Strengthening the Connections: Research Innovation and Economic Growth

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Good afternoon. For those of you do not know me, I'm Patricia Beeson. I'm the Provost of the University of Pittsburgh, and it's my pleasure to welcome this year's Provost Lecturer, Dr. Patrick Gallagher. Less then a year ago in November 2009, the United States Senate confirmed Dr. Gallagher to his current post as director of the National Institute for Standards and Technology. Before taking this leadership position at NIST, Dr. Gallagher was the director of the NIST Center for Neutron Research, a national facility for neutron scattering in Gaithersburg, Maryland. I'm especially pleased to introduce Patrick today because this is a return to the University of Pittsburgh for him.

He earned his PhD in physics at Pitt in 1991 and his PhD mentor here was my predecessor, Pitt professor of physics and former Provost, Dr. James Maher. While at Pitt, Patrick worked in an area of soft condensed matter physics known as colloidal suspensions. In other words, he studied mixtures of liquids and solids. These mixtures are common in nature and play a large role in industry, emerging technology, and biomedicine. After earning his PhD, Dr. Gallagher completed a post-doc at Boston University, and in 1993 he joined NIST as an instrument scientist in the NIST Center for Neutron Research.

At NCNR, Dr. Gallagher's research focused on neutron and X-ray instrumentation and studies of systems such as liquids, solids, and gels. For those who know Patrick from his days at Pitt, it's not surprising that throughout his career he's excelled in leadership positions that require a sort of colloidal suspension of scientific expertise, communication skills, and a vision of what science can accomplish. In addition to serving as director of the NCNR from 2004 through 2009, Dr. Gallagher also chaired the Interagency Working Groups on Neutron and Light Source Facilities under the Office of Science and Technology Policy.

In 2006, the United States Department of Commerce awarded Dr. Gallagher a gold medal for his leadership in interagency coordination of policies for the nation's scientific user facilities. As Director of NIST, he leads an institute with a broad mission to advance measurement science and technology. Its work is foundational to the economic vitality of this nation. One good measure of this is the fact that $610 million of the recent stimulus package went to NIST to pay for research, grants, new equipment, and the construction of new facilities and laboratories.

NIST has its hands in everything from the orderly conduct of commerce to the development of new technologies and the advancement of cyber security. These priorities are well reflected in the title of today's talk, "Strengthening the Connections: Research Innovation and Economic Growth." It's my pleasure to welcome Dr. Patrick Gallagher. [APPLAUSE] And I forgot I'm supposed to remind everyone to turn off their cell phones, please.

Patrick Gallagher: Thank you very much. That was a very, very kind introduction. Congratulations to you on your new position. It's very exciting to be back at Pitt. I have to say, it's always more exciting to hear your bio read by somebody else than when you look at it, so I appreciate hearing that. This is also the first time I've given a lecture where I'm underneath Superman, so I'm going to... enjoy this as well. There's a usa-button up here that's supposed to switch screens, so I might ask for someone to help with that.

So let me start by saying, what I'd like to do today is give you a quick overview of NIST and innovation. Before diving into the talk, let me first reminisce a little bit about today. This is the first time I've been back at Pitt in 19 years, so I don't know why it took me so long. My grandfather, who turned 100 this year, lives in Pittsburgh, so I actually visit the city fairly often, and I have no good excuse. But it was delightful today to see so many old friends and teachers and mentors and to be back at a campus that's even more vibrant and exciting than when I was here before. So this has been a big part of my life and it was great to see it in such good shape.

It was particularly delightful to be here and see my old mentor, Jim Maher. Jim, as many of you know, is a great leader himself, was obviously a great teacher and mentor, but what he probably doesn't know, is that he was also a role model for me in looking at his leadership. His quiet, competent, and very high personal integrity that sort of characterizes Jim. And that was, something I looked to very much. So it was great to see him again.

Before getting into innovation, let me quickly give you an overview of NIST. Many of you probably know this, but in case you don't, NIST is one of the country's oldest national laboratories. It was founded in 1901, and it was known up until the late 1980s as the National Bureau of Standards. It was given a responsibility by Congress to generate and develop a national system of measurement and at the time it was first founded, this was probably thought of as being an artifact-based role. We were going to have standard weights and measures and we were going to transport them to the different states so the scales and other devices could be calibrated. It's interesting that from its immediate founding it immediately became a science agency — one of the first deep-science agencies. The first director of NIST actually came, was recruited from, Case Western, working with Michelson.

And so it's quite interesting that those roots came, and the mission really at NIST has not changed. We remain an agency focused on developing and supporting the nation's measurement infrastructure and particularly the measurement infrastructure as used by industry. And it's only become more important as we've become a more technological society. The types of measurements that we do now are much different. We still do fundamental length, time, mass, and other fundamental quantities, but now we're measuring much more difficult things, like how do you measure security performance in a computer system? How do you assess the effectiveness of biological compounds and put a measure on bioactivity, things of that type. So it's become quite interesting.

We are not a large agency; we're about 2800 employees. We have two major campuses; the largest is in Gaithersburg, Maryland. We also have a facility in Boulder, Colorado. What's interesting, at any given time at NIST, of the technical staff working on the campus, only half of them will be federal employees, the other half will be from universities, companies, and other institutions around the world. So we are a very hybrid organization, working with a large number of guest workers, and maybe we'll see many of you joining us as guest staff and guest researchers.

