Category Archives: Innovation

Has the world gone crazy? Maybe…

I wanted to write this article the day after July 14 and the tragic events in Nice. But it took me a little longer. Start-ups, Innovation are above all a passion for me, a topic that fascinates me. I see many reasons for optimism and hope for humankind and for the planet as a whole. But for any positive pole, there is a negative one. And any optimistic analysis of a complex topic always induces its pessimistic viewpoints. The point is not to provide a “simplistic” opposition to innovation and entrepreneurial creativity, but to mention here some works which demonstrate, by their depth, the complexity of the subject.

The simplest, and probably the least interesting of the three controversial analyses I will present here comes from the United States. Two MIT researchers, Erik Brynjolfsson and Andrew McAfee, explain the risk of automation that are created by science and information and communication technologies (ICT). In Race Against The Machine followed by The Second Machine Age, they show that many jobs will necessarily disappear with the development of ICT. All technological advances have created such risks (printing, the steam engine, electricity) but it seems that ICT is of much higher dimension, with the “fantasy” of transhumanism, which suggests that humans could be totally replaced by the machine.

Brynjolfsson-McAfee

The book is an excellent introduction to the challenges the world will meet and let me quote. The chapter Beyond GDP begins with a quote of Robert Kennedy: “The Gross National Product does not include the beauty of our poetry or the intelligence of our public debate. It measures neither our wit nor our courage, neither our wisdom nor our learning, neither our compassion nor our devotion. It measures everything, in short, except that which makes life worthwhile.” I know that these books were best-sellers in the US, probably because they ask interesting questions. But I must say that I found the analysis a little light with nor facts and figures compared to the two books that I will write about now.

Piketty-Stiegler

Capital in the 21st Century by Thomas Piketty is one of the most impressive books I have ever read. I will not give my summary here, and I encourage you to read the wikipedia page or slides from its website, if you do not have the courage to read some 900 pages! But again this is an absolutely remarkable book which the following 4 figures will further encourage you in trying…

Piketty-tables-en

Piketty shows that capitalism has reached its limits probably due to unregulated globalization but more importantly because the growth of the planet will probably not be anymore what it was during the post-war boom. Piketty is quite close to the theses of Erik Brynjolfsson and Andrew McAfee, but he seems to me much more convincing about the causes, effects and remedies. Bernard Stiegler wrote a strange book, In the disruption – How not to go crazy? (In French only so far, but many of his books have been translated) This is a very difficult book to read, closer to philosophy and psychology, but behind the difficulty, what a fascinating analysis, rich and also taking into account the complexity of the world. If you fear the demanding reading, you can listen Stiegler (in French only )in a series of 15 one-hour epiosed produced by Radio Suisse Romande in June 2016: see the web site of Histoire Vivante that is devoted to the work of Ars Industrialis. The main thesis of Stiegler is that capitalism has gone crazy and that the absence of regulation can lead you to madness. The “disruption” can be good when it is followed by a stabilization phase. And as serious as the economic analysis of Piketty, Stiegler undoubtedly explains why people become crazy to the point of causing events like in Nice.

HistoireVivante-ArsIndustrialis

Challenges and Opportunities of Industry 4.0

I must say that last week I did not understand very well the “Industry 4.0” concept. And after a brief stay in Munich this week – where I had an explanation by E&Y – see below – but especially after reading the text of a speech entitled “Smart Industry 4.0 in Switzerland” (see pdf) given by Matthias Kaiserswerth, the “Business and Innovation Forum Slovakia – Switzerland” in Bratislava on June 20, I fully understood the importance of the subject. I also found out this morning two excellent reports: “Industry 4.0 – The role of Switzerland Within a European manufacturing revolution” (see pdf) by the firm Roland Berger and the “Digital Vortex – How Digital Disruption Is Redefining Industries’ (see pdf) published by Cisco and IMD. I got permission from Matthias Kaiserswerth to publish his speech here (I thank him for this) and this speech is an excellent introduction to the subject with many interesting ideas to solve the challenges ahead…

Smart Industry 4.0 in Switzerland

Matthias Kaiserswerth, Business and Innovation Forum Slovakia – Switzerland, 20.06.2016, Bratislava

In this brief input speech, I want to talk about some of the challenges and opportunities that the on-going digitalization has for the Swiss economy, our labor force and the education system.

Current State and Challenges

Unfortunately, Switzerland is not yet a leader in digitalization. When we compare ourselves with other OECD countries, we play at best in the middle field. From a policy point of view, we are behind the European Union. This month, June 7, our Ständerat, the smaller parliamentary chamber representing the cantons, has asked our government to analyze what economic effect the emerging EU single digital market will have on our country. Our current president, the minister for economy, education, and research in his response admitted that until the beginning of this year Switzerland had underestimated the 4th industrial revolution and now is trying to catch up with various measures[1].

