There are too many fields in which advances in complex systems modelling will be revolutionary and I frankly don't have the knowledge to describe most those. Let me tell you about my own field, soft condensed matter physics.
A grand aim of soft matter physicists is to be able to describe biology in the quantitative language of physics. However, this is hard: biology is ridiculously complicated. However, as mentioned, we're slowly but surely making consistent progress. Advanced molecular simulation combined with machine learning appears to be an incredibly powerful approach that an entire generation of PhD students have begun to master. This has the add on effect in that it becomes easier to build theories if you have precise numerical undestanding of the physical system you're trying to study: something that simulation provides that traditional experiment doesn't.
Let's get onto the sci-fi. Imagine now that it's the 2050s and we've gotten to a point where the complexity of biology is manageable. Not fully solved: that's not going to happen any time soon. But manageable. At this point we can harness microbiology as an engineering tool. Viruses especially become active materials for construction: this has actually already happened [1], but in an extremely rudimentary way. Viruses are essentially spontaneously self-assembling molecular machines: even having a vague understanding of how they can be engineered promises a nanotechnology revolution. And that's just viruses. Imagine the other players of biology being actively used as tools for humanity: where does that even end?
We're taking our first teeny-tiny steps towards actually developing an understanding of biology in the same way we've developed an undestanding of electronics. We can't do it in the same way because the challenges are so much more tremendous, but we're honestly getting there. Ordinary lives won't so much as be changed for the better - rather, the meaning of "ordinary" life will be changed entirely.
[1] Fischlechner, M. and Donath, E. (2007), Viruses as Building Blocks for Materials and Devices.
A grand aim of soft matter physicists is to be able to describe biology in the quantitative language of physics. However, this is hard: biology is ridiculously complicated. However, as mentioned, we're slowly but surely making consistent progress. Advanced molecular simulation combined with machine learning appears to be an incredibly powerful approach that an entire generation of PhD students have begun to master. This has the add on effect in that it becomes easier to build theories if you have precise numerical undestanding of the physical system you're trying to study: something that simulation provides that traditional experiment doesn't.
Let's get onto the sci-fi. Imagine now that it's the 2050s and we've gotten to a point where the complexity of biology is manageable. Not fully solved: that's not going to happen any time soon. But manageable. At this point we can harness microbiology as an engineering tool. Viruses especially become active materials for construction: this has actually already happened [1], but in an extremely rudimentary way. Viruses are essentially spontaneously self-assembling molecular machines: even having a vague understanding of how they can be engineered promises a nanotechnology revolution. And that's just viruses. Imagine the other players of biology being actively used as tools for humanity: where does that even end?
We're taking our first teeny-tiny steps towards actually developing an understanding of biology in the same way we've developed an undestanding of electronics. We can't do it in the same way because the challenges are so much more tremendous, but we're honestly getting there. Ordinary lives won't so much as be changed for the better - rather, the meaning of "ordinary" life will be changed entirely.
[1] Fischlechner, M. and Donath, E. (2007), Viruses as Building Blocks for Materials and Devices.