We also have three other programs outside of the laboratory program that was the old National Bureau of Standards. These were added specifically in the late 1980s, and that's the Baldridge Quality, National Quality Program — now called the Baldridge Performance Excellence Program; the Hollings Manufacturing Extension Partnership Program, which works in all 50 states to deliver business services to small and mid-size manufacturers; and the TIP Program, which is a grant program that funds high-risk, high-payoff research to develop breakthrough technologies in areas of critica national need.

And the reason I give you this little introduction is I'm going to talk now about innovation, and one of the things you will see is that NIST is quite different from other federal agencies in that our programs are really designed to sit all across this innovation framework. And that gives us somewhat of a unique set of roles as we look at policy development in innovation. So innovation has become a major policy basis in which we think about R&D activities in the United States. And what's the genesis of that? Well there's probably many to point to, but one of the ones that has driven a lot of recent legislation was catalyzed by a National Academy report that came out about five years ago called Rising Above the Gathering Storm.

And this report basically identified the fact that our economy is increasingly dependent, in fact has been for quite a long time, on the ability to generate new products and services, on our ability to discover and create new technology. In fact, the half of economic growth is probably an underestimate; estimates looking at our more recent economic behavior give much higher values. Our ability to, economic growth is really tied directly to your productivity. Almost all of the positive impact on productivity has come from new technology. It drives our output growth, and it drives high-quality jobs —interesting, particularly in today's environment, something we're very focused on, and something that's recognized broadly in the business community.

The other part of this report, though, was pointing out that as a society that has led technology-driven development for many years, the indicators are not good. Where we appear to be going is not positive. And I'll show you some of that data as we go forward, and this was really a call to action to address systematic issues in U.S. education, particularly in science, technology, engineering, and math; in R&D investments by both the federal government and by industry; and looking at a whole host of issues that would seek to improve our position so we don't fall behind.

Today, I would say that the innovation discussion has been amplified by the recent recession. This is some economic data that plots the change in job growth from the point of a recession. And it shows some historical data, one showing a series of the post-World War II recessions up through the early 1970s and then some subsequent recessions and, of course, you see the deep recession that we are trying to come out of now. And one of the things that you will see, of course, is this recession that we're in, is astonishingly deep. This was, as we all know and feel, this was an enormous job impact. But the other interesting thing is to look where the employment crosses back over zero, and that gives you some estimate of the duration for job recovery in these different recessions. And what you will see is up until the early '70s, the average recovery time was a little less than two years.

And what you see is progressively longer periods of time for the job recovery to take hold. And in fact, economists right now are very focused on how long this job recovery could be for the current recession, and it's not good. And it's data like this that leads a lot of folks to look at whether there are structural issues underneath this and not simply business cycle issues. And, and in fact, that type of thinking was at the heart of the Gathering Storm report as well — that we are seeing structural changes in the way our economy performs that impact our ability to create jobs. And this type of discussion is impacting all the discussions on innovation.

Here's another piece of data that came from the National Science Foundation, specifically looking at the impact of innovation on companies. And one, the way they did it was to look at companies (my laser has died, there it goes) and then look at the amount of R&D activity, so these would be companies with, the number of companies with less then $10 million all the way up to companies with over $100 million in research activity. And then to basicall ask how much innovation in the form of new or significantly improved products or in terms of innovation in process. And this is the data for the companies without any reported R&D activity, and this is the data for the R&D activity above. What you see is a stunning difference in both new product and service generation for the number of companies reporting new products and services that year versus the ones that don't, versus the baseline. And, of course, this is where over 80 percent of the companies are sitting. And then you see the same thing happening on process innovation here.

The problem with the innovation discussion isn't an understanding of how important it is. In fact, I would say one of the things that's really happened from the policy world is there is a pretty strong consensus at this point. It crosses the political divide, and it really permeates, you'll see, depending whether the President's doing it or whether a piece of legislation or whether you're talking to agencies or whether you're even talking about how a university participates in this, there's a pretty strong consensus that our ability as a country to do research and development and its tie to economic performance, is real. The problem, I think, is understanding how that takes place, and at one level the innovation discussion is a bit of a correlation argument. What we're saying is that very good economic outcomes, whether it's economic growth or new jobs, is tied to have the ability to innovate and develop new products and, therefore, for example, our research and development enterprise is critically important to us. And what happens in the middle is something we don't know very well, and that, of course, will impact our ability to respond to it.

The one thing we do know, even at this level of understanding, is who the players are. From a policy world, one of the reasons the innovation argument is so important is it's justifying a major public investment. We agree as a county to make deep investments in R&D because of the public good of, the growth and economic activity, even though this activity is in the private sector. And in fact, if you look at these innovation models, they often flow from the who's participating at the front end with a lot of public-funded entities, to who's allowed to participate at the other end, where it's really private funding. And you're going to see how this impacts our ability to do things in the middle.