ICTSwitzerland, the association of the Swiss ICT industry, earlier this year launched a scorecard [2] digital.swiss in which they rate Switzerland’s state of digitalization in 15 dimensions. While we have excellent basic infrastructure and rank highly on a generic international competitive index, we don’t yet sufficiently leverage digital technologies in the various sectors of our economy.

Scorecard
SI4.0-SwissScorecard

The scorecard reflects a classic Swiss paradox. Because of our very direct democratic system, built on subsidiarity, we provide good infrastructure and general economic framework. When it comes to leveraging these foundations, we leave it to private initiative as we don’t pursue an active industrial policy – certainly not at the federal level. So far our companies – mostly SMBs, 99.96% of our companies have less than 250 employees – have excelled at incremental innovation. Incremental innovation can be good for a long time, but it impedes dealing with major technology shifts that can disrupt an entire industry.

This happened in the 70s and early 80s when the “Quartz Revolution” almost extinguished Swiss watchmaking. Now again history may repeat itself as the watch industry missed or were too slow to embrace the trend towards smartwatches. Apple within the course of only one year managed to surpass with their watch-related revenues all Swiss watch companies even Rolex [3].

With the digital revolution, driven out of Silicon Valley, we compete with an entirely different innovation model, namely disruptive innovation.

Just look at examples from the sharing economy such as Airbnb and Uber.

But it doesn’t stop there. Consider computer companies now building the future self-driving electric car – Google being a prime example. While European OEMs had experimented for a long time with self-driving cars putting all the intelligence into the car, Google took an entirely different approach. Because of their maps, their work with Streetview, they already have very precise information about where the car is going and thus can leverage the power of connectivity and the cloud as well.

While we would strive to build the perfect battery for an electric car, Tesla took what we would consider inferior laptop batteries and leveraged IT to make them useful in their cars.

Opportunities

With the long Swiss tradition of bringing foreign talents into the country and allowing them to succeed, we have an outstanding opportunity not to miss out on the current industrial revolution. Many of our successful international companies got started by foreigners – just think of Nestle, ABB, or Swatch.

Businesses have now realized that meeting the pressures of the strong Swiss Franc with only cutting costs is insufficient. They are looking for different forms of innovation leveraging IT. About a year ago, various Swiss industry associations launched an initiative “Industry 2025” to change the mindset in our machine industry and alert them to the new opportunities [4].

Some companies though have seen these chances already long before our national bank stopped pegging the Swiss Franc to the Euro.

For example in 2012, Belimo a company producing actuator solutions to control heating, ventilation and air conditioning systems launched their “Energy Valve”. It consists of a 2-way characterized control valve, volumetric flow meter, temperature sensors and an actuator with integrated logic, that combines the five functions of measuring, controlling, balancing, shutting and monitoring energy into a single unit with its own web server as IT interface. The intelligent valve can be used to optimize water flow in heating and cooling systems and yields significant energy savings for its customers [5].

Other companies in the Swiss machine industry have started to think about how they can leverage Internet of Things (IoT) to create new businesses based on the data that their machines generate. A good example is LCA Automation, a company in the business of building factory automation solutions. They want to offer predictive maintenance based on dynamic condition monitoring of their installed factories. Leveraging existing information like current and position from frequency converters in their drives help understand how the machines are used. In select cases they install additional sensors to measure vibration, acoustic noise to allow their clients to schedule maintenance instead of running their installations to failure [6].

In my opinion, the challenges in addressing more of these opportunities are (1) cultural, (2) an IT skills gap, (3) finding and realizing new business models that best exploit the digital opportunity and finally (4) creating an environment where collaboration with external partners can let you innovate with speed.

Contrary to software, industrial products cannot be easily updated in the field, they are engineered to last 10 to 20 years. The mindset of the computer scientist: “we can fix it remotely with an update,” requires the mechanical and electrical engineers to rethink how they construct their systems. When Tesla had issues in 2013 with one of their cars catching fire because its suspension at high speeds lowered the car too close to the road, they did not issue a massive recall but instead remotely overnight changed the software in the cars to guarantee a higher distance between car and road.

Getting these diverse cultures to collaborate requires respect among the different professional disciplines and would call for the occasional computer scientist to serve on the board of industrial companies to challenge their established way of thinking.

The skills gap, finding enough software engineers interested to work in industrial companies is significant. Current predictions are that by 2022 Switzerland will lack 30’000 IT experts. Considering that industrial companies compete with the better paying finance industry for the same talents, means that industrial companies need to become very creative to address this shortage.

Implementing new business models that exploit the digital opportunities is a significant challenge for established industrial companies. If a company whose core business is selling industrial machines, wants to start offering value added subscription based services to optimize the industrial process realized by their products, they get into an entirely new business. They will need to decide whether these services are only available for a process realized by only their machines or whether they want to offer it also on competitors’ installations. They need to devise a new sales incentive scheme based on a recurring revenue stream. They need to build a support infrastructure that matches the optimized process and no longer consists of experts that only know about their own machine. In short, they need to build an entirely new business. Doing so inside an established large company is extremely hard maybe even more so than doing it in an external startup.

