Technology is the undisputed champion of efficiency. Tasks that were once complex and time-consuming are now completed in the blink of an eye. But there is a downside to an abundance of technology. In his new book, scholar Edward Tenner explains how too much efficiency can kill creativity, which can turn off avant-garde thinking, innovation and problem-solving. He believes there is a better way to improve our lives through a combination of technology and intuition, and by exploring the random and unexpected.

Tenner, a distinguished scholar at the Lemelson Center for the Study of Invention and Innovation at the Smithsonian, spoke about his book, The Efficiency Paradox: What Big Data Can’t Do, on the Knowledge@Wharton radio show on SiriusXM. (Listen to the podcast at the top of this page.)

An edited transcript of the conversation follows.

Knowlege@Wharton: What’s so terrible about efficiency?

Edward Tenner: The problem with efficiency is that algorithms let us really learn from experience, they let us codify experience, they let us benefit, they recognize patterns. They are really tremendous at that. For example, I use the Google navigation program Waze. I first started out as a critic of it, but then I got into it more and more. However, the problem with Waze is that every once in a while, it will make a terrific blunder. If somebody relies completely on a system like that, no matter how brilliantly engineered, sooner or later some glitch is going to bite back. However, if they keep their awareness of where they are, if they keep their common sense, and if they keep trust in their common sense, then they can get the most of the program while avoiding those little disasters.

Knowlege@Wharton: Because we are so reliant on technology, are we losing something as a society, as a culture?

Tenner: There is definitely that risk, and it happens all of the time because it is so easy to become dependent. It is so easy just to accept what a program is proposing to you and to shut your eyes to other things that might be a little more unusual. But that didn’t really start with technology because people were using pattern recognition and routines for a long time.

For example, look at all of the publishers that turned down the Harry Potter series. Although it had elements from other literary works obviously, it was something so new that it really didn’t fit into the pattern of what publishers thought would be a really successful children’s book. It was only when the 8-year-old daughter of the editor wrote an ecstatic little review of the book that he decided this was the one to buy.

“It is so easy just to accept what a program is proposing to you and to shut your eyes to other things that might be a little more unusual.”

The problem with artificial intelligence is not limited to the technology, it is extended to the tendency that we all have to go on what has been familiar and to ignore the unexpected. To ignore really our ability to recognize something that is really fresh and exciting.

Knowlege@Wharton: You said that efficiency was redefined in the 19th century. What happened then?

Tenner: Yes, the 19th century made a huge difference. Before the 19th century, people were always concerned with managing with the least overhead, getting the most for the least and so forth, but they didn’t really have a doctrine about it. One of the big changes of the 19th century with the rise of the steam engine was that now people were very much concerned with how much work they could get out of a given unit of coal, for example. Which steam engines would let a railroad travel fastest on a given amount of fuel? People started thinking much more systematically about efficiency, and that fed back into business and social thinking more generally.

Knowlege@Wharton: One of the descriptions you use relates efficiency at times to a threat. How so?

Tenner: Efficiency as a threat, I think, appears in a number of ways. If we try to do everything efficiently, then we are turning off the power of serendipity, which relies on our taking a wrong turn occasionally or picking up a book that we hadn’t expected.

In fact, one of my most exciting moments was when John Kennedy Jr., who was editor of George magazine, called me. He had been looking for another book in a bookstore, and he happened to see mine on a different topic. I would have never thought of being a contributor, but he liked the book, so we had lunch and I was able to write a couple of articles for him.

Recently, there has been an article in The New York Times about the declining number of bookstores in New York. So, possibly that bookstore wouldn’t have been there, and I wouldn’t have gotten the call. That led me to see that bookstores are a really great example of an institution that promoted serendipity, and it is important for people to seek out that kind of opportunity.

Knowlege@Wharton: You look at efficiency in different areas, and one of the areas that we have focused on is education. What are your thoughts on how efficiency is affecting our education system?

Tenner: Education naturally fascinates me because I have been involved in it in different connections for most of my life. When I wrote the book, I had not realized that the application of efficiency to education actually goes back to Thomas Edison himself. Edison once said that he thought that textbooks are only 3% efficient. Bill Gates recently said something very similar.

“If we try to do everything efficiently, then we are turning off the power of serendipity.”

Edison thought that an adaptation of his new motion picture system could really jumpstart science education, so he started a company to produce those. He invented a new kind of projector that would be suitable for classrooms, and it was a marketing bomb. The reason for that was that Edison was an absolutely brilliant dropout, and he was able to hire really great technical people. He deserves his reputation as a technical genius. But he had never taught a class and had very limited experience to the system. He didn’t really understand what goes into science education, or education more broadly, so he wasn’t able to market the product. This has been a thread I discovered in most of the programs for making education more efficient through technology. B.F. Skinner, the psychologist, was one of the very few people in the field who actually had taught classes. But even his system of programmed learning was not terribly successful.