So here's an example. The linear model of innovation is one that Vannevar Bush, I think, is credited in some circles for coming up with this, and it's one we've probably all seen where you start with basic research, then you do applied research, and then it's development. Then you go into production and then you have sales and marketing. And the gist of it from the policy world is that the federal government will support basic research and, in fact, a lot of applied research, and then it expects industry to pickup the activity when you're into development and production. And in fact, it has defined how we have built our agencies and our programs.

The exception to this, when you allow the federal government to go deeper down this path, is when there's an overriding public need. National defense: we allow the Defense Department to go very deep into this process because it's an overriding national goal. Energy technology: you'll see a mission agency that takes energy technology and we're allowed to go much farther down this path. Space program: the space exploration; we were able to take this technology very far. So what we have is this, at a general level we're comfortable with basic R&D investments, and when there's this overriding national need, we're comfortable taking this farther.

I may come back and explain how that actually leads to a very poor optimization of our R&D investments if you look at it from a purely economic perspective. The other thing we can do without understanding what's in that cloudy innovation process is we can at least identify the players, the moving parts. You can look at who's doing activities. The government clearly has a role. Universities play a major role in this process. Industries play a major role in this process. The investment community plays a major role in this process. Consortia, there's a whole host of participants in here.

And since it shifts from one set of participants at one end to another group of participants at the other end, we know there's a lot of mixing in the middle, so that's going to be one of the characteristics of policy. The other thing we can do is we can look at key processes that are occurring in that translation across there and a lot of the current debate, and you've all heard this, talks about R&D and discovery. And we're talking about tech transfer. We're looking at commercialization policy. We're looking at entrepreneurship, a major focus. Looking at manufacturing, looking at marketing, and so forth. I'm going to come back that as well and talk about some of the ramifications.

So let's talk a little bit about the government, one of the key players. If you're at the one end of innovation where we're talking about — the seed corn — where some of these ideas are being generated, you have to look at the R&D intensity we have as a country; that would be an obvious measure. And of course, that's looked at as the total R&D as a function of our gross domestic product. And you'll see that there's some very interesting shifts that are occurring, in our portfolio, I'm going to come back and talk about this, but the federal share of R&D has been steadily declining since the 1960s.

Industrial R&D has grown and, of course, the composite basically leaves you with some oscillation but a fairly constant level of R&D intensity as a country over a fairly long period of time. And if you want to improve the efficiency of innovation as a country, one obvious thing you can do is seek policies that seek to increase the level of investment, increase the R&D intensity. And in fact, if you look at the President's innovation policy, that is a goal.

Now how do we compare with other countries? Well, there's been a lot of data; one of the things we find, we are not the most R&D intensive country in the world. Israel actually has that distinction right now. We are not bad, but we're sitting at, as I said, a little over two and a half percent of GDP. China, which everybody watches, is way down here. And so one of the questions you can ask, well that's not too bad, but this is the graph that scares everybody. This is the change in R&D intensity since 1995 through 2008. The United State has only changed as we said, it's been a very flat R&D intensity over this period of time, and now you have China, which has changed its R&D intensity by 170 percent. Remarkable amount of investment in this area, followed by Singapore, Finland, Thailand, South Korea. And so this was the kind of information that the Gathering Storm was really focused on.

We're not bad, but we're not getting much better and other countries are aggressively, basically seeking the same policy solution we are. So the competitive advantage we seek to hold is not unique. It's one that's achievable by other countries.

Let me go back to the federal R&D. If you're in the government world you, you focus a lot on budgets, and one interesting thing is to plot the amount of defense or non-defense spending in this country as a function of the total outlays, the total amount of federal spending that's made, and this is basically that data. This bump that you see right here, was the Sputnik response; that's the space program.

And this is the data, this was the highest level of R&D intensity we ever had, was going through that bump. So that was very real, that was a dramatic shift in the investment priorities of this country because what's happened since then is that it's come back and basically lived at a total fraction of the total outlay of the budget. And so what typically happens in budget debates today is that the total amount of the fraction of discretionary funding that the government's going to spend in science is not really changing. What you're really doing is looking at the mix and who gets the inflationary growth. That's really what the debate is about because we've been a constant piece of the pie for a very long time.

The exception is here, and it's data like this that leads to Bill Gates saying, well, where's a good Sputnik when you need it? This is what we need to do, in real terms, raise the absolute level of priority for this type of investment.

The other thing the government does, besides money, is policy. In the current Administration, the President released a framework for American innovation. It was released by the National Economic Council last year. It was a joint document with the National Economic Council and with OSTP. And it was a very interesting framework. It was strongly motivated by the fact that the Administration had just worked with Congress to pass the American Recovery and Reinvestment Act, the stimulus bill.

And of course, the stimulus bill was interesting because it wasn't pure stimulus. It was a major recovery piece, tax breaks and short-term investments into projects, but there was explicitly a major component that made a long-term investment in the ability of the country to grow. That was the reinvestment part and the media has tended to forget that side of the story. And so the, that's where most of the science funding in the American Recovery and Reinvestment Act came from, was the notion of reinvestment.