Finally, creating a collaborative environment with external partners to innovate with speed is not something unique to the age of digitalization, however it will be key for industrial companies to capture the opportunity. In spite of the good examples from large industrial companies like Procter and Gamble around Open Innovation, a concept coined 13 years ago, many firms still have a strong sentiment of doing everything themselves or with their established supply chain partners. In the case of digitalization, however, new partners from outside the traditional industry need to be involved and made part of the solution. “Rather than using their own R&D budget, enterprises can leverage venture capitalist investments and integrate a technology solution in an accelerated timeframe” [7].

Education

Before I close, let me get back to education, a topic of particular importance in this new era. Switzerland has an excellent education system. However, we have a significant shortage of students that pursue a career in the Science Technology Engineering and Mathematics field (in short STEM) in addition to a skills gap in STEM for all the other students.

In 2014, the German speaking cantons launched a new common competence oriented curriculum “Lehrplan 21” (LP21) to address the skills gap by putting more focus on STEM subjects. For example, by introducing a new subject called Media and Informatics, the cantonal education ministers have accepted the notion that all students need basic skills in computer science to succeed in the professional or academic education system. As we speak, this LP21 is being implemented in the German speaking part of Switzerland, albeit not fast enough for my taste.

To succeed with LP21 we also need to qualify the teachers to competently teach these subjects in a way that keeps all students motivated. Specifically female students have a significantly lower self-perception in how they master technology and what they can use technology for [8]. The consequence is that we lose the female talent also in our workforce. So for example, in IT there are only 13% women in the Swiss workforce.

Promoting women in technology as role models and broadening specific programs to get girls interested in technology at a primary school age will hopefully help to bridge the gender gap in the long run.

Summary

When we look at the system of the Federal Polytechnic Schools (ETH Zurich and EPF Lausanne), the universities and specifically also the universities of applied science, government funding for research then we have an outstanding foundation upon which we can build to effectively compete in this 4th Industrial Revolution. It now requires a new mind set for our industrial companies to embrace the emerging IoT, Big Data, and artificial intelligence trends and the courage to experiment with the new business models that they enable.

You don’t get disrupted because you don’t see the technological shift and opportunity, you get disrupted because you chose to ignore it.


1: http://www.inside-it.ch/articles/44100
2: http://digital.ictswitzerland.ch/en/
3: http://www.wsj.com/articles/apple-watch-with-sizable-sales-cant-shake-its-critics-1461524901
4: http://www.industrie2025.ch/industrie-2025/charta.html
5: http://energyvalve.com
6: http://www.industrie2025.ch/fileadmin/user_upload/casestudies/industrie2025_fallbeispiel_lca_automation_2.pdf
7: https://www.accenture.com/ch-en/insight-enterprise-disruption-open-innovation
8: http://www.satw.ch/mint-nachwuchsbarometer/MINT-Nachwuchsbarometer_Schweiz_DE.pdf

Postscript: I mentioned above the presentation by E&Y, here is the slide that struck me…

The crazy ones. The misfits. The rebels. The troublemakers.

How is possible I never used this great quote when I talk about what is needed in innovation and entrepreneurship. What a moron, I am (sometimes…)

Here’s to the crazy ones. The misfits. The rebels. The troublemakers. The round pegs in the square holes. The ones who see things differently. They’re not fond of rules. And they have no respect for the status quo. You can quote them, disagree with them, glorify or vilify them. About the only thing you can’t do is ignore them. Because they change things. They push the human race forward. While some may see them as the crazy ones, we see genius. Because the people who are crazy enough to think they can change the world, are the ones who do.

Of course it’s very likely that you know what this is. And if not, no worry either. Here is the video:

And if you want to know more, check Think_different on Wikipedia.

Listen to the other voice too:

Andrew S. Grove 1936 – 2016

Andrew Grove died a few days ago. I remember reading is “Only The Paranoid Survive”. I remember that he had an amazing life, at least his first years from his native Hungary until he reached New York.

andrew-grove_2-225x300
Andrew S. Grove was chairman of the board of Intel Corporation from May 1997 to May 2005. He was the company’s chief executive officer from 1987 to 1998 and its president from 1979 to 1997. Ref: Andrew S. Grove 1936 – 2016 (Intel web site)

I also remember he wrote in 1010 an analysis about start-ups which is very profound. So I will quote him again.

It’s our own misplaced faith in the power of startups to create U.S. jobs. Americans love the idea of the guys in the garage inventing something that changes the world. New York Times columnist Thomas L. Friedman recently encapsulated this view in a piece called Start-Ups, Not Bailouts. His argument: Let tired old companies that do commodity manufacturing die if they have to. If Washington really wants to create jobs, he wrote, it should back startups.