I am not saying that technology can’t be valuable in education. It can be extremely valuable, but there is a lot about education that can be improved by what is called desirable difficulty. That means that somebody who is taking notes on a lecture, for example, will learn more if they have to paraphrase the lecturer in longhand than if they can type verbatim on some device with a keyboard. When you are forced to write, when you have that constraint of writing, when you can’t write everything down verbatim, then you are forced to digest for yourself and understand better the major questions of the lecturer. Whereas, when you can just type, you are just typing. It is what psychologists call fluency. And fluency does not necessarily translate into understanding.

Knowlege@Wharton: I have thought about that with my oldest daughter, who is in seventh grade and is allowed to use a calculator for certain elements of learning math instead of actually writing it out and doing it.

Tenner: Calculators can be really great in math. Calculators can reduce the tedious side. But there is a risk that in eliminating steps, you are turning mathematical thinking into a black box. You don’t really understand how the computer got to the subject. I think there needs to be a balance between what students will do mentally and what they are doing with a device.

The interesting thing about the older math culture was the slide rule, because the slide rule was something kind of in between. When I worked in publishing, my first boss, Herb Bailey, who was director of Princeton University Press, would still use a slide rule for a lot of his calculations because he said it let him visualize a range of scenarios. He taught in the military in World War II, so he was from that technological culture. But I think there was a lot in that, and he certainly was a very, very efficient director.

Knowlege@Wharton: Can you talk about the efficiency paradox in terms medicine?

Tenner: There has been a dream of better medicine through information technology, and there are lots of things that computers can do to improve medical outcomes, if only in research. I am very enthusiastic about the possibility of technology in medicine. However, lots of things have had really unexpected outcomes. For example, the electronic medical record has been praised by politicians and leading doctors and administrators as a way to eliminate all of the costly misunderstandings of doctors’ handwritings, to enable the better transfer of patient’s medical records.

In principle, the electronic medical record looks like a really great thing. But the problem is that it shifts a lot of the burden to doctors and their staffs to enter information in a standardized way. There are also all kinds of problems of interoperation of systems, of updating systems. A lot of doctors are complaining about burn out, and there have been a number of articles in medical journals about this. It may just be that we are not doing it right, but the point is that if something like that is not implemented correctly, move for efficiency can lead to less efficiency.

“Fluency does not necessarily translate into understanding.”

Knowlege@Wharton: How we will be able to balance both sides of this efficiency debate?

Tenner: It really depends on people’s own behavior. It is not something that can be decided by policy. If people want to delegate as much as possible of their lives to algorithms, there are lots of companies that will be very happy to do that for you. My book is suggesting that, in addition to using them, we also cultivate other things.

For example, we have a lot of what sociologists and psychologists of technology call tacit knowledge. We know a lot more than we think, things that we can’t articulate that are impossible to build into artificial intelligence systems and yet are essential for everyday living. Consider the meaning of an unfamiliar proverb. A little kid can tell you, for example, what “a stitch in time saves nine” means, because we think metaphorically. It is a natural thing. Someone from another culture can probably tell you what it means. But it is much, much harder for an algorithm to make that jump unless it happens to have programmed into it some database with the meaning of that particular saying. The wonderful thing about human reasoning is that we have this stock of skills and knowledge that we can’t articulate but are there when we need it.

One of the fascinating things about artificial intelligence and computer guidance generally is that when builders of advanced aircrafts are designing the control systems, they don’t entrust anything really crucial to a single computer. They use multiple redundant systems, and those systems are programmed by different people with different hardware and software. The idea is that you can have one system like Waze that makes a glitch, but it is unlikely that a number of independent systems will all be making the same mistake at the same time. That kind of redundancy is one way to avoid some of the problems of artificial intelligence, but it doesn’t get at this element of serendipity, it doesn’t get at the element of surprise. So much of human progress has consisted of people taking that jump from the established patterns and intuitively finding some more interesting ways of thinking.

That is why so many really successful books have originally been turned down or begrudgingly published, like Moby Dick. Moby Dick seemed to be this really weird book that broke all the rules. The original sales were not that great, and an algorithm might have defeated it entirely. But the point was that here was somebody who had a really stunning original vision and was able to express it in a new way that didn’t fit into any of those patterns.

Knowlege@Wharton: How does this concern over efficiency play out with what we have seen recently surrounding social media and data sharing?

Tenner: The problems of social media are that they tend to reinforce what is already there. They tend to build on trends. There have been studies, for example, on how people rate songs. And what they find is that a small difference in a listener’s initial preference can snowball and really distort what people would otherwise think of as the quality of the songs.

There is that bias. But I think there is also the issue that social media, by taking away so much advertising revenue from newspapers and magazines, have also really changed the total media environment and weakened the kind of original reporting and writing that should be the basis of social media. They have kind of undermined themselves.