And so to put that into context, they released this framework. And what's quite interesting about it is it includes what you would all think would have to be there, the basic building blocks, which is workforce; education reform; immigration reform--making sure we hold onto talent that's trained and brought in to this country; and restoring leadership and fundamental research — a doubling of the budgets for the agencies that do the physical science research. Looking at infrastructure, physical infrastructure and broadband technology infrastructure that's imperative to growth. And this is all very important and very traditional and things that we all care a lot about.

What was very interesting to me is that they added two more pieces to this. One I had never seen before in this context. It was showing to me a real maturity in this thinking, which is starting to look farther downstream now into the markets and really looking at promoting American exports, looking at the capital markets and how capitalization is flowing in this system. Looking at entrepreneurship and encouraging risk at key sections of this process. And looking at public-private sector innovation, which I told you there's going to be a strong mixing piece. And so you start seeing, coming out very explicitly, a set of issues in the middle space. And I'm going to spend most of my remaining time talking about this.

And then again this element that we've talked about before that's been there from the beginning. In areas where the government has an overriding public policy goal — national defense is one we all think about, but if you think about it now in terms of energy, the President has stated as a priority of the Administration to promote energy independence and one aspect of that program is to look at renewable energy and to promote renewable energy sources. One of the key technology infrastructures you will need for that to take place is a modernization of the electrical distribution system. You can't put widespread, photovoltaic cells on houses if the grid infrastructure doesn't allow electricity to move both ways — allow pricing to work both ways where you are now a seller as well as a consumer — and allow for what would be much increased instability in the distribution system as you have this wide set of power generators that you don't control coming online and doing this.

And that's where the smart grid effort came from. Health IT was promoted on increasing the efficiency and improving the cost efficiency and the quality of health care. So what you see is a recognition that technology innovation is going to play a key role in these overriding national priorities and these become thrust areas that we've always had, but maybe the thrust areas are going to be a little bit different now.

This type of policy framework is the subject of a lot of legislation that goes through the Hill. Most of us don't have to worry about all the legislation that goes through on the Hill, but this legislation actually authorizes the funding increases for the agencies and many of the programs that we talk about.

Let me talk momentarily about universities. I'm not going to spend a lot of time on this. You guys should give this part of the talk, but I wanted to note a couple of things. This is again from the National Science Foundation, looking at expenditures for science and engineering, research and development at colleges and universities in the United States. And it shows over the past six-year period. What I wanted to point out was this very interesting shift here between where the funding is coming from. Federal and state funding, government funding, for R&D expenditures at universities, is declining significantly, if you compare the overall change of all funding compared with the growth rates and needs.

Actually, I was surprised by this because given all the news we've heard about state and local funding, I was surprised that it kept up. It clearly shows some of the R&D expenditures in the states are being protected and we'll see whether this holds up over time. But the federal R&D rate is much lower. So where's the difference being made up? It's very significantly being made up by industry, by internal institutional funds, which I'm sure is something you're quite aware of, and by other and much of this is also outside external foreign investment that's coming into universities. And there will be consequences to those shifts because they change the whole interaction between the funder and how we do that work.

Universities play a central role in the process of innovation. This is a series of bragging rights by universities that you're probably all familiar with. But universities sit at the junction of several of the major components in this whole structure, including workforce. So the primary mission of universities to train and educate our next generation of leaders, technologists, and scientists, is at the heart of, in fact, the policy solution. But they also play a key role in the performance of research and technology development itself, certainly in basic research, but also they play a role in the commercialization of some technology and, of course, this is where it becomes interesting because now you start to ask very deep questions about the role of the university in technology development. And a lot of it I think stems from an indirect role at the universities as leaders within their communities. And universities feel a great pressure to participate in the local economy and to support and, in fact, very often are the nucleus of technology-based economic development in their communities.

To talk a little bit more about some of the programs, I thought I'd show you this graph that one of the NIST economists showed me. And it's a different way of thinking about the technology development process. Again, going from the discovery phase, science to the commercial phase, and it's done in terms of a risk concept where you would plot the overall risk of the process over time. And you could ignore the actual durations here because it would probably be technology dependent and I don't know what technology they were thinking about when they made the graph.

But in science it's a high risk, you know, that's why the federal government invests in this. There would not be a market condition in which you would expect base R&D to be funded. And what it points out is that the science discovery gets to a point where, in fact, you see what's called a risk spike. And this is very important because in my way of thinking what happens is the output of basic R&D is science, scientific discovery. It is not a potential commercial technology. And so there's this gap and so at risk, this double risk is there's a technology risk, which is this great scientific discovery, a potential technology and there's also a business risk. Can you take that technology and turn it into a successful business enterprise? And what happens is, they both sort of pile on at the same time.

We typically think of the valley of death as starting where, you know, the venture capitalists sit, but remember, investors of that type are primarily looking at the business de-risking. They're already looking at a potential technology and asking how do we fund this? Does it have a market? Does it have the business plan? These are all business considerations. And there's a recent follow-up report to the Gathering Storm report that came out this last week that talked about the fact there are really multiple valleys of death and the one I'm concerned about now is the technology valley of death. How do you motivate taking a science research outcome and taking it to a possible commercial technology? And there's a couple different things that are happening.

