Some folks think "Objective reality exists" is a good counterargument to "Science is socially constructed". It's not and here's why ...
The more I argue with folks about how "science is socially constructed", the more obvious it is to me that the people disagreeing with me are simply saying "Objective reality exists" (which I agree with but they seem to think I don't.)
Over and over again, they restate that reality is indeed real. Although this requires philosophical arguments to defend, they tend not to make any. Perhaps this is because messing with philosophy is how we get statements like "science is socially constructed" in the first place.
Often people resort to threats. What if you jump off a building? What if your boss fires you? What if your bridge collapses or your plane crashes? They seem to be saying "I'm very scared of this and I'm sure you are too! Why would we be so scared if reality didn't exist?"
This is not a good argument. What if I'm not easily scared? What if I'm overly anxious and inclined to irrational fears? Even if I agree that logically, one ought to fear falling out of an airplane, it doesn't prove anything other than we share subjective beliefs.
Of course, at the end of the day, I do think objective reality exists but my best guess as to the nature of that objective reality differs from yours. For instance, in my reality, science is socially constructed and if you're disagreeing with me then it's not in yours.
If you're not making use of philosophical arguments then your sense of objective reality is more of a strongly held intuition. Perhaps you once experienced a bridge collapse and you were very convinced by the experience. I've had similar experiences and so I share the intuition!
The question for me isn't whether objective reality exists. The question is how do we get at it given that our individual experience is subjective. My answer is in part by comparing our individual sense of reality and triangulating.
Social construction is thus an extremely important part of generating knowledge in science. We use triangulation between our differing perceptions and inferences to create a shared truth.
"Social" because the interaction with and understanding of the contents of the minds of others is critical to the process of knowledge creation.
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You may have heard hallucinations are a big problem in AI, that they make stuff up that sounds very convincing, but isn't real.
Hallucinations aren't the real issue. The real issue is Exact vs Approximate, and it's a much, much bigger problem.
When you fit a curve to data, you have choices.
You can force it to pass through every point, or you can approximate the overall shape of the points without hitting any single point exactly.
When it comes to AI, there's a similar choice.
These models are built to match the shape of language. In any given context, the model can either produce exactly the text it was trained on, or it can produce text that's close but not identical
I’m deeply skeptical of the AI hype because I’ve seen this all before. I’ve watched Silicon Valley chase the dream of easy money from data over and over again, and they always hit a wall.
Story time.
First it was big data. The claim was that if you just piled up enough data, the answers would be so obvious that even the dumbest algorithm or biggest idiot could see them.
Models were an afterthought. People laughed at you if you said the details mattered.
Unsurprisingly, it didn't work out.
Next came data scientists. The idea was simple: hire smart science PhDs, point them at your pile of data, wait for the monetizable insights to roll in.
As a statistician, this is extremely alarming. I’ve spent years thinking about the ethical principles that guide data analysis. Here are a few that feel most urgent:
RESPECT AUTONOMY
Collect data only with meaningful consent. People deserve control over how their information is used.
Example: If you're studying mobile app behavior, don’t log GPS location unless users explicitly opt in and understand the implications.
DO NO HARM
Anticipate and prevent harm, including breaches of privacy and stigmatization.
Example: If 100% of a small town tests positive for HIV, reporting that stat would violate privacy. Aggregating to the county level protects individuals while keeping the data useful.
Hot take: Students using chatgpt to cheat are just following the system’s logic to its natural conclusion, a system that treats learning as a series of hoops to jump through, not a path to becoming more fully oneself.
The tragedy is that teachers and students actually want the same thing, for the student to grow in capability and agency, but school pits them against each other, turning learning into compliance and grading into surveillance.
Properly understood, passing up a real chance to learn is like skipping out on great sex or premium ice cream. One could but why would one want to?
If you think about how statistics works it’s extremely obvious why a model built on purely statistical patterns would “hallucinate”. Explanation in next tweet.
Very simply, statistics is about taking two points you know exist and drawing a line between them, basically completing patterns.
Sometimes that middle point is something that exists in the physical world, sometimes it’s something that could potentially exist, but doesn’t.
Imagine an algorithm that could predict what a couple’s kids might look like. How’s the algorithm supposed to know if one of those kids it predicted actually exists or not?
The child’s existence has no logical relationship to the genomics data the algorithm has available.