Mythical Moment.

Friedman is wrong. Startups are a wonderful thing, but they cannot by themselves increase tech employment. Equally important is what comes after that mythical moment of creation in the garage, as technology goes from prototype to mass production. This is the phase where companies scale up. They work out design details, figure out how to make things affordably, build factories, and hire people by the thousands. Scaling is hard work but necessary to make innovation matter. The scaling process is no longer happening in the U.S. And as long as that’s the case, plowing capital into young companies that build their factories elsewhere will continue to yield a bad return in terms of American jobs. Scaling used to work well in Silicon Valley. Entrepreneurs came up with an invention. Investors gave them money to build their business. If the founders and their investors were lucky, the company grew and had an initial public offering, which brought in money that financed further growth.

Intel Startup

I am fortunate to have lived through one such example. In 1968, two well-known technologists and their investor friends anted up $3 million to start Intel Corp., making memory chips for the computer industry. From the beginning, we had to figure out how to make our chips in volume. We had to build factories; hire, train and retain employees; establish relationships with suppliers; and sort out a million other things before Intel could become a billion-dollar company. Three years later, it went public and grew to be one of the biggest technology companies in the world. By 1980, which was 10 years after our IPO, about 13,000 people worked for Intel in the U.S. Not far from Intel’s headquarters in Santa Clara, California, other companies developed. Tandem Computers Inc. went through a similar process, then Sun Microsystems Inc., Cisco Systems Inc., Netscape Communications Corp., and on and on. Some companies died along the way or were absorbed by others, but each survivor added to the complex technological ecosystem that came to be called Silicon Valley. As time passed, wages and health-care costs rose in the U.S., and China opened up. American companies discovered they could have their manufacturing and even their engineering done cheaper overseas. When they did so, margins improved. Management was happy, and so were stockholders. Growth continued, even more profitably. But the job machine began sputtering.

U.S. Versus China

Today, manufacturing employment in the U.S. computer industry is about 166,000 — lower than it was before the first personal computer, the MITS Altair 2800, was assembled in 1975. Meanwhile, a very effective computer-manufacturing industry has emerged in Asia, employing about 1.5 million workers — factory employees, engineers and managers. The largest of these companies is Hon Hai Precision Industry Co., also known as Foxconn. The company has grown at an astounding rate, first in Taiwan and later in China. Its revenue last year was $62 billion, larger than Apple Inc., Microsoft Corp., Dell Inc. or Intel. Foxconn employs more than 800,000 people, more than the combined worldwide head count of Apple, Dell, Microsoft, Hewlett-Packard Co., Intel and Sony Corp.

10-to-1 Ratio

Until a recent spate of suicides at Foxconn’s giant factory complex in Shenzhen, China, few Americans had heard of the company. But most know the products it makes: computers for Dell and HP, Nokia Oyj cell phones, Microsoft Xbox 360 consoles, Intel motherboards, and countless other familiar gadgets. Some 250,000 Foxconn employees in southern China produce Apple’s products. Apple, meanwhile, has about 25,000 employees in the U.S. — that means for every Apple worker in the U.S. there are 10 people in China working on iMacs, iPods and iPhones. The same roughly 10-to-1 relationship holds for Dell, disk-drive maker Seagate Technology, and other U.S. tech companies… (more on the Bloomberg article)

A great man has just disappeared.

Two Challenges of Technology Transfer – Part 2, Get to Know Your TTO.

My second post about Technology Transfer (following the one about National Systems) is about the micro-economics of the activity. This is motivated by the very good Keys to the kingdom – subtitled What you need to know about your technology transfer office.

Before summarizing its content, let me remind you about the posts which already cover the topic so you will agree it’s not a new topic for me and I consider it as important:
– University licensing to start-ups in May 2010 (www.startup-book.com/2010/05/04/university-licensing-to-start-ups) followed by
– University licensing to start-ups (Part 2) in June 2010 (www.startup-book.com/2010/06/15/university-licensing-to-start-ups-part-2)
– How much Equity Universities take in Start-ups from IP Licensing? in November 2013 (www.startup-book.com/2013/11/05/how-much-equity-universities-take-in-start-ups-from-ip-licensing)
– Should universities get rich with their spin-offs? in June 205 (www.startup-book.com/2015/06/09/should-universities-get-rich-with-their-spin-offs)

bioe2015

Co-authored by 18 people from Stanford, Oxford, Harvard, the University of California in San Francisco and the University College London, the article describes what should know people interested in getting a license on intellectual property to create a start-up. The paper begins with “As an academic […]entrepreneur, you will face many challenges” and the second paragraph follows with “In addition, you will most likely have to negotiate with your university’s technology transfer office (TTO) to license the intellectual property (IP) related to your research”.

