What the Tech Industry Can Teach AcademiaNew Technologies Opinions and Editorials 

What the Tech Industry Can Teach Academia



By Sami Benchekroun

Without taking risks and challenging the status quo, the majority of the world’s biggest scientific breakthroughs would not have been possible. That’s why it’s all the more surprising that academia itself is often reluctant to embrace new ways of working and sharing results. Scientists work on their research in secrecy for months or years and then wait an average of 100 days from the moment they submit their paper until it is published in a journal. Early-stage findings are hidden, failures are rarely shared, and the online presence of scientific content is disjointed, meaning that valuable findings often end up obscured from both researchers and the general public.

The tech industry, on the other hand, is known for moving quickly and working openly when building innovative products. Although startups share similarities with academia—like scientists, entrepreneurs research and brainstorm, test, and iterate ideas—tech companies face the added pressure of needing to make decisions and implement results quickly, or risk going out of business. Building products—and sometimes failing—happens publicly and is an accepted part of the entrepreneurial career.

This, along with the fast-paced, transparent, and risk-friendly startup culture, is the main reason that technology has progressed so rapidly over the past decades. I believe adopting a more entrepreneurial mindset and sharing research more openly could help scientists make progress, too. Moving away from the traditional, siloed environment of academia and encouraging a more transparent and digital way of working would not only allow individual researchers to get to results faster but improve the state of science as a whole.

An open-source approach

Entrepreneurs present minimum viable products, get feedback, iterate, and improve continuously. Software engineers often subscribe to the open-source movement, sharing APIs and code publicly and allowing other developers to build their applications using this data. A big reason the world is so technologically advanced today is that many engineers and tech companies were willing to put down the foundations for others to build on. Although there’s no denying that tech companies also have trade secrets, entrepreneurs are generally more aware of the business benefits of having an open source approach. It certainly helps that giants such as Facebook, Microsoft, and Google are leading the charge by joining the Open Compute Project, where all members openly share their data center designs, to name just one example from the tech industry.

Imagine the same mindset in academia. Rather than working in isolation and secrecy and waiting months or even years to publish their findings in a journal article, scientists should share each step of the research process openly, from raw datasets to the first conference poster. Introducing mandates from publishing groups, including Nature and Science, which require the underlying data and code from research studies to be made available for all articles they publish is a step in the right direction, but there’s still a lot of room for improvement. By sharing every step of the research process from the very beginning, scientists could discover peers who are working on the same topic, get feedback along the way, and allow others to cite and build on their datasets or preliminary results. Opening up early-stage science would also mean that valuable scientific trends and analytics could be discovered far earlier in the research process than is currently possible.

[tweetthis]Tech entrepreneur suggests what scientists in academia can learn from the boom and bust of Silicon Valley.[/tweetthis]

An integrated set of software tools

The tech industry is the first to adopt new digital services designed to increase productivity, streamline communication, or improve workflow. Startups gravitate toward applications that are intuitive to use and beautifully designed. Academia, on the other hand, is slower to embrace workflow tools, especially those designed to increase research sharing and collaboration.

Articles, datasets, and research findings are not organized in a meaningful way online, so even the process of finding relevant research can be overly complicated and time-consuming. Early-stage scientific content, such as the posters that are shared at academic conferences, is often restricted to the offline world and cannot be discovered by relevant researchers. In order to improve access to data and documents online, universities and institutions need to be more open to adopting software products that connect and order this research while providing an excellent user experience.

A culture of failing

Failures are inevitable. Nine out of ten startups end up failing, and, although it’s difficult to judge exact numbers, it’s safe to say that a significant number of research studies do not yield positive results. Yet one major difference between the tech industry and academia is that entrepreneurs are more willing to communicate their failures publicly, pick themselves up, and try again. In Silicon Valley, having founded an unsuccessful startup does not automatically mean an entrepreneur has a negative mark against their name. Every failure can be learned from, and sharing this experience transparently can be immensely useful for other people who are working on a similar topic.

If scientists shared their failed results, for example, they could save their peers from making the same mistakes. The only way to truly solve the world’s problems is if scientists are willing to work together to make progress on their research.

—Sami Benchekroun is the co-founder and CEO of early-stage research platform Morressier.

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