Part 3: Design Talk — With Don Norman

Insights from Design4India’s Design Talk, a podcast series with thought leaders of design.

This is Part 3 of the series if you haven’t read the previous ones,

Part 1: Design Talk — With Don Norman.

“A lot of times, people don’t know what they want until you show it to them”

How do you apply this thinking to create great user experiences that change the very economics, often industries to create habit-forming experiences.

When you ask people what they want, they will take a look at their lives and they will see where they’re having trouble with their lives and they’ll say, I really wish that we could do this differently or we could do this faster or we could do this easier or whatever.

If you go to a city where there aren’t enough taxis and ask people “so what should we do?” People would say, well, we should allow the city to issue more taxi licenses so we have more chances and more available for people. Well, that’s not how Uber solved the problem. The problem is saying that does not legislate. Let’s just say anybody can pick up somebody, all you have to do is make the call. There’ll be a service that connects you to the closest available person, but we also make sure that the people are pretty good. So Uber, first of all, collect statistics about which are the good drivers and the not so good drivers but for the passengers too, they won’t pick up the bad passengers like they won’t allow the bad drivers.

All you have to do is step back, understand “What is the real problem we are facing” and solve that. And that’s how you create a great user experience that changes the very economics of an industry creating new business models.

The famous Steve Jobs quote, “A lot of times, people don’t know what they want until you show it to them” was adopted from Henry Ford who made the first mass-produced, automobiles. He said, “If I asked people what they want, they would say they want faster horses”. But the automobiles when they first came out were slower than horses.

Designing for peoples trust in offline and online experiences

The amount of trust varies with the culture. It really depends upon your past experience. But the press plays a large part because they tell us about the rare problems, not about the common problems. The common problem is that, We can trust the systems, the rare problems is somebody stealing all your stuff, but they only write about the stealing and so we think that it’s worse than it is, but it’s also made us more cautious and basically we’re going to need a whole different system because we do not trust the internet anymore. Nor should we.

Private information is really not a safe thing anymore. So to overcome that we have to actually change the Internet because the Internet was designed on the assumption that all people are good back in the 1960’s when it was just starting, it was really based on the fact that people like to work with each other but they never imagined that it would be used by every country in the world, so there are major problems that are difficult to overcome.

https://electrek.co

Let’s take automobiles that drive by themselves. How can we learn to trust them? There are two problems here, One is you don’t trust it enough to actually keep yourself as healthy as you should or you may not take advantage of safety features, but the other half is over trust. You may trust it too much and there have been several deaths in the United States when people thought that their cars were completely automatic and autonomous and they didn’t have to pay any attention anymore. Well, that’s not true with any car yet, and so they died. So developing trust and maintaining it is one of the most complex problems that we’re facing. No, it’s not a technology problem. It’s a social problem.

Building platforms and marketplaces that benefit people, society and communities.

In the world, there have been major revolutions that completely changed cultures, the development of sailing ships that went all around the world. and the development of the steam engine, which for the first time we now had a reliable source of power and then eventually the ability to put their scene engine on a platform, namely a train allowed transportation of goods over long distances, fairly inexpensively, was used to be done only by horse or by water, by canals and rivers and the development of the electricity, the Telegraph which allowed people to signal messages all across the country and even across the oceans. Then, of course, the telephone which allowed even better communication. These were dramatic in every way.

We were changing the world today too but a bit in business models, but actually the invention of money is probably the biggest invention and the invention of a common way of dealing with currencies across the world countries so that there was a standard way of deciding how much money of one country is worth in another country. That was a pretty major innovation took a long time but truly creating value never before seen, but in part, because capitalism has destroyed it over.

Many people now are not interested in the benefits or what it does for people or society or communities. They’re interested only in the money and they will destroy communities if they have to, as long as they get a profit. There are traders who would buy something in a few nanoseconds and sell it a few nanoseconds later because if they do that they can make a 10 per cent in buying and selling and they’re selling millions and millions of objects and they can do this many times an hour and they make a huge amount of money and they offer no value to the world. It is pure greed, that’s a problem and it’s really a bad model.

But there are some of the ground up, the new bottom-up kind of businesses that are happening by creating new ways of trading and creating business opportunities to get away from these universal powerful people who have money and sort of dictate what one should do and good ones are really concerned about helping the company succeed, since some really good ideas might take time to actually work. Even if a company fails it really means that you can understand the issues and the problems so you can build a successful one later.

Algorithms replacing people

Our understanding of people, conversations and interactions are far too limited and we do not have an artificial system that can really engage in a conversation remembering the past, understanding the context and then helping with the problem , but on the other hand, people who answer these systems don’t really understand the systems very deeply that they’re helping with.These people often have scripts which in some senses is an algorithm. When people ask them questions and they quickly go through their scripts to find the one that matches and then they ask you questions in return. It’s often really stupid and upsetting. Even if you explain in great detail exactly everything you did and what problems you have found out and they will start with the basic questions like “Is it plugged in”. So the algorithm or the people that are being placed are not that good either.

And that’s why if you have anything that’s unusual, you have to move up to a higher level of support and of course, that’s what the algorithms will do too. So the new algorithms are not impressive in decision making today but they’re really good at recognizing patterns. They can’t answer everyday questions. But they’re really good at some things so if they are coupled with humans they are going to be superior, but the notion that the algorithms today can replace people, they might replace people for the very simple problems but not for the complex ones.

The combination of an algorithm and humans works because a lot of people are really good at figuring out what the real issue is and finding out innovative answers. But one thing people are not good at is understanding the huge manuals, the financial systems, the rules and regulations that are so complex. No single person can fully understand, but the machines can. So people can work with the machines to understand issues and when they don’t have an answer, they can formulate questions in a way the machine, algorithms can guide them. The combination would be powerful. That’s where we’re going especially in medicine where there are very powerful diagnostic systems, which we don’t trust them yet. Even though they’re very good but when they make a mistake they don’t know it. Whereas a doctor, when he makes an error usually knows he/she wasn’t really certain.

This is part 3/3 of the series of insights from Design4India’s Design Talk with Don Norman.

In case if you have missed other two,

Part 1: Design Talk — With Don Norman

Part 2: Design Talk — With Don Norman

‘For more podcasts and expert talks on Design, please visit https://design4india.in/'

I write about things I learn, discover, hear about design and tools here at https://siddarth.design/