Five Must-Read Pieces on Automation and Inequality


Photo by Brian Sugden on Unsplash

This week’s selection involves research into demographics, cities, social services, and “raising” better bots

I dedicated this week’s issue of my newsletter, Exponential View, to the ongoing and necessary conversations about inequality and bias in automation processes. Here are five pieces I recommend you read on the topic this week:

1. Research on demographics, automation & inequality

Bain, a consultancy, published results of their research into demographics, automation and inequality, warning of increasing volatility. Interesting and challenging times ahead: “faced with market imbalances and growth-stifling levels of inequality, many societies may reset the government’s role in the marketplace.” EXCELLENT

Labor 2030: The Collision of Demographics, Automation and Inequality

2. How inequality is evolving, and why

Will Denayer: “neoclassical recipes have decreased productivity [and] make investment in new technologies less rewarding.”

How Inequality is Evolving and Why

3. Automation in large vs. small cities

Automation may hit employment levels in smaller cities harder than larger cities. (Academic paper). Large cities just appear to be more resilient because they can support and supervise more specialised jobs, tend to be more innovative and harness the types of people willing to adapt and use emerging know-how.

Small cities face greater impact from automation

4. “Raising” unbiased and respectful bots

Bex vanKoot’s second story in the series on the future of robotics—meaning, humans and robots living together— describes the issues with gendering of artificial intelligence. They also offer practical advice on how to build unbiased bots.

How to “Make” a Woman

5. What does high-tech have to do with criminalising the poor? Increasingly, everything

Interview with Virginia Eubanks about her new book: “My fear is that sometimes these systems act as empathy overrides — that we are allowing these machines to make decisions that are too difficult for us to make as human beings.”

When Criminalizing the Poor Goes High-Tech

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