Future of cities, technology and society: now what?

I haven’t sent out this newsletter since November - I wasn’t sure what to talk about next. I felt others were doing a better job talking about cities, mobility, technology and privacy. And now things have changed.

One thing is for sure though: we live in a time of rapid change, and technology + the move into cities will keep accelerating this.

More to come soon.

Stay safe,

🚗 How to design the UX of a driverless car

And how to imagine a better future.

google search autofill suggestions for "analytics as"

We are learning that many sensible and proven improvements that aren’t implemented for a fear of backlash very quickly become the new and better normal, and nobody wants to go back.

If you’re designing driverless cars, it would be a great team trip to visit a few bicycle friendly cities and study the micro interactions between car drivers, bicyclists, pedestrians. And then think about how your car will interact with the world. This is hard to appreciate if you’ve never experienced it.

Lower maximum speeds. It works. There was a protest against lowering speeds on highways planned in Holland, but they couldn’t find enough angry drivers to show up.

Also, if you’re interested in designing cities: we’ve learnt you can take the highways out and it’s all good stuff.

Now go read this wonderful essay: a technocratic delusion is eating our future.

As product people, imagining and designing a better future is our job.

Thanks for sharing this on Twitter, and have a great week,


👁 Wait what? "Your face could become your credit card."

That's not the good thing you think it is.

This newsletter has veered much towards the surveillance society and been less about designing better cities, I will work on improving that! Meanwhile, let me know what you enjoy reading about.

I am seeing a lot of thinking/writing around the surveillance society. Much of it focuses on facial recognition technology, which seems like a good place to start.

Amazon’s doorbell is filming you and sharing that with who-knows-who:

In general, we all need to learn more about how to best use “AI”. The constant news about its downsides I think is helpful with that, but we also need thinking about when AI works and is good. Or what to be careful about.

And in our series Easily Understandable Examples of the Surveillance Society:

Tracking people is tempting but should really just be against the law. Else you get things like this:

Or stuff like this, trying to sell us on the advantages of being tracked. “Your face could become your credit card”. That’s not a good thing my friend.

Have a great week,


The algorithmic society

It’s Sunday!

This project is creating a database of police use of facial recognition in the US.

At the same time, the US military is gathering and using biometric data around the world, effectively building a global surveillance system. Not planned, but in action today and for the past years. We can’t assume the Chinese aren’t doing the same. We’re building the surveillance society at breakneck speed.

That weapon is a vast database, packed with millions of images of faces, irises, fingerprints, and DNA data — a biometric dragnet of anyone who has come in contact with the U.S. military abroad. The 7.4 million identities in the database range from suspected terrorists in active military zones to allied soldiers training with U.S. forces.

A significant issue with the algorithmic society we’re building is people’s blind trust in/deference to “the algorithm”. This thread provides an easy-to-understand example:

There’s a lot of work to do. Interesting discussions around what scale means (think Facebook who argues they can’t police things), and that scale needs to be localized:

Technologists need to get their act together and realize technology is now eating the economy and our societies.

Meanwhile, the global south is redefining innovation, this article argues that bottom-up innovation is more user-centered.

And to show how fast the technology continues to evolve, here’s an incredible open source library that separates voices from music tracks.

Have a great week, and as always, if you find this newsletter useful, a tweet sharing https://twopointfour.substack.com/ is incredibly appreciated.


AI: ⚠️ scenes from the future-past.

Welcome to another edition of our newsletter on rapidly evolving technology, and the urbanization of 2.4 billion people in the next 30 years.

If you’re enjoying this, please share https://twopointfour.substack.com/ in a tweet. It is incredibly appreciated and is the best way for more people to find this newsletter.

Techno-centric solutions often forget that we already know what works. Smart City sure, but let’s not forget to build real mobility, spaces for people and affordable housing. Here are some great ideas on affordable (social) housing. The rush to techno-solutions reminds me of the rush to management fads or re-orgs in large enterprises, when they are often not even getting the basics right. Let’s be clear: technology CAN have an outsized positive impact. But don’t just build technology without understanding non-tech solutions.

Scenes from the future: live-streaming on 40+ social platforms to sell clothes:

And scenes from the future-past:

I remember those!

More scenes from the future: can you play this game to make the AI (the algorythm) fairer than a real courtroom judge?

The call to ban facial recognition becomes stronger: here’s the NYT on the topic. If you build products, you should be reading this stuff.

Bus cameras are catching illegally parked cars in NYC. That certainly seems like a healthy use of technology. Note: no face recognition involved.

Should business have values? In the future, that’s a yes. Marc Benioff, who built a $130B business, on how we need a new capitalism. (NYT, paywall.) He *wants* billionaires to be taxed more. Businesses to have values. Here’s a longer non-paywalled interview on Fortune (he has a book out).

How is AI changing society? This is an interesting perspective: some sectors of society are not being AI’d, social sectors and many parts of the governement. The money quote:

What it does mean is that the gap between the sectors of our society is likely to grow to such a size that the sectors that haven’t already undergone a digital transformation — much of the public and social sectors — may literally never be able to catch up.

Machine Learning can totally write perfect articles. It’s exceedingly close today, as this article in the New Yorker shows, partly written by AI. Read it, it is scarily good. What does that mean though? How will this be weaponized for political or financial gains? How will this disrupt how we interact?

Have a great week,


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