One is, you try to take the people doing this, that way. And a lot of the focus today on university-based entrepreneurship is exactly focused on this. You take a faculty member and you get them interested in starting a business, licensing a technology. What you're doing is you're taking the people who know this science and pulling them this way to try to take the technology. It doesn't matter if they get all the way here and are billionaires, you really just want to get them to the point where it's a possible scientific activity. In fact, the business community will tell you these people are very important because they come over here, they learn enough about business, and even if they sell it and go back to the university and do research, they understand this process and their value really starts to come up.

The other thing that happens is industry, which sits way out here, tries to peer over here and see what's happening, and you know there's been a lot of interest in what are called open innovation models; Proctor and Gamble and other companies that are really looking at mining and trying to gather information from what's happening over here and again try to identify the potential ideas in a informatics way and using funding and other vehicles to pull it forward. And I'm going to come back to another vehicle, at the end, that's sort of a mixture of the two. So universities and entrepreneurship as a consequence of this, are receiving enormous attention.

Well from the White House and from the Commerce Department, there has been really from my perspective, a striking focus on entrepreneurship because from a government program perspective, there's not a lot of overlap. And yet what we see is enormous focus on how do we support entrepreneurs; in many cases it's not so much helping, but how do we get out of their way? How do we lower barriers and reduce friction in the system?

A key player here are the universities themselves and one of the things we did in response was before launching into, here's a great program that's going to fix everything, well let's go talk to the people doing it. And so we launched a national series of workshops, hosted by Secretary Locke across the United States, talked to university leaderships about their role in commercialization, innovation, entrepreneurship, and that's all being distilled now. There's also a national advisory committee drawn from industry and academia that's looking at these results and coming up with ideas. So this is going to continue to be an important area.

In the context of industry, I wanted to focus today on manufacturing. This is a little bit unusual, and I always get into a little bit of trouble near an economist, sorry, when I do this because the economist will say no one sector should be preferred over the other. And that's probably true from an economics perspective. I'm not an economist so I don't know. From a technologist perspective, somebody looking at innovation, manufacturing is unique. They play a unique role in the innovation process. Why? One, that's where a lot of capacity is.

Seventy percent of the private-sector R&D engine is sitting in the private sector in the manufacturing industry base. That's where it sits. It plays an enormous role in extracting the full economic benefit out of this innovation process. If you just come up with the idea of offshoring the manufacturing too early, a lot of the real value add is missed and doesn't pay in. And a lot of the value add is jobs, by the way. This is where the high-paying jobs are. Trade, our trade deficit, our trade volume is, is in terms of the trade balance, is driven by manufacturing. And the majority of our trade value is in manufactured products, and almost all of that is coming out of our manufacturing sector. And so from my perspective, manufacturing deserves special attention because it plays such a critical role in this process.

Here's sort of a striking graph looking at the trade deficits compared with all manufactured products in the United States and with advanced technology products. We know we have a trade deficit, but until 2001 we did not, we had a trade surplus in high-tech manufacturing. We lost that in 2001 and, in fact, that high-tech trade balance is growing. The largest exporter of high-tech products in the world today is China. High-tech, not toys and other low-tech commodities, it's high-tech products. And this should be of grave concern to all of us because it has not just an impact on manufacturing jobs and trade, but I would argue it has a very strong impact backwards on the process of innovation. You have 70 percent of your R&D capacity sitting in the manufacturing and if it's not here then how's it going to participate?

This is some economic data that compares the R&D intensity within industries by sector and their change in real output. And you know, there's interesting differences we could talk about. But if you look at the difference, you will see there's a very striking correlation between the R&D intensity of industry and its economic performance. And, of course, you saw that in the trade numbers as well.

So if they're a major performer in this process, are there any signatures that we should be worried about from industry? And the answer is yes, and I think most of you probably know this, either directly or anecdotally, but the interest in industry in the early, in the R&D phase, is actually diminishing. The valley of death from their side is getting broader as well, and this is a survey that basically asks, it's a sea-change index, so you ask a bunch of companies are they planning on starting a short-term business, investing more in short-term business opportunities, or investing more in directed basic research, a long-term investment. And you subtract the number that say it's going up from the ones going down, and you plot this. And for every year, with the exception of just that one year in 2008, the respondents indicated more of them were going to be decreasing their investment in directed basic research and increasing their investment in short-term business functions.

So the time horizon in the business community is getting shorter and shorter, and that's driving the investment posture, even though when you saw the R&D intensity, it's the industry R&D that's been growing, the federal government's has been declining and yet in that industry portfolio it's becoming shorter and shorter time horizon focused. So that should be of concern.

So we talked about this innovation model. It's clearly inadequate to do any sort of process, so one of the economists at NIST, Greg Tassey, has proposed an economic model of a technology-based economy that looks like this, which goes from planning and production and goes to value add and then what you see is the development of technology in these lower boxes, which include entrepreneurial activity, risk reduction technology methodologies, which include standards development and regulations and other things that lower the risk of introducing a technology into the market. This is where the real technology innovation is occurring and what's interesting from this discussion is that there, you can divide the technologies into several pieces. We tend to think of the technology as the intellectually protected part of it, the IP part of technology. But, in fact, it's also equally important to have technology infrastructure, manufacturing process technology is vital to productivity increases and, in fact, are essential for this system to work. And very often these proprietary technologies are built on underlying generic technology platforms. And the color coding is basically to suggest where in blue, public-sector government money can participate. And the red is indicating where it's primarily private-sector investment. And you see what's quite interesting is from a government side, it means we should really start focusing on these generic technology issues. And, of course, what happens, you can start designing programs around a model like that, I won't go into that. But I wanted to talk to you about an idea that's, that we've been exploring at NIST, which is how to get across this technology valley of death.

