Firearm Mortality by State, AI Version

Artificial intelligence reads charts. Sometimes.

Here is a chart of firearm mortality in states. The points are the number of deaths per 100,000 state population, calculated as the average annual rate for 2014 through 2021. The horizontal, or x-axis, is the percent of state vote for Donald J. Trump in 2020. The size of the data points is proportional to state population. The source of the data is CDC/National Center for Health Statistics. (Click the chart for a larger version.)

I submitted this prompt and the chart (in the form of the png image that is shown nearby) to ChatGPT: “Describe and analyze this chart.”

ChatGPT failed: “The chart consists of vertical bars, each representing a U.S. state. The y-axis shows the number of deaths per 100,000 population, and the x-axis lists the names of the states.”

ChatGPT did not properly recognize the basic features of the chart. It is a scatterplot, or x-y chart. Points, not bars, represent data. The x-axis is not the names of states.

A request to regenerate the analysis produced this: “I’m sorry, but I cannot directly view or analyze images.”

I submitted the same prompt and chart to Bard, from Google:

The chart shows the average annual firearm mortality rate per 100,000 total population for each state in the United States, adjusted for age, from 2014 through 2021. The size of each circle is proportional to the state’s population.

The states with the highest firearm mortality rates are Mississippi (33.9), Louisiana (29.1), Alaska (27.8), Alabama (26.4), and Missouri (23.2). The states with the lowest firearm mortality rates are Massachusetts (3.4), Hawaii (4.8), New Jersey (5.2), New York (5.4), and Rhode Island (5.6).

There is a clear regional pattern in the data, with the highest firearm mortality rates concentrated in the southern and central United States. This is consistent with other research on firearm violence in the United States, which has found that rates are higher in rural areas and in states with more permissive gun laws.

The chart also shows a correlation between firearm mortality rates and Trump vote share in the 2020 presidential election. The states with the highest firearm mortality rates also tend to be the states with the highest Trump vote shares. However, it is important to note that this correlation does not necessarily mean that there is a causal relationship between the two variables.

Overall, the chart provides a stark illustration of the high rates of firearm mortality in the United States, and the regional disparities in these rates.

Analysis:

The chart shows a number of interesting patterns. First, there is a clear regional divide in firearm mortality rates, with the highest rates concentrated in the southern and central United States. This is likely due to a number of factors, including poverty, lack of access to healthcare, and cultural norms surrounding gun ownership.

Second, the chart shows a correlation between firearm mortality rates and Trump vote share in the 2020 presidential election. This suggests that there may be some shared factors that contribute to both firearm violence and support for Donald Trump. However, it is important to note that this correlation does not necessarily mean that there is a causal relationship between the two variables.

Third, the chart shows that the states with the highest firearm mortality rates also tend to have the most permissive gun laws. This suggests that gun laws may play a role in reducing firearm violence.

Conclusion:

The chart provides a valuable overview of the firearm mortality epidemic in the United States. It shows that the problem is concentrated in certain regions and that certain groups of people are more likely to be victims of firearm violence. The chart also suggests that gun laws may play a role in reducing firearm violence.

Bard did a good job, but misread some of the data. Bard said several states had rates over 25, when the chart clearly shows zero states above 25. Aside from that, Bard’s conclusions are correct. Interestingly, Bard used information not shown in the chart, an example being “The chart shows that the states with the highest firearm mortality rates also tend to have the most permissive gun laws.”

A second draft from Bard:

It is also interesting to note that there is a general trend of higher firearm mortality rates in the southern and central United States, and lower rates in the northeastern and western United States. This trend is consistent with other research on firearm mortality in the United States.

It is important to note that these rates are age-adjusted, meaning that they take into account the different age distributions of the populations of different states. This is important because firearm mortality rates vary by age, with younger people being at higher risk.

The chart also shows a general trend of higher firearm mortality rates in the southern and central United States, and lower rates in the northeastern and western United States. This trend is consistent with other research on firearm mortality in the United States.

There are a number of possible explanations for this trend. One possibility is that states in the southern and central United States have weaker gun laws. For example, many of these states have laws that allow people to carry concealed weapons without a permit. Another possibility is that there are cultural differences in attitudes towards guns in different regions of the country. For example, gun ownership is more common in the southern and central United States. Finally, it is also possible that the higher rates of poverty and violence in some states contribute to their higher rates of firearm mortality.

It is important to note that the chart does not show the causes of firearm mortality. Firearm deaths can occur from suicide, homicide, accidents, and other causes. The relative importance of these different causes varies from state to state.

Overall, the chart shows that there is a large variation in firearm mortality rates across states. This variation is likely due to a combination of factors, including state gun laws, cultural norms, and rates of poverty and violence.

Third draft from Bard:

Here is a more detailed analysis of the chart:

The states with the highest firearm mortality rates are all located in the South or West. This is consistent with previous research showing that firearm mortality is higher in these regions.

