How to Ensure AI Models Reflect the Richness of Human Diversity

Author(s): John Loewen, PhD

Originally published on Towards AI.

Insights from bridging data science and cultural understanding
Dall-E image:impressionist painting interpretation of a herring boat on the open ocean

At my core I am a numbers guy, a computer scientist by trade, fascinated by data and what information can be gleaned from it.

I invest (some would say waste) my time poring over all kinds of numbers, from R values to 7-day rolling averages.

I am fascinated by websites like fivethirtyeight.com, — I spent hours glued to their polling and predictive statistics leading up to the 2016 and 2020 US elections (boy, they sure got it wrong in 2016, eh?).

Isn’t AI just great for this sort of analysis? Through complex algorithms, AI can provide predictive analysis in a multitude of domains — crunching data sets to predict outcomes, from elections to education, from weather to wearables.

But is it great for everyone? Learning requires data — and who’s data is it anyways? And who’s model is crunching the data?

Some feel AI can solve all our problems, robots can do everything for us — they may take over the world but it’s worth the risk!

AI facilitates decision making based on quantitative data, most often on a dataset devised by scientists.

I am one of those scientists who works on datasets. I have worked… Read the full blog for free on Medium.

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Published via Towards AI