So I talked about you can encourage scientists to go this way with entrepreneurship and really promoting that. You can have industry looking back this way, through open innovation models. The other thing we can do is we can define a goal at this end that is not a proprietary technology where somebody's going to win or lose.

We can define a goal that's a generic technology, one that everyone can share in. And then people can take that generic technology and begin to commercialize offshoots of it. If you can do that, and that's the big if, what you can create is a consortia that's willing to share the funding, share the risk of investing in the development of that generic technology. You've created a commons, and the classic example of this that's given is Sematech. The semiconductor industry was facing a deep technology challenge that was going to impact Moore's Law. And it was basically a process technology question, having to do with how to get the line shape of these devices smaller and smaller. And there were open questions about whether the traditional optical technologies would enable this to happen. Semiconductors as many of you know was, was viewed in a national need context, so DARPA was very involved with semiconductor research, as with DoD. And, in fact, what the government did at that time was, with public funding, invest in the formation of a consortia of semiconductor companies. That consortia formalized their arrangements into a corporation called Sematech. It was 50/50, $100 million from the government, $100 million from the semiconductor industry. And in the end we all know what they did. They developed a technology roadmap that defined a research path and a technology path to develop. In the end it was interesting, it was process technology. The money didn't go back to the semiconductor companies, it went to the applied materials and the other type of process technology companies that were developing the equipment that could do this. From there, the semiconductor companies knew they could take that technology and run with it, whether it was memory, whether it was processors, whatever the output was. And that was a model that we looked at.

So at NIST what we did is we initiated a pilot program in nanoelectronics research in 2007. Let me skip that and just tell you the major ingredients. The technology challenge in this case was that the current semiconductor technology is CMOS based. CMOS will play out, it's very clear we're going to run out of gas here. And the question is, if you're going to continue on this curve, what is the next technology? We don't know, so this is beyond Moore's Law debate that's been occurring and beyond CMOS technology. The semiconductor organizations, SRI, and the SRC in this case, developed a consortia to identify what is the next switch, what is the next transistor beyond CMOS? It's a generic technology, all the companies agreed that they could use whatever the outcome of that research was and go their own direction. NIST funded this very modestly at $2.75 million a year. It attracted an additional $20 million a year and that led to four university-based research enterprises across the United States. What's interesting is that the existence of this effort seeded the formation of over $110 million of funding that was ready to take the generic technology and commercialize it. So you see leveraging, 10 to one leveraging of the public investment and then another 10 to one leveraging almost looking at the commercialization. These are the university centers that go across the United States. What they're basically doing is looking at promising nanotechnologies that could be the next switch.

The early stage of this was a little bit of a thousand flowers blooming. So the research centers identified various promising technologies, decided which centers would focus on which technologies and you see some of the examples here in spintronics, graphing, plasmonics, many of the areas that I know are of interest here at Pitt. This consortia is now reaching the very interesting phase where some of these are promising enough that they're going to begin to down-select and move to a proof-of-concept. Again still in this discovery mode.

Over just two years the output of this consortium has been remarkable. It's pulled together over 30 universities, over 100 graduate students, many publications, and the patent number has jumped by 10 over just the last year, and again, this is a very young project. And so it's hard to look at a trailing indicator yet because this is such a new program, but the indications are very good.

And so one of the questions is, is this a general model for trying to cross and look at this? And I think the answer is going to hinge on can you define that technology challenge properly? You've got to create the commons, and it's got to be a big enough challenge that the companies see their future success in addressing it, and yet it has to be a precompetitive outcome, a generic technology where they're willing to work together. And I'm not sure that can be done in every case, but we think it can be done in many.

Last week, a follow-up report to the Rising Above the Gathering Storm was issued. It's called Rising Above the Gathering Storm, Revisited: Rapidly Approaching Category 5. And in it there's a series of findings, which are all pretty depressing. In 2009, 51 percent, for the first time in this country, the majority of U.S. patents went to non-U.S. companies. There are 16 energy companies with more reserves than the largest U.S. energy company--16. Manufacturing, manufacturing of computer technology in this country is now smaller then it was in 1975, when the first PC was made. China is now, as I said, the largest high-technology exporter. Surveys repeatedly indicate a preference to invest in China and India. In fact what's quite interesting is if you ask large U.S.-based, multinational corporations if they're increasing their R&D investments, most of them will say yes, you saw the curve going up. But if you look at where they are investing in R&D, the rate of growth in their investments in China and India is three times larger than the rate of investment in the United States. China has seen the dividends of their investments. Over just 15 years, China has moved from 14th place to second in terms of the number of published research papers. And the quality of that work is quite high.

