Excerpt:  Strategy and Science / Technology, part two

In part one, we explored the idea of science, that is, how science came to be what it is today, and what strategists can learn from that development.  We now pivot (as Silicon Valley types like to say) to the practice of science, with a focus on education and innovation.  We begin with a few questions, such as:  How exactly does one become a scientist (beyond the typical steps of undergraduate and graduate degree programs)?  What strategies should a prospective science major use to be successful in their chosen field?

Stanford University’s Carl Wieman recently shared findings from his research in physics education, findings generalisable across the sciences.  His work is built upon others’ cognitive science studies into how expertise is achieved in any field, exploring specific aspects of expertise in science and how it is learned.  In particular, Wieman is interested in the physicist as problem-solver, where “solving is defined as everything a physicist does in their research, from selecting a suitable problem, to carrying out the lengthy process of obtaining results, to finally presenting those results and their implications to the community.”*

* Wieman, C., “How to become a successful physicist,” Physics Today (September 2022): 46-52

Starting from the position that, according to cognitive science research, people gain proficiency by practising tasks repeatedly over time, Wieman builds a model similar to master-apprentice approaches in craftsmanship.  Skills are learnt and the learner advances to higher levels of skills with guidance from those already skilled.  From his own research, Wieman constructed a series of problem-solving decisions, nearly 30 in total, found to be necessary for all physicists.  These decisions are, as one would expect, choices between options, characterised as much as possible by the information available and the judgement of the individual.

“With limited information, the decisions can never be certain; rather, they are educated guesses or judgements, albeit highly informed ones. The problem-solving skill was in the quality of the judgements. The experts often noted that research breakthroughs came from recognising the significance of some additional information that other researchers had overlooked.”

* Ibid

Straightforward enough.  What stood out, for Wieman and his team of researchers, was the importance of domain knowledge and cross-disciplinary expertise in making good decisions.  Therefore, just as we see in critical thinking theory, becoming a good scientist requires learning both the knowledge and how to use the knowledge in decision-making tasks.  This includes how to organise information, the design and application of mental models and algorithms, and intense practice over an extended period of time, coupled with frequent feedback.

Wieman goes on to emphasise general professional and interpersonal skills that serve to reinforce decision-making abilities.  He also translates his findings into specific tradecraft suggestions for science educators at all levels, including course design, instruction, and related activities, as well as more advanced programs.  He notes, for instance, how post-doctoral advisors may inadvertently restrict the range of decisions to be undertaken by a student out of habit or necessity and thus constrain the potential for growth and learning.

“For example, many of the problem-definition and planning decisions occur when the adviser develops proposals to fund the work and hire students and postdocs.  To address that weakness, the student (or postdoc) and adviser should seek out opportunities to review those previous decisions and how they were made. Whenever possible, the adviser should challenge the student to think of alternatives and then discuss why those alternatives would usually not be as good. Of course, if the student comes up with an improvement, so much the better. Additionally, the student could apply for graduate fellowships, such as from NSF’s Graduate Research Fellowship Program, that require them to write a research proposal, which should include making and justifying those first decisions.”*

* Ibid

Lastly, Wieman highlights the challenges of self-awareness, confirmation bias, and reflection aspects of several of the decisions, skills that are difficult to learn and are not usually taught explicitly within the context of scientific education.

So, say we follow Wieman et al’s advice and create an extraordinary cohort of skilled scientists.  To what end?  You may recall our earlier observation regarding the power derived from science and technology, a resource much in demand by business and government alike.  As Voltaire is reputed to have said, “With great power comes great responsibility.”  Thought must be given, therefore, to the strategies related to the relationship between science, technology, and society.

This topic is so wide-ranging it could warrant its own separate book.  Let’s look at just three aspects, namely access to information, surveillance, and geopolitical rivalry...