The anthropomorphization of computers (especially powerful ones) is pretty annoying. A _person used a supercomputer_ to analyze Covid-19, and I’m guessing the theory didn’t just ‘emerge’ from the computer.
1. When a system is very simple, we explain its actions in terms of its properties and external forces acting on it.
2. When it's a medium complexity system, we tend to explain its actions in terms of its design, putting ourselves in the designer's shoes.
3. When it's a complex enough goal-seeking system, we begin to empathise with the system itself, thinking why "it chose" a course of action.
I remember how impressed I was with this classification and how much sense it made in terms of how we're able to understand the world and predict what will happen next.
From this angle, much of modern computer software is clearly in category 3, and it just makes things easier for us to think of it as having a mind of its own.
Quoting from wikipedia "For the simplest vehicles, the motion of the vehicle is directly controlled by some sensors (for example photo cells). Yet the resulting behaviour may appear complex or even intelligent."
Or do we simply fall into the trap the GP described, where once something is complex enough that we don't understand what is going on from a purely mechanical perspective we consider it close enough to human to empathize with it?
A much simpler question can be answered: is it possible to be cruel to an animal? The accepted answer revolves around whether or not you can influence the behavior of the animal (or machine). Crabs naturally hide under rocks. If you shock them when they hide under the rocks they eventually stop hiding under the rocks. Meanwhile a bacteria, by itself, will never learn to associate a stimulus with a condition.
That may capture the capability for thought. There are higher levels past it, like learning to model the behavior of other organisms, and those models eventually turning into a theory of self.
One of the best nuclear astrophysicists I know thinks about stars as entities that want to stay alive -- "I'm running out of hydrogen, what can I burn next?" That approach yields the right phenomenology almost all the time.
https://plato.stanford.edu/entries/intentionality/
"However, in the absence of detailed knowledge of the physical laws that govern the behavior of a physical system, the intentional idiom is a useful stance for predicting a system’s behavior."
When you try to describe a complex or subtle thing concisely, you might find it hard. Even if the system is neither animal nor human, you too might notice yourself reaching for "character with motivations" to describe it.
> Covid-19 is like a burglar who slips in your unlocked second-floor window and starts to ransack your house.
https://www.cs.utexas.edu/users/EWD/transcriptions/EWD10xx/E...
"It is probably more illuminating to go a little bit further back, to the Middle Ages. One of its characteristics was that "reasoning by analogy" was rampant; another characteristic was almost total intellectual stagnation, and we now see why the two go together. A reason for mentioning this is to point out that, by developing a keen ear for unwarranted analogies, one can detect a lot of medieval thinking today."
https://www.cs.utexas.edu/users/EWD/transcriptions/EWD08xx/E...
And the ever-popular
https://www.cs.utexas.edu/users/EWD/transcriptions/EWD12xx/E...
"When we returned from the interview, some more legal professionals had arrived and there was a lively discussion going on. For me the exposure was a cultural shock, instructive, but also rather disorienting. Of course I knew that lawyers are not scientists, yet the atmosphere of a trade school took me by surprise. Of course I knew that lawyers mainly deal with national law, yet I was unprepared for the prevailing parochialism. (Now I come to think of it, the system of common law, based —as it is— on custom and precedent, could very well strengthen this phenomenon.) but the most disorienting thing was that I found myself suddenly submerged in a verbal tradition that was totally foreign to me! They were on the average very verbose —some even repetitive—, they had a tendency to "reason" by analogy and more than once I felt that speakers cared more about the potential influence of their words than about what they actually said. (Are these common professional deformations of the trial lawyer?) I spoke for ten minutes, that is, I tried to do so: after several hours of exposure I no longer knew how to address this crowd."
Why do you believe that?
Theories are attempts to explain the mechanism of something based on the observed data. Given data on patient symptoms and known drugs (ACE inhibitors in this case) and their effects, a computer could easily produce a theory that the disease acted like ACE inhibitors. It'd still take a human to write the program to generate these theories, but a computer could do it.
But what if the data represents ideas?
https://en.wikipedia.org/wiki/Automated_theorem_proving
> Unless the computer is conscious, it can not generate the theory.
Why would you say that consciousness is necessary for theory generation? It isn't for arithmetic, equation solving, natural language processing or image identification, etc.
>But what if the data represents ideas?
Then the computer would still be generating and analyzing data, not processing ideas.
>> Unless the computer is conscious, it can not generate the theory. >Why would you say that consciousness is necessary for theory generation? It isn't for arithmetic, equation solving, natural language processing or image identification, etc.
I think that the conscious analyst/observer is an intrinsic part of theory discovery, in the same way that a computer can not understand Chinese[1].
If the conscious observer is not necessary for a theory to exist, why is the computer necessary either? Certainly the phenomenon and data exist without it?
Arithmetic was deliberately mentioned, you might as well say "Of course a calculator app on your phone isn't _really_ doing arithmetic, the conscious analyst/observer is an intrinsic part of discovering the correct answer, in the same way that a computer can not understand compound interest".
There is a sense in which you are correct, but it is a very uninteresting one. Practical applications of computation follow from ignoring this semantic debate.
I think the fact that a computer can execute a program to compound interest isn’t a particularly novel one or interesting idea to me.
Going back to the original article, I think it was an unnecessary and incorrect anthropromorpiziation to write a computer discovered a theory of disease. Why isn’t my lazy laptop curing diseases?
I think there is a lot of interesting ideas in this semantic area. Can a computer compose all possible melodies and release them into the public domain[1]. If I write a script that formulates and posts every combination of "x variable cures cancer", did the computer or I discover a theory? If no, what are the minimum requirements?
https://www.google.com/amp/s/www.vice.com/amp/en_us/article/...
Yes, you're correct. However, identifying the correlations is a necessary precondition to making a theory about them. And the automated analysis can help with that step.
You might phrase a title that way if you believe that we trust computers more than we trust scientists. Is that true? I don't think so. But if it is, how horrifying.
We evolved in kinship groups. The most important phenomena to understand were your fellow humans, followed by animals.
The human brain has a highly-optimised "Character with motivations taking actions" parser.
"A person used a supercomputer to analyse Covid-19" conveys no more knowledge than "A supercomputer analyzed Covid-19".