoy. I think it’ll be easiest if I just work through the article and highlight them in the order that they appear.
1. “My PhD students seem to have to spend three years just getting to the point where they understand what’s being asked of them…”: It’s getting increasingly difficult to make advances in a variety of research domains. The low-hanging fruit has been picked and it subsequently takes longer and longer to get to the forefront of knowledge in any particular area. At some point, making progress in any scientific endeavor is going to require so much expertise that no single human being will be able to contribute much to the overall problem.
2. “I have found myself wondering, with the onslaught of new developments in AI, if the job of mathematician will still be available to humans in decades to come. Mathematics is a subject of numbers and logic. Isn’t that what computers do best?”: On top of this, we also need to contend with the idea that advances in AI seem to indicate that some of these systems are able to develop innovations in what we might consider
3. “I think human laziness is a really important part of finding good, new ways to do things…”: Even in domains of knowledge that seem to be dominated by computation, there is hope in the idea that working together, we may be able to develop new solutions to complex problems. Human beings often look for shortcuts when faced with inefficiency or boredom, something that AI-based systems are unlikely to do because they can simply brute force their way through the problem. Perhaps a combination of a human desire to take the path of least resistance, combined with the massive computational resources that an AI could bring to bear, would result in a solution that’s beyond the capacity of either working in isolation.
4. “Whenever I talk about maths and music, people get very angry because they think I’m trying to take the emotion out of it…”: Du Sautoy suggests that what we’re responding to in creative works of art isn’t an innately emotional thing. Rather, there’s a mathematical structure that we recognise first, and the emotion comes later. If that’s true, then there really is nothing in the way of AI-based systems not only creating beautiful art (they already do that) but of creating art that moves us.
5. “We often behave too like machines. We get stuck. I’m probably stuck in my ways of thinking about mathematical problems”: If it’s true that AI-based systems may open us up to new ways of thinking about problems, we may find that working in collaboration with them makes us – perhaps counterintuitively – more human. If we keep asking what it is that makes us human, and let machines take on the tasks that don’t fit into that model, it may provide space for us to expand and develop those things that we believe make us unique. Rather than competing on computation and reason, what if we left those things to machines, and looked instead to find other ways of valuing human capacity?