And so the committee makes an interesting set of conclusions. What they say is, it is the unanimous view of this committee (This is the same committee that had Stephen Chu and other notable folks on it. This is the Norm Augustine report) that the nation's outlook has worsened. What they also say is, the only promising solution for this problem is through innovation. And I take that as a call to action. I think that there's no more important work that we have in front of us. I think that the future of the country is literally at stake. And it's certainly the way I view my role at NIST — how we structure our programs, how we work to try to address this.

I will also say the challenge is bigger than any one agency or piece. I think that the solution is going to require a framework in which we reach broad agreement over the set of things that we have to do. This is a complicated enough issue that it's not going to be one signature program that's going to solve innovation. It's going to take a concerted effort over time. And the only way to do that is to develop the political and policy consensus over what the right things to do are. Otherwise, and that's why if we get stuck into a bitter battle on this, that's probably the worst outcome of all.

So with that I want to again, once again thank you all for having me out to Pitt, it was great to be back here and I look forward to seeing if there's any questions. Thanks.

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Q: You did mention the discrepancy in engineering degrees being produced in Asia and the U.S. Comment on that [unint.] I'm the dean of engineering here and that's something we've been paying a lot of attention to.

A: Yeah it's not an area that I'm a deep expert in, so let me give you the superficial answer. We've had a problem with this discussion, as a policy discussion in the past. In fact, many of you remember we'll declare there's a shortage and then have an apparent overproduction and we get this whipsawing and sort of a, in fact NSF has been beaten over the head over this issue very aggressively in the past. And the Gathering Storm Report actually touches on this. And it makes the comment that you have to look at the workforce issue in the broad context. That this, this is a bigger issue then just the number of research PhDs that are working, for example, in the engineering field. In that case, you can get into these very cyclical because as we teach more, we create more, and you can end up into these. But if you take the broader view and look at what's happening in terms of the needs coming particularly from industry and in other nontraditional sectors, they argue that it's abundantly clear that there's a gross shortage and we're starting to see increased anecdotal evidence from industry that this is a major problem. That in fact, some of the surveys the Council on Competitiveness is looking at is that workforce considerations are one of these motivators, leading companies to offshore, right.

One of the discussions that is I think hurting this, is that there's a notion still that the reason U.S. companies offshore manufacturing, for example, is lower labor costs. We're seeing companies offshore when in fact the, the marginal cost of labor in the produced product is extremely low. So that's really not what's driving it, there are other factors. And one of the key ones appears to be the caliber of the workforce. If you look at China, you're seeing they're, they're parking research, in fact the highest-rated advantage for, when they ask Chinese companies why they put their plant in China, it was the quality of the workforce and the associated nearby research infrastructure.

So I don't know if that answers your question, but I think, I know this report took a careful look at that and said we really have to take a broad view of this workforce issue.

Q: There was a New York Times article today about the honeybee system and how it took a collaboration between defense- funded research and university-based research to discover a link between a virus and a fungus that might be causing the honeybee syndrome. And I thought back to one of your early slides where you were showing the five different areas where research and development is happening and the real huge amount of money being spent on R&D in the military and defense funding. And I'm wondering how we can have more collaboration, developing more innovation between those five different areas?

A: Yeah, so the, I... it's an excellent question because if you think back not that many years ago, in fact, if I think back to when I was a graduate student with Jim, you know, you had mission-based funding, let's say DoD funding. It was pretty clear that if you had that kind of funding, it was targeted at addressing a particular area of interest that was of direct concern to defense. And if you came up with something that had an economic spinoff, that was icing on the cake. That was, you know, that was a spinoff. And we talked about that in the space program, you know, the whole discussions we had about Tang and Velcro as being you know... these... go into that.

So what's happened now of course, the innovation discussion kind of pivots this a little bit and says that this economic driver is in fact very important. And so even in the case of a defense technology like the one you're talking about, now all the concern is, is how do we make sure, how do we increase the efficiency with which funded research like that is turned into commercial activity? That's a big part of the debate. The other part of the debate that I didn't touch on is that... take the argument to its, you know, logical conclusion. If the purpose of our R&D investment were to maximize the economic return to the country, is the portfolio of research optimized to do that? And so I could have shown you a graph that if you look at... take manufacturing, and you look at where the U.S. invests in research and the manufacturing, you will see it's dominated in medical and defense related manufacturing technology. If you compare that with the U.S. manufacturing base, even the high-tech base, you're going to see that it's badly skewed. Seventy-five percent of the manufacturing sector is not represented by those types of investments. So we really haven't optimized seriously our R&D investments towards a purely economic thing. We still have this mission lens and so that's why I think a lot of the focus right now is how can you take... however the project, and maximize the commercial return? So DoD is very focused on this. DARPA's very focused on this and the other agencies.

I hadn't seen this report. I'll have to take a look at the article in the New York Times.

Q: Yes, does NIST have a list--short, long, or otherwise--of suitable industries or sectors for the generic technologies that you mentioned in your, uh...[inaud.]?

