What does AI ‘think’ of Radical Statistics?

Guest Author: John Bibby

I was doodling with WordPress the other day and noted that it has a new option – “AI paragraph (experimental)”.  Another new option is “AI image (experimental)”. I tried the first option and put “Radical Statistics” as the prompt for an experimental paragraph. After ten seconds, this is what it gave me:

Radical Statistics is a field of study that aims to challenge the status quo and traditional methods of gathering and interpreting data. It is about recognizing the power dynamics that affect the collection of statistics and understanding the impact that data can have on policy decisions and social justice.

At its core, Radical Statistics is about questioning the data that is presented to us and demanding transparency and accountability from those who collect it. It is about recognizing the biases and assumptions that can be hidden in supposedly objective measurements and understanding how these can perpetuate inequality and discrimination.

One key aspect of Radical Statistics is the recognition that data cannot be divorced from the context in which it is collected. It is about recognizing the history and power dynamics that have shaped the way in which data is collected and interpreted, and working to ensure that these do not perpetuate systemic inequalities.

Radical Statistics also recognizes the role that data can play in social change. By providing accurate and meaningful data, we can challenge dominant narratives and create more just and equitable societies. It is about using data as a tool for social change rather than simply accepting it as an objective truth.

Ultimately, Radical Statistics is about changing the way we think about data and its role in society. It is about recognizing the power that data can have and working to ensure that this power is used for good. By challenging traditional methods of gathering and interpreting data, we can create a more just and equitable world for all.

Actually I felt it was rather good. However, surprisingly, it failed to mention the brilliant Radical Statistics organisation. I wonder if that is because its algorithm tells it not to?