Generating Generational Data Activism

enterlifeonline
5 min readJul 27, 2021

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Data Activism (2021)

“Everyone is just a set of numbers that the government has access to. Humanity lies in the interpretation of those numbers.”

Peter Tieryas

CNBC came out with a story that stated, “Rapid digital adoption during the pandemic has accelerated the automation of jobs and worsened underlying ageism, making it harder for mid-career workers to secure roles.” Why?

Survey data revealed 45- to 60-year-olds are the most overlooked employee bracket for the following reasons: reluctance among older workers to try new technologies (38%), an inability to learn new skills (27%), and difficulty in working with other generations (21%).

But I believe there is another problem. The 45- to 60-year-old generation is one of the data creators and technologists who have somehow turned their backs on the data and technology they created. They have been lumped into the political firefight of Trump supporters. They have been lumped into the misinformation generation — not backing beliefs, facts with data. They simply believe things because it was said or broadcasted by those that look like them.

Often when approached by very smart people that vaccines are a way for Fauci to become a billionaire via pharmaceutical companies — I ask them to show me the data. Or when I get told that the US 2020 Presidential Election was rigged and faked — I ask them to show me the data. Or that more police or Caucasians have been injured or killed than those who have been injured or killed by the police — I ask them to show me the data.

In the data’s place, I am sent a podcast link or a YouTube video of a person that claims they are an expert in their specific field. But when I Google the person, it’s a website I have never seen before or a recent Wikipedia page that mirrors the content the person spoke on the podcast or the YouTube video. The person who claims I am wrong compares me to the person in the piece of content.

When I ask again to show me the data, they tell me the data doesn’t exist as it was manufactured by the “snowflake” generation: the young adults of the 2010s (born from 1980–1994), viewed as being less resilient and more prone to taking offence than previous generations.

Or they say the data is too “woke”, as Merriam-Webster dictionary defines as a state of being “aware of and actively attentive to important facts and issues (especially issues of racial and social justice).

Well, call me a snowflake. Call me woke.

I promise I am not upset about being called wrong. I just want to see the data that proves I am wrong. I also want to cross-reference that data against reputable data sources (usually data I have used in the past for other types of forecasting or reporting) to see if the same patterns emerge.

If you believe something, it is your right to believe it. But if you want to change my belief, I need to see the data for myself. No amount of podcast links, YouTube videos, and/or Facebook posts is going to change my mind.

Because anyone can say anything.

0.99948% of statistics can be made up (I just made up that statistic).

To disrupt my belief system with data you need to do the following:

  1. Allow me to download data sources that at least come from HTTPS hosting sites with a valid certificate. Reputable data comes from a reputable website. If they can’t spend the time or money to build a secure website, they can’t be bothered with “real” data.
  2. Next, show me data that is somewhat clean. It doesn’t have to be perfect. But some data that doesn’t contain duplicates, various inconsistencies, keying errors, multiple values of state, nulls, and NaN (not a number).
  3. Your data should show both sides of an argument without trying. If both sides aren’t shown, it means the data is manufactured to lift up a narrative. Noise and outliers — that’s okay. That’s good stuff.
  4. Lastly, show me a sample size of at least 10,000 records. No big data is necessary. But make sure the data is timely and not useless not an observed/measured variable from the year 2008.

Generations need to instead of fighting with manipulated news and misinformation discuss ideas and beliefs with data activism.

Data activism is a specific type of activism that can use the production and collection of digital, volunteered, open data to challenge existing power relations. Data activism uses digital technology and data politically and proactively to foster social change.

The biggest hindrance to Artificial Intelligence is old white man data.

To create true artificial intelligence and machine learning requires building an empathy engine that takes in data from all sexes, all nationalities, all religions, and all sexual preferences. We need all people to generate data to create true forecasts and predictions that create inclusion. As I wrote in a previous piece, artificial intelligence requires emotional intelligence.

Imagine a future where instead of fighting with emotions and memes, people are digging into the data to visualize their points and referencing the data sources they used. Or sharing the statistical models they borrow or create new ones to push forward innovation.

Currently, we are creating a data Amish society of those deliberately separating themselves from the world because they believe the world is a model and fixed to ruin them.

Generating generational data activism means we would bring about data literacy, statistical revolution, manifesting empathy, and understanding regardless of age or background.

Call it data karma.

The angst you put into your data is the angst you create in the world. The more inclusive your data sources — means the more voices speak through the data and the visualizations.

And if you are trying to say something or show an injustice, go find the data.

If it doesn’t exist, create it — but not alone — pull data from those that oppose you and those who support you.

Then whatever you build, share it.

Discuss it. Change it. Build it again. Rebuild it again.

All the while, thank all the developers even those who are not on your side because you are pulling data of two extremes.

Remember creating a happy average between extremes is the joy of all statisticians.

And affinity makes all of us more human.

My humanity is bound up in yours, for we can only be human together.

- Desmond Tutu

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