What are these challenges related to TTO? they are written in the article in bold fonts as follows: Overcoming information asymmetries – Long negotiations – Inexperience – Lack of funding – Conflict of interest rules – Experienced legal counsel. This means that as a future entrepreneur, you should be prepared and ideally be knowledgeable about these.

The challenges

The main challenge seems to be the administrative complexity and opacity (page 1), including confidentiality of contracts, which makes it difficult for outside observers to understand fair market terms (page 1 again). In the end, they nearly conclude with: “Indeed, even for the universities for whom we have data regarding equity policies, it was often hidden deep within a jumble of legalese. To that end we encourage universities and research institutes receiving public monies to be fully transparent in their equity and royalty policies, and not use these information asymmetries as a bargaining advantage against fledgling […]entrepreneurs.”

On page 2, I note:
– A negotiation may be long (6-12 months, even 18 months) and one way to make it short is to take the proposed terms.
– A way to mitigate inexperience is by “preparing an adequate business plan or strategy for your IP before approaching your TTO” or by “bringing aboard team members with prior experience in […] commercialization to improve your team’s credibility”.
Lack of funding can be partially solved by signing “license option agreements”.
Conflict of interest rules “exist to prevent academics from playing both sides of a technology licensing deal or devoting too much time to nonacademic obligations”. Furthermore, “TTOs represent the interests of the university (not the academic), yet the academic is technically an employee of the university. “Our policy is to never negotiate directly with the faculty,” says a US-based TTO representative”.
– Experienced legal counsel is advised for assessing the quality of the IP but also because “[…]entrepreneurs often fail to appreciate the opportunity cost to the TTO in outlicensing. If a technology is licensed to an ineffective team (particularly with an exclusive license), the university forgoes any success or revenue it may have received from licensing the technology to a better organized industry partner. Moreover, universities have limited resources and manpower to protect IP, and, for this reason, prefer to license technology to teams they believe are well prepared to commercialize it.”

The equity deal terms

“Perhaps the most striking difference between the United States and United Kingdom is seen with equity deal terms. In the United Kingdom, a typical licensing deal is a rarely negotiable 50:50 split between the university and the academic […]entrepreneur, whereas US interviewees often reported universities taking a 5–10% negotiable equity share.”

You now understand why I said I was not convinced in my previous post about taking the UK as a reference. The US practice shows space for debate. You may check again my article from November 2013, where you will see that a typical deal is either 10% at creation or 5% after significant funding. Very rarely more.

Again the authors mention “US founders often do not realize that some deal terms are negotiable, including upfront fees, option payments, equity, royalty payments, milestone payments, territories covered, field of use and exclusivity versus nonexclusivity” and “In the UK, licensing deal equity terms are often perceived as being non-negotiable, though this is not always the case. In fact, many institute policies explicitly state that equity terms are negotiable.” This may however make the process lengthier.

On page 4, the authors add: “It is difficult to understand the justification of UK TTOs, such as Oxford’s Isis Innovation, taking 50% of a company’s equity at formation — which after investment can leave the academic entrepreneur with an extremely low stake from the get-go, for what was likely years of work, and will require many years and millions more to develop.” and indeed “The data would suggest that TTOs taking less upfront and leaving more to the academic and investors who will actually carry the idea forward pays off in the long term. Simply put: holding a smaller piece of something is still more valuable than a large piece of nothing.”

The mystery of royalties

“It is also worth noting that while a discussion on royalties was outside the scope of this study, it was clear from our research that many university TTOs “double dip” and take significant equity and royalty.” but again “Perhaps more disquieting than the out-sized equity and royalty stakes that universities are claiming is the lack of transparency from many universities on this critical issue.”

My conclusion: any wannabe entrepreneur should read this short 5-page paper and be prepared to negotiate. I would love as much as the authors that universities and research institutes be fully transparent in their equity and royalty policies, though I am also aware of the possibly weakened position of universities which would do so.

Two Challenges of Technology Transfer – Part 1, the National Systems.

Two documents have led me to describe two types of challenges facing the technology transfer of academic institutions.
– First, at a macro-economic level, the challenge comes from the various possible administrative structures, but also the complexity of the operations. The report Transfert et Valorisation dans le PIA (in French) by Bruno Rostand compares the national policies of Germany and the United Kingdom to that of France.
– Secondly, at the micro-economic level, the journal Nature published the article Keys to the kingdom with the subtitle, What you should know about your technology transfer office. I will come back to this in my next post.

Mise en page 1

The report of Bruno Rostand addresses the challenges that France meets after having established regional structures for technology transfer, the “SATT”. He notes that Germany has built a similar system with its “PVA” in the Länder. In both cases, there is a goal of financial independence which seems difficult to achieve if not unrealistic, despite the existence of public subsidies. In Germany, two of these companies have even filed for bankruptcy in Lower Saxony in 2006 and Berlin in 2013.

