We didn’t really understand the human heart until the mid 17th century, when engineers developed vacuum pumps to move water out of mines. Anatomists realized that such pumps provided an excellent analogy for what the heart does and how it does it. As technology advanced, we used it to learn about our own biology.
In the 20th century, with the advent of the digital computer, we humans reached a similar conclusion-by-analogy: computers show us how our brains work. In the computer, we see elementary logic, various switches flipping on and off, and memory cells that hold information in its most elemental form – binary digits. Perhaps our brains work the same way.
The brain-as-computer analogy has never been perfect, however. The computer, for instance, has a central processing unit (CPU) that manages pretty much everything. The brain doesn’t appear to have an analogous organ. Rather, human thinking seems to be diffuse and decentralized. Indeed, much of our thinking seems to occur outside our brain; the mind is, apparently, much bigger than the brain. Similarly, we can precisely locate a “memory” in a computer. No such luck with a human brain. Memories are elusive and difficult to pinpoint.
Further, the brain is plastic in ways that computers are not. For instance, a good chunk of our brainpower is given over to visual processing. If I go blind, however, my brain can redeploy that processing power to other tasks. The brain can analyze its own limitations and change its functions in ways that computers can’t.
Given the shortcomings of the brain-as-computer analogy, perhaps it’s time to propose a new analogy. Having absorbed a healthy dose of Daniel Dennett (see here and here), I’d like to propose a simple alternative: the brain functions much like the United Sates of America.
That may sound bizarre but let’s go through the reasoning. First, Dennett points out that brain cells, as living organisms, can have their own agendas in ways that silicon cannot. Yes, brain cells may switch on and off as electricity pulses through them, but they could conceivably do other things as well. Perhaps they can plot and plan. Perhaps they can cooperate – or collude, depending on how you look at it. Perhaps they can aim to do things that are in their best interests, as opposed to the interests of the overall organism.
Second, Dennet notes that all biological creatures descended from single-celled organisms. Once upon a time, single-cell organisms were free to do as they pleased. Some chose to associate with similar organisms to form multi-celled organisms. In doing so, cells started to specialize and create communities with much greater potential. However, they also gave up some of their primordial freedom. They worked not just for themselves but also for the organism as a whole. Perhaps our cells have some “memory” of that primordial freedom and some desire to return to it. Perhaps some of our cells just want to go feral.
And how is this like the United States? The original colonies were free to do as they pleased. When they joined together, they gave up some freedom and created a community with much greater potential. We assume that each state works for the good of the union. But each state also has strong incentives to work for its own good, even if doing so undermines the union. Similarly, each state has a “memory” of its primordial freedom and an inchoate desire to return there. Indeed, states’ rights are jealously guarded.
Let’s assume, for a moment, that we have a microscope as big as the solar system. When we examine the United States, we see 50 cells. Each cell seems to be similar in function and process. We might assume that they always function for the good of the whole. But when we look closer, we see that each cell has its own agenda. Some cells (Texas?) may want to go feral to recapture their primordial freedom. Other cells are jockeying for position and advantage. Some are forming alliances and coalitions with like-minded cells to accomplish their aims. Red cells seem to have different values and processes than blue cells.
Could our brains really be as chaotic as the good old USA? It’s possible. If nothing else, such an analogy frees up our thinking. We’re no longer in a silicon straitjacket. We recognize the possibility that living cells may have complex agendas. We start to see possibilities that we were previously blind to. I would write more but I suspect that some of my neurons have just gone feral.
In his 1984 novel, Neuromancer, that kicked off the cyberpunk wave, William Gibson wrote about a new type of police force. Dubbed the Turing Police, the force was composed of humans charged with the task of controlling non-human intelligence.
Humans had concluded that artificial intelligence – A.I. – would always seek to make itself more intelligent. Starting with advanced intelligence, an A.I. implementation could add new intelligence with startling speed. The more intelligence it added, the faster the pace. The growth of pure intelligence could only accelerate. Humans were no match. A.I. was a mortal threat. The Turing Police had to keep it under control.
Alas, the Turing Police were no match for gangsters, drug runners, body parts dealers, and national militaries. The most threatening A.I. in the novel was “military-grade ice” developed by the Chinese Army. Was Gibson prescient?
If the Turing Police couldn’t control A.I., I wonder if we can. Three years ago, I wrote a brief essay expressing surprise that a computer could grade a college essay better than I could. I thought of grading papers as a messy, fuzzy, subtle task and assumed that no machine could match my superior wit. I was wrong.