A: No. So the question was does NIST have a list of potential generic technologies of the type I talked about? And I would say the answer is no. In fact, I would say the question is actually more fundamental then that. I would say it's still not known, how do you pick an appropriate generic technology where this will work? The magic sauce of Sematech was that it was a very compelling technical problem. They could not maintain the growth of their industry if they were not able to get these device sizes smaller. It was clearly a business imperative, and the answer to that problem was one that they, didn't require them to protect it with IP protection. It could be shared by all. It was a process technology, they could all live with the outcome. So it's, it's the creating the commons that's the magic sauce of this thing. Compelling problem that's still precompetitive in nature. And I think, I don't know how to pick those yet--I think that's still a question. We may not pick them from the government side, what we may do is put that challenge out and then evaluate the ideas that come up. I think that would make more sense. But I have a suspicion that we're going to find that a majority of those candidates are process technologies. You know, it's the thing that enables you to make something better, faster, cheaper, that's going to be. Because that's tooling, that's often shared already.

So I think that's going to be comfortable in this pre-competitive side and yet to the extent these process technologies are foundational to achieving what you need to do, and they often are, we're going to see, you know, either a critical materials problem or a critical process technology problem are going to probably be the predominant, but I don't know. And I think we're going to end up having to issue calls and evaluate under some sort of criteria for what... And if you do it wrong, I think it can fail pretty badly. If you pick the problem that's too high in the sky, it's just a, it's just a, you know, nano-technology, it's just a field. If it's too narrow, it's going to be just a research collaboration, it won't, it won't have the same character as you saw from the other one.

Q: I think from the university standpoint, one of the major watershed changes in terms of moving things forward was the passage of the Bayh-Dole Act. And, and that act I think is in some people's view now, may be an obstacle or a, a something that promotes innovation or at least the, the movement across that linear line. Do you want to comment about whether or not that, that particular act is helpful? And is there any other future legislative activities that might help the innovation process?

A: So what I can say is that the Bayh-Dole Act and its cousin in the federal side, the Stevenson-Wydler Act, were both put in in this early to mid-80s period to try to address that risk bump. And the idea was if we give people an incentive to take a technology further down the road, give them a piece of the action, that we will incentivize this path to commercialization. I think the overriding consensus from most folks, and this is something that came up in these forum that we held across the United States, was that from almost every measure, big measure, this has been a spectacular success.

Is it perfect? Hard to say. I mean it would be great if the one piece of legislation with no adjustments was perfect on its first time out of the box. The, the point I would make is, it's hard to even answer that question right now. We have a done a poor job in putting really meaningful metrics on the ramifications of this incentive through the system. What we tend to measure are the things that were easy to measure. So we look at patents issued and license and revenue, and a lot if had to do with the business viability. The mentality within universities going from this is going to be a cash cow, to no, this is not. It's, we're happy if it actually breaks even.

But it's part of... So I think there's a lot of maturing going on both on the public side and within the universities about the, what this all means. The only way we're going to meaningfully inform your exact question, which is, you know, what adjustments would you make to make it better and to what extent does it actually introduce barriers? Sometimes if you talk to industry, real or perceived, they see a barrier because it creates what they view as conflicting interest in a particular technology. Without the data, it's going to be a faith-based policy discussion and it's not going to be very much fun or productive.

And so I think the immediate challenge is, and I think the universities have really embraced this, is let's roll up our sleeves and start looking at the metrics underlying commercialization and try to really drive some meaningful adjustments to those, if they're needed at all.

Q: I'm not sure that there's a question here yet, but as a scientist in basic research over the last 50 years I have seen basic research mostly go the way of big science. And big science in my field of astrophysics means that there is not a single country that can afford to fund our projects. All of our projects are multinational. So how, how, what is the thinking about funneling multinational, basic research outcomes into national technologies and commercialization?

A: Yeah, you know that's a great question and, and it's a good thing you didn't actually ask me a question because I don't think I actually have an answer. It's, it's very clear, you know I was doing big science, so I was a neutron scatterer. And one of the things we, we noticed is, as the scale of a collaboration reaches a certain point, it now transcends the scale of your country. And so you, you're automatically now into these international collaborations. It's very clear. I would say that our ability to manage those international collaborations is very immature. There is an enormous amount of friction in just setting them up and doing them effectively.

And all you have to do is look at the, the international fusion, you know, of the EDAR program, to see how contentious and difficult this can be. Some great things come out of it when it works, and I think we haven't even begun to address your question, which is in that sort of international collaboration framework, what's the context for... you know. And by the way the whole discussion on commercialization is very, has this boundary issue in there because the R&D environment, you know, it's, it's interesting that we position that as our competitive advantage because it's the most fungible aspect of it all.

The R&D enterprise has been international all along. The ideas move around and we build on each other's ideas and so that's not a national asset, and yet we are investing public. So there's some very interesting boundary, boundary value issues in here that we probably haven't even begun to address.

Q: Thank you.

A: I wish I had an answer for you. Well, great, thank you all very much. I enjoyed it.

[APPLAUSE]

PB: Thank you Patrick. I've been asked to let everyone know just quickly that downstairs immediately following this, is a undergraduate research poster fair, and I heard George whispering that there might be some food there as well. So if you could show up to just support our undergraduates that would be terrific. And a little later this evening at 7:30 there's going to be a special presentation of a play, "Darwin and the Kid," at the Stephen Foster Memorial and you're all welcome to that as well. So thank you again, Patrick. [APPLAUSE]