Why such difficulties? Because the returns on investment have not been up to the expectations. For example, approximately €10M euros have been invested each year in the form of public funds in Germany, but revenues remained much lower. In addition the regional structure has its limitations, as it is difficult to gain expertise in all areas of technology.

The United Kingdom has a different situation. The state has been a marginal actor and technology transfer was organized either by universities (Cambridge, Oxford, Imperial College) or by private structures close to venture capital (IP group) which organically helped in structuring technology transfer. Through externalization, these organizations have become private organizations, which have become rich in financial and human resources. At Oxford, ISIS employs 80 people for £14.5m in revenue in 2014. Imperial innovation has been publicly traded since 2006, employs 45 people and generated a profit of £27M in 2014. Imperial innovation has expanded its initial base in collaborating with other universities. Finally, the IP Group has agreements with over 15 universities for a profit of £9.5M in 2014. The report shows very different philosophies, whether public or private, with profitability as an end or not, with an obvious entrepreneurial dimension in the UK. if the focus on start-ups is important, this will lead to different structures, including maturation funds and incubators.

The report also shows that a licensing policy and a policy to support the creation of start-ups are very different. Finally, the new TT structures often have the sole responsibility of the development and maturation of IP, while research collaborations with industry remain the responsibility of universities. This separation could be a weakness when the two topics are linked.

A sensitive issue is that of exclusivity that can create tension when TT management is pooled over many universities. Some universities want to maintain some autonomy, especially in areas where the technical competence of the TT structure seems weak to them. Another sensitive issue is that of the structure by region while a transregional structure by field of expertise might be more appropriate. (The report also addresses research partnerships and international cooperation that I will not discuss here.)

In the final part, Rostand shows the complexity of the challenges. One must first define the mission of technology transfer which can be for profit or not. Externalization seems to be a trend in the three countries, but it has its advantages and disadvantages. It also seems that there is a lot of instability and fluctuations in funding cycles, which does not help to make an analysis of the transfer tools. The report also addresses the issue of human resources (types of skills and experience), another subject which may be related to the available resources of these organizations.

The only personal comment I make here is about my slight frustration at not having found in the report (which is extremely informative) an analysis of the US situation. The country of liberalism and private universities have very few external technology transfer structures, let alone for-profit. I have in mind WARF at University of Wisconsin-Madison – www.warf.org) while revenues of TT in the USA are significantly higher than in Europe. The explanation could simply come from a far more dynamic private innovation, regardless of all the systems in place.

Emerging Science and Technologies, why so many promises? (Part 4)

This is my final post about what I have learned from Sciences et technologies émergentes, pourquoi tant de promesses? (For the record here are the links to part 1, part 2 and part 3).

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The last chapters of this excellent book try to explore ways to solve the problem of excessive promises that have become a system. In Chapter IV.2, it is question of “désorcèlement” (the closest term I found would be “disenchanted”); I read it as a critical analysis of the vocabulary used by those who promise. The chapter speaks at length of the transhumanist movement, the promise of promises! “[…] Describe how these actors certainly produce, but especially divert away, reconfigure and amplify these promises […] in front of passive and naive consumers.” [Page 261] and later “[but] transhumanists are first activists, mostly neither engineers nor practitioners […] attempting answers to questions not asked or badly expressed, […] hence a really caricatural corpus,” to the point of talking about a “cult” (quoting Jean-Pierre Dupuy), “a muddled, often questionable thinking.” [Page 262]

In Chapter IV.3, the authors explore unconventional approaches, a possible sign of disarray to “scientifically” react to the promises. For example, they have contributed to the creation of a comic book to answer another comic which wanted to popularize and promote synthetic biology.

Adventures_Synthetic_Biology

The final chapter explores scenarios that may follow the explosion of promises, like the idea of ​​increasing the number of Nobel Prize. New promises?!! More concretely, the author shows that the initial promises are not followed in practice: “The wait & see phenomenon in investment, or lack of innovation, is less known, though widespread: the effect of general and diffuse promises maintains the interest of players but too much uncertainty holds back investment in cycles of concrete promises-requirements.” [Page 297] “A game is at work which continues as long as the players follow the rules, […] they are prisoners of the game. […] They may also leave it if the right circumstances occur and then the game collapses.” [Page 298]

In conclusion, beyond a very rich description of many examples of scientific and technical promises, the authors have shown how a system of promises was built through interactions between the various stakeholders (the researchers themselves, the (political, social and economic) decision makers who fund them, and the general public which hopes and feels anxiety). The relationship to time, not only the future but also the present and the past, is beautifully described, in addition to a desire for eternity. And finally, we mostly discover that the promises have led to numerous debates that were perhaps, if not entirely, useless, as we could have known that the promises can not be kept, even from the moment they were created…

Emerging Science and Technologies, why so many promises? (Part 3)

This is my third article about the book Sciences et technologies émergentes, pourquoi tant de promesses? After the general considerations on the system of promises, the book presents contributions describing specific areas:

I.3: nanotechnologies
II.1: semiconductors through Moore’s Law
II.2: big ata
II.3: digital Humanities
III.1: neurosciences and psychiatry
III.2: The Human Brain Project (HBP)
III.3: personalized medicine
III.4: biodiversity and nanomedicine
IV.1: assisted reproduction
IV.2: regenerative medicine

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Each chapter is interesting for the curious reader as it shows the dynamics between promises and expectations of stakeholders (researchers, politicy makers, general public). The chapter about the HBP is particularly interesting in the description of the disconnection between content and form. “How was it possible that the HBP “won the competition” despite the lack of evidence to establish pragmatically the scientific relevance and the legitimacy of its ambitious organizational goals? We develop the hypothesis that this deficit, criticized afterwards, was both hidden and compensated by the production of promises shaped to anticipate and / or respond effectively to the political, economic, social and health-realted stakes on the agenda of the “challenges to come”. [Page 166] The credibility of the HBP sealed by this decision has been built […] following an adaptation process and reciprocal validations in the double register of the politicization of science and the scientification of politics. In other words, we show that one of the important conditions of this credibility was the successful co-production of a strategic congruence between [scientific] promises and the agenda of policy issues. [Page 171] The connection between knowledge of the brain and forms of social life took place mainly in the domain of discourse. […] In this contrasting situation, discursive inflation around the brain and neuroscience seems to be the consequence of a lack of evidence, as if it had overcome, positively or negatively, the differences between the present and the future, the proven and the possible, the absence and the desire. This regular feature of big science projects has resulted in the development and implementation of a prophetic rhetoric that seeks to anticipate the possibility of a better future by borrowing to the notions of hope and promise.” [Page 176-77]

I come back to a quote from chapter 3 that is essential to me as a conclusion to this new post: The real progress of techno-science will less come from their ability to keep promises than from their ability to do without them, to inherit critically from the era of great technological promise. This is not to break an idol, but to learn how to inherit. [Page 111]

Emerging Science and Technologies, why so many promises? (Part 2)

(A word of caution: my English is reaching its limits in trying to analyze a demanding book, written in French. I apologize in advance for the very awkward wording…)

So just one day after my article describing Chapter 1 of Emerging Science and Technologies, why so many promises?, here comes an analysis of the second chapter, where the relation to time is analyzed, as well as presentism, futurism and the role of time in the promise system. There is the nice following passage:

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Since The New Atlantis, futuristic speculations have accompanied the development of modern science. And in the twentieth century, Jean Perrin has sealed a new alliance between science and hope. But for him, it is science that preceded and provoked hope while now, it is rather hope that drives research. Technosciences reverse, in fact, the order of the questions that was following the three critiques of Kant: “What can I know?” – the issue addressed in Critique of Pure Reason – then the question “What can I do?” – treated in the Critique of Practical Reason – finally the question “What can I expect?” – discussed in the Critique of Judgment. In contrast, in the current scientific policies, one determines what to do and what we can possibly acquire as knowledge by identifying the hopes and promises. (Page 50)

Yet there is a paradox already expressed in the first chapter between futurism with the terms of promise, foresight and prophecy that project us and presentism particularly marked by the memory that freezes the past and transforms the future as a threat that no longer enlightens neither the past nor the present. To the point of talking about a future presentification…

The chapter also deals with the question of the future as a shock, a time “crisis” due to the acceleration. To the feeling of the misunderstanding and helplessness, is added the experience of frustration and stress caused by the accelerated pace of life, the disappointment of a promise related to modernity, where techniques were supposed to save time, to emancipate.

Another confusion: the features of planning and roadmap which are typical of technology projects slipped into research projects where is used the term of production of knowledge, while in research, it is impossible to guarantee a result. But the author shows through two examples, that this development is complex.

In the case of nanotechnology, there has been roadmap with the first two relatively predictable stages of component production followed by a third stage on more speculative systems crowned by a fourth stage which speaks of emergence, and all this by also “neglecting contingency, serendipity and possible bifurcations,” not to predict, but to “linearize the knowledge production”. The roadmap predicts the unexpected by announcing an emergence, combining a reassuring scenario of control which helps in inspiring confidence and with at the same time an emerging scenario, to create dreams. (Pages 55-56)

In the case of synthetic biology “despite a clear convergence with nanotechnology,” the rapid development occurs without any roadmap. “A common intention – the design of the living – gathers these research paths.” And it is more to redo the past (“3.6 billion years of genetic code”) than to imagine the future. The future becomes abstract and it comes as proofs of concept. And the author adds that in normal science in the sense of Kuhn, these proofs of concepts would have fallen into oblivion. The paradox is that there is no question of right or wrong, but of designing without any needed functionality.