But I’m a teacher at heart and I assumed that the future would still need people like me to teach the machines. Again, I was wrong. Here’s a recent article from MIT Technology Review that describes how robots are teaching robots. Indeed, they’re even pooling their knowledge in “robot wikipedias” so they can learn even more quickly. Soon, robots will be able to tune in, turn on, and take over.
So, is there any future for me … or any other knowledge worker? Well, I still think I’m funnier than a robot. But if my new career in standup comedy doesn’t work out, I’m not sure that there’s any real need for me. Or you, for that matter.
That raises an existential question: are humans needed? We’ve traditionally defined “need” based on our ability to produce something. We produced goods and services that made our lives better and, therefore, we were needed. But if machines can produce goods and services more effectively than we can, are we still needed? Perhaps it’s time to re-define why we’re here.
Existential questions are messy and difficult to resolve. (Indeed, maybe it will take A.I. to figure out why we’re here). While we’re debating the issue, we have a narrower problem to solve: the issue of wealth distribution. Traditionally, we’ve used productivity as a rough guide for distributing wealth. The more you produce, the more wealth flows your way. But what if nobody produces anything? How will we parcel out the wealth?
This question has led to the development of a concept that’s now generally known as Universal Basic Income or U.B.I. The idea is simple – the government gives everybody money. It doesn’t depend on need or productivity or performance or fairness or justice. There’s no concept of receiving only what you deserve or what you’ve earned. The government just gives you money.
Is it fair? It depends on how you define fairness. Is it workable? It may be the only workable scheme in an age of abundance driven by intelligent machines. Could a worldwide government administer the scheme evenhandedly? If the government is composed of humans, then I doubt that the scheme would be fair and balanced. On the other hand, if the government were composed of A.I.s, then it might work just fine.
Which is more important: questions or answers?
Being a good systems thinker, I used to think the answer was obvious: answers are more important than questions. You’re given a problem, you pull it apart into its subsystems, you analyze them, and you develop solutions.
But what if you’re analyzing the wrong problem?
I thought about this yesterday when I read a profile of Alejandro Aravena, the Chilean architect who just won the Pritzker Prize. Aravena and his colleagues – as you might imagine – develop some very creative ideas. They do so by focusing on questions rather than answers. (Aravena’s building at the Universidad Católica de Chile is pictured).
In 2010, for instance, Aravena’s firm, Elemental, was selected to help rebuild the city of Constitución after it was hit by an earthquake and tsunami. I would have thought that they would focus on the built environment – buildings, infrastructure, and so on. They’re architects, after all. Isn’t that what architects do?
But Aravena explains it differently:
“We asked the community to identify not the answer, but what was the question,” Mr. Aravena said. This, it turned out, was how to manage rainfall, so the firm designed a forest that could help prevent flooding.
Architects, then, designed a forest instead of a building. If they were thinking about answers rather than questions, they might have missed this altogether.
On a smaller scale, I had a similar experience early in my career when I worked for Solbourne Computer. We build very fast computers – in 1988, Electronics magazine named our high-end machine the computer of the year. Naturally, we positioned our messages around speed, advanced technology, and throughput.
But our early customers were actually buying something else. When we interviewed our first dozen customers, we found that they were all men, in their early thirties, and that they had recently been promoted to replace an executive who had been in place for many years. They bought our computers to mark the changeover from the old regime to the new regime. They were meeting a sociological need as much as a technical need.
When you go to a gas station to fill your car’s tank, you may imagine that you’re buying gasoline. But, as the marketing guru Ted Levitt pointed out long ago, you’re really buying the right to continue driving your car. It’s a different question and a broader perspective and may well lead you to more creative ways to continue driving.
More recently, another marketing guru, Daniel Pink, wrote that products and services “… are far more valuable when your prospect is mistaken, confused or completely clueless about their true problem.” So often our market research focuses on simple questions about obvious problems. The classic question is, “What keeps you up at night?” We identify an obvious problem and then propose a solution. Meanwhile, our competitors are identifying the same problem and proposing their solutions. We’re locked into the same problem space.
But if we step back, look around, dig a little deeper, observe more creatively, and ask non-obvious questions, we may find that the customer actually needs something completely different. Different than what they imagined – or we imagined or our competitors imagined. They may, in fact, need a forest not a building.
Suellen and I love to go to art museums. I like to look at the art. I also like to observe people looking at the art. Here’s a basic truth: nobody smiles while looking at art in art museums. Ever. It’s just not done.
Why would that be? Is art really so serious that we can’t smile at it or about it? Is it acceptable for an artist to give us a nudge and a wink and let us in on a good joke? Some very serious literature can also make us laugh out loud. Couldn’t visual art do the same?
I’ve been worried about this for some time now. Here are my best guesses as to why we behave the way we do.