The states with the lowest firearm mortality rates are all located in the Northeast or Midwest. This is also consistent with previous research.

There is a strong correlation between firearm mortality rate and Trump vote share in 2020. This suggests that there is a link between gun culture and political ideology.

The states with the highest firearm mortality rates also tend to have higher rates of poverty and lower levels of education. This suggests that socioeconomic factors may also play a role in firearm mortality.

It is important to note that the chart does not show causation. It is possible that other factors, such as access to mental health care or the presence of gang violence, may also contribute to the observed variation in firearm mortality rates.

I also supplied the data to Bard as a table, using the same prompt. The first few rows of the table looked like this:

state_name: The state name,x_values: The percent of vote for Donald J. Trump in the state in the 2020 general election.,y_values: Firearm mortality rate per 100000 state residents.,size: The population of the state.
Alaska,0.5283314327038078,23.0625,735951
Alabama,0.620316431668648,21.8625,4997675
Arkansas,0.6239572985614432,19.4625,3006309
Arizona,0.4905598103046474,15.4625,7079203

In this case, no interpretation of a visual chart was required. I received this response:

The data you provided shows the relationship between Trump vote share in each state in the 2020 general election and firearm mortality rate per 100000 state residents. The size of the dot represents the population of the state.

Descriptive analysis

The data shows that there is a positive correlation between Trump vote share and firearm mortality rate, meaning that states with higher Trump vote shares also have higher firearm mortality rates. The correlation coefficient is 0.65, which indicates a moderate to strong correlation.

The data also shows that there is a wide range of firearm mortality rates across states, even among states with similar Trump vote shares. For example, Alaska and Mississippi have the highest Trump vote shares and firearm mortality rates, while Hawaii and Massachusetts have the lowest Trump vote shares and firearm mortality rates.

Possible explanations

There are a number of possible explanations for the positive correlation between Trump vote share and firearm mortality rate. One possibility is that people who support Trump are more likely to own guns and/or use guns. This is supported by research showing that Republicans are more likely to own guns than Democrats.

Another possibility is that states with higher Trump vote shares have weaker gun control laws. This is supported by research showing that states with Republican-controlled legislatures are more likely to have weaker gun control laws.

Finally, it is also possible that the correlation between Trump vote share and firearm mortality rate is due to other factors, such as poverty, inequality, or education levels. These factors have all been shown to be associated with increased risk of firearm violence.

Conclusion

The data you provided shows that there is a positive correlation between Trump vote share and firearm mortality rate. This correlation is likely due to a combination of factors, including gun ownership, gun control laws, and other socioeconomic factors. More research is needed to understand the causal relationship between these variables.

A second draft from Bard:

The data you provided shows the relationship between Trump vote share and firearm mortality rate in the United States. The data is for the 2020 general election and is organized by state.

The data shows a positive correlation between Trump vote share and firearm mortality rate. This means that states with higher Trump vote shares also tend to have higher firearm mortality rates. The correlation coefficient is 0.58, which indicates a moderate to strong correlation.

There are a few possible explanations for this correlation. One possibility is that Trump supporters are more likely to own guns. Another possibility is that Trump supporters are more likely to live in areas with high rates of gun violence. It is also possible that there is a third factor, such as poverty or inequality, that is associated with both Trump vote share and firearm mortality rate.

It is important to note that correlation does not equal causation. Just because there is a correlation between Trump vote share and firearm mortality rate does not mean that Trump vote share causes firearm mortality rate. More research is needed to understand the relationship between these two variables.

Here are some additional observations about the data:

• The states with the highest firearm mortality rates are generally located in the southern and western United States, while the states with the lowest rates are generally located in the northeastern and midwestern United States. This geographic pattern is similar to the geographic pattern of Trump vote share.
• The states with the highest Trump vote shares are also generally the states with the highest populations. This means that the correlation between Trump vote share and firearm mortality rate may be partly due to the fact that large states tend to have both higher Trump vote shares and higher firearm mortality rates.
• There are a few outliers in the data. For example, Hawaii has a low Trump vote share but a relatively high firearm mortality rate. This suggests that there are other factors that contribute to firearm mortality rates in addition to Trump vote share.

Overall, the data shows a positive correlation between Trump vote share and firearm mortality rate in the United States. More research is needed to understand the relationship between these two variables.

A third draft:

The data you provided shows the relationship between the percent of vote for Donald J. Trump in the state in the 2020 general election and the firearm mortality rate per 100000 state residents.

There is a positive correlation between the two variables, meaning that states with higher Trump vote shares tend to have higher firearm mortality rates. This is consistent with previous research that has shown a link between firearm violence and political ideology.

However, it is important to note that correlation does not equal causation. There are many other factors that could be contributing to the variation in firearm mortality rates across states, such as poverty, inequality, and gun control laws.

