“Freedom of Science” or “Freedom from Science”?*

“Freedom of Science” or “Freedom from Science”?*

Universities were one of the strongest pillars in the Western Age of Enlightenment. Over time, the segregation into independent disciplines replaced the classical four faculties (theology, jurisprudence, philosophy, medicine) – a development from which students but also society and economy significantly benefitted. However, scientific progress itself, as well as social requirements and economic needs, led to a situation in which even higher degrees of specialization did not necessarily produce better outcomes or higher productivity:

Three examples:

  • Traditional clinical disciplines could no longer cope with all aspects of biochemical and physiological progress. The view on cancer had drastically changed in the years prior; yet, clinical disciplines and education streams remained unchanged. At the time, modern hospitals found a workaround by establishing “expert boards for tumors” with representatives from all clinical disciplines until state-of-the-art oncologists could be educated and accepted by the medical societies.
  • Physicist graduates who starting their career in industry figured out that being able to solve Schroedinger’s equation under special boundary conditions did not help them at all to understand economic phenomena like design-to-cost, world market regulations or benchmarking analysis.
  • Human resource managers sought specialists that could step in immediately rather than receiving post-university / pre-industrial training to bridge the academic and practical worlds. Instead, productivity gains within the first six months of fresh hires are more or less expected by the hiring managers, which meant that finding the right specialist at the right point-in-time was in their interest and part of their incentive scheme.


The death of the academic hero and the need for ‘T-shaped’ individuals

While students wanted an education that takes them through a privileged life, the traditionalists of an independent science insisted on value conservatism regarding knowledge creation, and economy called for specialists in every new discipline – picking up the pace.

So what needed to be done to cope with conflicting interests of the various stakeholders? The answer for the last 30 years has been to develop more cross-disciplinarily. Topics such as “mechatronics” (mechanics & electronics), “business informatics” (business administration & data science) and many more have been created, however at the same time the problems developed even faster. Industry needs innovation, and innovation – and in particular disruptive innovation – which takes place between the disciplines rather than by extrapolating existing technologies and disciplines. So, further specialization can address certain issues. But this will not solve the fundamental problem of the different stakeholders – neither for the individuals, businesses, economy, nor society – that T-Shaped individuals, with a mix of specialist and transversal competencies are required, and that study programs at universities do little to provide these.

The specialist, one time the ‘academic hero’, loses attractiveness once his core competency gets standardized. Society is fighting against megatrends like demographic change, ubiquitous digitalization or unbalanced wealth with teams of all kind of experts; however, the overarching mega-problem of increasing complexity can’t be addressed by further specialization. Industry feeling the competitive breath on its neck increases pace but – at the same time – is about to ignore adjacent innovations… A vicious cycle!


So how can universities respond going forward?

This leaves universities with an unsolvable job to do, however, at the same time a unique opportunity:

Firstly, the programs offered by academia need to be broader and at the same time more focused. A broad education exceeding today’s fundamentals is a must: Physicists need to understand economics, physicians must understand latest developments in genomics, economists need to know what to expect from data science – just to give a few examples.

In a second phase, however, universities need to team up with partners in touch with the future needs: The link to industry, enterprises and other institutions (e.g. NGOs) has to be much closer to specialize on the right topics! Today’s sequence of B.Sc. – M.Sc. – PhD followed by further vocational training (programs for MBAs, post docs, trainees) are not efficient; neither for future industry employees nor for the next generation of committed scientists.

Universities will compete by being best in both – a solid knowledge base for their students, and a coordinated guidance into their next professional phase. Teaming up with the parties that have a demand without losing independence – this is the key differentiator for being attractive to future students. “I got the best education and the best guidance into my professional life” – all stakeholders will sign up to this.



So how could this look like? Traditional education in small groups in the elementary classes, ongoing individualized consultancy and guidance on what to do next, and joint exercises with future partners thereafter. A smooth transition, mutual monitoring, path correction, but no certificate without need!

The good thing is: We see more and more universities forming “schools” or institutes that are focused on “industries” or application areas, such as mobility or health. We see more and more innovative examples of industry-on-campus, co-locations, regional special topic clusters, application or innovation labs, etc. Already today we count a lot of those formats targeting an intensive interaction on real challenges from industry and applicable solutions from academia.

To really “transfer” knowledge into applicable innovation and a competitive technology advantage we need even more direct interaction and dialogue in a faster time. The systematic knowledge transfer through these mechanisms might be viable for students and PhDs: dedicated courses and seminars (e.g. case studies, capstone projects, student case competition), hackathons, internships as part of the study program, training-on-the-job (i.e. university study/training supporting employment).

However, the biggest challenge will remain: How do we establish an efficient knowledge transfer in a life-long-interaction between scientific and industrial experts – in an on-going two-way exchange?

Career paths – industrial and scientific – have to become more permeable. That requires a review of incentive and evaluation schemes on both sides. Focusing academics on the present academic KPIs only (e.g., publications, evidence of qualification for public funding) does not support the exchange with experts from industry, nor the academic going (back) to academia after some years of working experience in industry. For scientific experts, the exclusive evaluation of academic and non-industrial KPIs does not help them to gain experience in industry.

Furthermore, focusing on seamless career paths on the industry side, which cover a broad experience in different functions, cultures and leadership positions, does not honor or recognize scientific sabbaticals or any other kind of friction in the career path. This lack of recognition of the need for regular knowledge updating (often referred to as ‘adult education’, specializing (through a PhD), or lifelong learning) limits the potential for industry experts to re-engage with universities.

Thinking about a completely new permeable career path is not only worth a try; it is the future!

Being engaged in the university-industry cooperation business for the last 10 years, I see a lot of changes for the better. But I also observe the systems working and optimizing themselves quite independently from each other. Coming too close to each other brought around numerous claims by self-proclaimed judges: “Industry corrupts the independency of science”, “science prostitutes oneself for the sake of capitalism”…

Getting back to the initial question, we absolutely need a dialogue between all involved stakeholders: academia, industry, society, government going forward. The answer is not an “or”, rather the answer can only be an “and”: freedom of science AND freedom from science.

*I borrowed this witticism in a slightly different meaning from my doctoral thesis supervisor, Prof. Dr. Werner Kirsch. I owe him more than this bon mot.


Since 18 years Natascha is active in various leading roles within Corporate Research and Innovation at companies like Siemens and Osram. She has a long-year experience in the University-Industry-Business, currently managing Siemens’ global strategic partner programs with universities and research institutes. Natascha has a long-year history in Siemens’ international technology and innovation management and was responsible for expanding Siemens Corporate Technology’s footprint to Asia and Russia. For many years Natascha has coordinated the company’s engagement in manifold external research and innovation organizations and bodies, e.g. Bayerische Forschungsstiftung, Stifterverband, Forschungsunion, acatech and DAAD. Natascha holds a PhD degree in BA from Ludwig-Maximilians-University Munich and had worked for several years as strategic consultant for various companies.

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