In the first case, “prediction or forecasting are convened as the indispensable basis for a strategy based on rational choice”, “the future looks to the present. “In the second case, there is the question of “towing the present” and “fleeing out of time.” We unite and mobilize without any necessary aim. The future is virtual, abstract, and devoid of culture and humanity; the life of the augmented human looks more like eternal rest …

Ultimately, the economy of promises remains riveted on the present either by making the future a reference point to guide action in the present, or it is seeking to perpetuate the present.

Chapters three and four are less theoretical, describing on one hand new examples in the field of nanotechnology and on the other, how Moore’s Law became a law when it was initially a prospective vision of progress in semiconductor. Perhaps soon a follow-up about the next chapters…

Emerging Science and Technologies, why so many promises? (Part 1)

Sciences et technologies émergentes, pourquoi tant de promesses? (Emerging Science and Technologies, why so many promises?) is the title of a book (in French only) from a group of authors under the direction of Marc Audétat, a political scientist and researcher at the Sciences -Society Interface of the University of Lausanne. This is not an easy reading book, it is quite demanding, but it raises important questions.

I have already reported on this blog about books that speak of a certain crisis of science, for example in The Crisis and the American model (in French), about the books “La Science à bout de Souffle” or “The University bubble. Should we pursue the American dream?” or in The Trouble With…, a book by Lee Smolin, not to mention the most violent criticism of the promises of technology by Peter Thiel in Technology = Salvation.

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This new book explores the promises related to science and technology to the point of talking about an economy of promises. This is a collective work which does not make it an easy reading, but the diversity of points of views is certainly an asset. I have not finished reading it and I will certainly come back to it. In the first chapter, P.-B. Joly describes the system of techno-scientific promises. He begins by introducing the concepts of Imaginary and Vision [Page 33] This “couple of concepts takes into account how various sources of inspiration are involved in the technical creation. […] The Imaginary gives an almost tangible appearance to concepts and ideals that are a priori devoid of it … [and becomes] a common sense that founds the action into society. […] The concept of Vision is close to that of Imaginary, but on a smaller scale. It is akin to that of “rational myth” used to analyze the dynamics of collective action in changing contexts. […] Coalitions of actors form around these visions of a prospective order and contribute to their dynamics. […] If we accept this conceptual distinction between Imaginaries (at large scales – the Nation – and in the long term) and Visions (at a level of coalitions of actors and active over periods of medium length) then comes the question of the interaction between the two.”

“Unlike Visions and Imaginaries, for which the content of technical arrangements is essential, what is essential for the techno-scientific promises is the creation of a relation, as well as a time horizon of expectations. […] Promises are essential in technology creation, because they enable innovators to legitimize their projects, to mobilize resources and to stabilize their environment. […] Any techno-scientific promise must convince a large audience that it determines a better future than the alternatives, even if the realization of the promise requires major, sometimes painful changes.” (The author mentions the history of electricity or the green revolution as the solution to world hunger)

“Our concept of techno-scientific promises has been systematized and became in the last forty years the governance of the new techno-sciences (biotechnology and genomics, nanotechnology, neuroscience, synthetic biology, geo -engineering, etc.) The construction of a techno-scientific promise meets two conflicting constraints: the constraint Radical Novelty and that of Credibility. […] (And I interpret that) for this request to be credible, one must disqualify alternatives. [Furthermore] For a scientific theory to be credible, its validity is neither necessary nor sufficient. […] The techno-scientific promises must have the support of a circle of specialists. Otherwise, they cannot resist the opposition manifested either in scientific arenas, or in public arenas. An extreme version is observed when the specialists refer to natural laws to justify the inevitability of technological change. (Examples are Moore’s Law and Gabor’s Law.) Thus, in principle, generic promises are not subject to validity tests.”

Finally, this intensification is reinforced by three complementary elements [page 39]:
– the future is more a threat than a source of hope;
– research and innovation are often presented as the only way to solve problems;
– the research stakeholders should demonstrate their societal impacts.

This leads to pathologies [pages 40-43]:
– the myth of a public victim of irrational fears and to be educated becomes an intangible scheme;
– the promises turn into bubbles;
– the radical novelty and uncertainty create conflicting discourses, sources of mistrust because the effects of such radicalism is not predictable so that through experimentation, the technologists become sorcerer’s apprentices and society, a laboratory;
– finally promises lead to endless discussions on fictions, on issues that may have nothing to do with the reality of research.

In conclusion Joly thinks this promises system is one of the enemies of the future because of the clear separation it creates between those who make the promise and those who are supposed to accept it. The recognition of this regime and therefore these problems is a prerequisite imperative.

After reading the first chapter, I remembered the societal concerns of Cynthia Fleury, about whom I have already said a few things in a digression in the article On France Culture, Transhumanism is Science Fiction. Our democratic societies are in crisis, and the distrust of politics as well as of experts has never been stronger. The issue of research and innovation is a component of this crisis. I am eager to discover the rest of this very interesting (and important) work …