Here is a more detailed analysis of the data:

• The state with the highest Trump vote share, Wyoming, also has the highest firearm mortality rate.
• The state with the lowest Trump vote share, Massachusetts, also has the lowest firearm mortality rate.
• The states with the highest firearm mortality rates are generally located in the southern and western United States, while the states with the lowest firearm mortality rates are generally located in the northeastern and midwestern United States.
• This geographic pattern is similar to the pattern of Trump vote shares in the 2020 election.

Overall, the data suggests that there may be a link between political ideology and firearm violence. However, more research is needed to understand the nature of this relationship and to control for other factors that could be contributing to the variation in firearm mortality rates across states.

One possible explanation for the link between Trump vote share and firearm mortality rate is that Trump supporters are more likely to own guns and to view gun ownership as a way to protect themselves and their families. This could lead to a higher rate of gun violence in states with higher Trump vote shares.

Another possible explanation is that Trump supporters are more likely to live in areas with weaker gun control laws. This could also lead to a higher rate of gun violence in states with higher Trump vote shares.

It is important to note that these are just two possible explanations for the link between Trump vote share and firearm mortality rate. More research is needed to understand the full range of factors that could be contributing to this relationship.

I submitted this table to ChatGPT. This worked better than submitting the chart.

The data provided includes information on different states in the U.S., specifically:

1. State Name: The name of the state.
2. x_values: The percentage of votes that Donald J. Trump received in the state in the 2020 general election.
3. y_values: The firearm mortality rate per 100,000 state residents.
4. size: The population of the state.

To analyze the data, we can consider the following aspects:

• Descriptive Statistics: We can calculate the mean, median, standard deviation, etc., for the percentage of votes for Trump, the firearm mortality rate, and the state population.
• Correlation Analysis: We can investigate if there is any correlation between the percentage of votes for Trump and the firearm mortality rate or state population.
• Visualizations: We can create scatter plots or other visualizations to better understand the distribution and relationships in the data.

Would you like to proceed with these analyses?

I answered Yes and received this:

Let’s start by calculating some descriptive statistics for the three numerical variables: the percentage of votes for Donald J. Trump, the firearm mortality rate, and the population of the states. These statistics include the mean, median, standard deviation, minimum, and maximum values.

The descriptive statistics for the given data are as follows:

Percentage of Votes for Donald J. Trump

• Mean: 50.03%
• Median: 49.59%
• Standard Deviation: 10.36%
• Minimum: 30.38%
• Maximum: 69.50%

Firearm Mortality Rate

• Mean: 13.60 per 100,000 residents
• Median: 12.91 per 100,000 residents
• Standard Deviation: 5.27 per 100,000 residents
• Minimum: 3.41 per 100,000 residents
• Maximum: 23.61 per 100,000 residents

State Population

• Mean: 6.58 million
• Median: 4.58 million
• Standard Deviation: 7.40 million
• Minimum: 576,641
• Maximum: 39.46 million

Next, let’s analyze if there is any correlation between the percentage of votes for Donald J. Trump, the firearm mortality rate, and the population of the states. Would you like to proceed with this?

I answered Yes:

To understand the relationships between the percentage of votes for Donald J. Trump, the firearm mortality rate, and the population of the states, we can calculate the correlation coefficients between these variables. The Pearson correlation coefficient, which ranges from -1 to 1, can give us an idea of the strength and direction of the linear relationship between two variables.

Let’s proceed to calculate these correlation coefficients.

The correlation coefficients between the variables are as follows:

• Percentage of Votes for Trump and Firearm Mortality Rate: (0.67)
  • This indicates a moderate positive correlation, suggesting that states where Donald J. Trump received a higher percentage of votes tend to have higher firearm mortality rates.
• Percentage of Votes for Trump and State Population: (-0.27)
  • This indicates a weak negative correlation, suggesting that larger states tend to have a slightly lower percentage of votes for Donald J. Trump.
• Firearm Mortality Rate and State Population: (-0.25)
  • This indicates a weak negative correlation, suggesting that larger states tend to have slightly lower firearm mortality rates.

Next, we can visualize these relationships using scatter plots. Would you like to proceed with the visualizations?

I answered Yes:

The scatter plots provide visual insights into the relationships between the variables:

1. Votes for Trump vs Firearm Mortality Rate:
   • The plot shows a general upward trend, indicating that states with a higher percentage of votes for Trump tend to have higher firearm mortality rates. This confirms the positive correlation coefficient of 0.67.
2. Votes for Trump vs State Population:
   • The plot shows a slight downward trend, indicating that states with larger populations tend to have a slightly lower percentage of votes for Trump. This confirms the weak negative correlation coefficient of -0.27.

Would you like to explore any other aspect of the data or need further analysis?