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AI explanation

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a TIME magazine cover featuring the bustling Syrian city scene. The cover should depict busy city streets filled with people huddled around glowing computer screens, engrossed in reading Bloomberg Money Stuff articles about cryptocurrency. Meanwhile, the streets are lined with cars, their owners too consumed by virtual currency mining to notice, causing a surge in petroleum consumption. The image should capture the stark and ironic contrast between the digital frenzy and its real-life impact, offering a simple yet powerful visual narrative of both virtual and tangible currency coexisting in the city. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Bloomberg Money Stuff articles about crypto and Petroluem consumption in Syria. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Parallax art a funny image macro Oragami A TIME magazine cover image Art nouveau
ChatGPT: A TIME magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Bloomberg Money Stuff articles about crypto and Petroluem consumption in Syria, in the following situation: The sudden surge in crypto coverage led to a nationwide obsession with mining virtual currencies, causing people to inadvertently leave their real-life engines running, consequently ramping up the demand for petroleum in Syria. Who knew that digital money could rev up the need for fossil fuels in such a tangible way? It's like they say, when it rains crypto, it pours petrol! . Keep the description simple.
ChatGPT: In a bustling Syrian city, people are huddled around their glowing computer screens, consumed by Bloomberg Money Stuff articles about crypto. Meanwhile, outside on the busy streets, car engines hum endlessly as their owners are too engrossed in virtual currency mining to notice, causing a surge in petroleum consumption. The contrast of the digital frenzy and the real-life impact is stark and ironic, as the city becomes a whirlwind of both virtual and tangible currency.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A TIME magazine cover image ] and depicting this scene: In a bustling Syrian city, people are huddled around their glowing computer screens, consumed by Bloomberg Money Stuff articles about crypto. Meanwhile, outside on the busy streets, car engines hum endlessly as their owners are too engrossed in virtual currency mining to notice, causing a surge in petroleum consumption. The contrast of the digital frenzy and the real-life impact is stark and ironic, as the city becomes a whirlwind of both virtual and tangible currency. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a TIME magazine cover featuring the bustling Syrian city scene. The cover should depict busy city streets filled with people huddled around glowing computer screens, engrossed in reading Bloomberg Money Stuff articles about cryptocurrency. Meanwhile, the streets are lined with cars, their owners too consumed by virtual currency mining to notice, causing a surge in petroleum consumption. The image should capture the stark and ironic contrast between the digital frenzy and its real-life impact, offering a simple yet powerful visual narrative of both virtual and tangible currency coexisting in the city.

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*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

AI academic paper

From Petro to Crypto: A Rhyme Between Bloomberg's Line and Syria's Oil and Gas Time The Journal of Energy Economics and Cryptocurrency Studies Jan 2024 Reminder: This paper is AI-generated. Not real!

Problem variable:	Which variable has a problem? Bloomberg Money Stuff articles about crypto Petroluem consumption in Syria Neither / both
Issue:	What is the issue? The data is incorrect The chart isn't displaying properly There is a typo The source link is incorrect A calculation is wrong Something else
Additional details: Optional
Confirm you are a human:

Data details

Why this works

1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
2. Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
   no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
   p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
4. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.
5. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
   Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1,1,2,12,66,19,4,15,])
array_2 = np.array([127.042,122.042,124.036,127.631,160.683,137.867,131.435,131.591,])
array_1_name = "Bloomberg Money Stuff articles about crypto"
array_2_name = "Petroluem consumption in Syria"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

• High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
  
  If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
  
  Alternatively you can use a tool like Inkscape.
  
• High resolution line chart, optimized for mobile
• Alternative high resolution line chart
• Scatterplot
• Portable line chart (png)
• Portable line chart (png), optimized for mobile
• Line chart for only Bloomberg Money Stuff articles about crypto
• Line chart for only Petroluem consumption in Syria
• AI-generated correlation image
• The spurious research paper: From Petro to Crypto: A Rhyme Between Bloomberg's Line and Syria's Oil and Gas Time