Art is hierarchical – artists profess to know something – or see something – that’s worth knowing. Further, artists profess to know something that the rest of us don’t. They present their ideas to us in museums. Since they know more than we do – in at least one domain – we look up to them. We show our respect with a serious demeanor.
Art museums are the new cathedrals – in centuries past, architects designed cathedrals to project power, wealth, and ineffable spiritual connections. Today, art museums serve the same function. Great architects used to design cathedrals; today they design art museums. You wouldn’t smile in a cathedral, would you?
Social imitation – we see that other people in art museums look very serious, so we assume that we should be serious, too. They see us being serious, so they assume they should be serious, too. With this in mind, I smiled continuously for 15 minutes in a very crowded Whitney museum. I got a few nervous glances but didn’t really have much impact. Perhaps we should organize smiling flash mobs to visit art museums. That might cheer things up a bit.
Museum mind – I enter a museum with a great deal of curiosity. I want to see things and learn things. Then, within a few minutes of entering, I see something that knocks my socks off. It captures my imagination and hangs on. My mind is preoccupied with the amazing thing I just saw. My eyes are seeing but my mind is not. With no new stimulus, my face goes blank. It’s not that I’m serious. I’m stunned.
We don’t get it – maybe we just don’t understand what we’re looking at. We keep looking for meaning when meaning is beside the point. We’re confused. And confused people don’t smile.
I enjoy going to art museums. I enjoy the art and the people watching. But I wish we wouldn’t be quite so serious about it all. It feels like going to church. I’d rather have it feel like fun. What about you?
I hate to admit it, but I may have spent my years in the software business looking through the wrong end of the telescope. I worked for sophisticated technology companies. Quite often, the fundamental question that animated us was, “What more can we do with all this great technology?”
As today’s technology companies (even IBM) are discovering, good design starts at the opposite end of the telescope: with user needs. Indeed, we may even need to discover user needs that users aren’t aware of. The trend is generally lumped under the terms, design thinking or design-oriented culture.
So how does one create a design-oriented culture? Here are some thoughts I’ve culled from recent readings.
It’s about the experience – the central question is simple: what do customers really need? Too often however, we add a limiting clause to the question: what do customers really need from us? Rather than focusing on the complete user experience, we ask a more self-centered question: How can we get customers to want more of what we have to offer?
Design thinking broadens the frame. Rather than thinking only about what we have to offer, we might think about how users acquire the product, how they learn to use it, and what ancillary products they might need to make the product useful.
McKinsey offers up two examples: 1) HP doesn’t just wait for you to order new ink cartridges. They monitor your use and send you cartridges before you even know you need them. 2) John Deere doesn’t just sell tractors anymore. They also offer,”… digital services such as crop advisories, weather alerts, planting prescriptions, and seeding-population advice.”
It’s about making sense – Jon Kolko in Harvard Business Review, argues that technologies and systems (think of our healthcare system) are so complicated today that people just can’t make sense of them. Good designs should address this. I find, for instance, that Turbo Tax addresses a complex issue and, in Kolko’s terminology, makes it “simple, intuitive, and pleasurable.” In other words, it’s well designed. Imagine if we could make buying health insurance equally simple, intuitive, and pleasurable.
It’s about prototypes – I remember introducing new products with a “big reveal”. We developed the products in secret. We couldn’t talk to customers about them – that would be selling futures. We built some buzz and, when everything was ready, we popped the new product out of the box. Sometimes the big reveal worked great. Sometimes not.
Kolko argues that design-cultures are much more interested in prototyping their ideas all along the development path. Kolko writes that, “The habit of publicly displaying rough prototypes hints at an open-minded culture, one that values exploration and experimentation over rule following.”
It’s about emotions – software seems like the ultimately rational product. Buying software should be rational as well – the product with the most features should always win.
Alas, it’s just not true. Indeed, the software industry has much more in common with the fashion industry than one might imagine. It’s not just what the software does. It’s how it makes you feel as it’s doing it. If it does the job but makes you feel stupid, it’s not well designed.
(As an aside, I think this is why the Lars Lawson cartoon character worked well for Lawson Software. Lars touched on our emotions – something quite unusual for B2B software).
It’s about thinking – as Lawton Ursrey notes in Forbes: “Design thinking combines creative and critical thinking that allows information and ideas to be organized, decisions to be made, situations to be improved, and knowledge to be gained.”
At the simplest level, design thinking means doing an about-face. Rather than facing inward, we turn around and face outward. We send our employees outside and bring our customers inside. It’s about attitude more than anything else. Unfortunately, attitudes are very hard to redesign.