Reframing the Purpose & Value of an Education

When we were young students, we often remarked to our teachers: "This subject is useless to me. When am I ever going to use this knowledge in the real world?"  Teachers everywhere cringe at this comment.  Today, many people are questioning the value of higher education as a whole.  Schools are scrambling to demonstrate their graduates' return on investment.  Institutions should be focused on helping students prepare for a successful career.  Developing practical skills and capabilities is important.  Yet, the value of higher education extends well beyond learning concrete skills that are easily transferable to the first job after graduation.  

As a faculty member, I believe that I'm helping to form the whole person, to contribute to the personal development of young people.   As part of that formation, I believe that I'm responsible for shaping the minds of my students, not by teaching them what to think, but how to think.  We sharpen their minds not by giving them all the answers, but asking tough questions. We push them, challenge them, and ask them to do something perhaps they did not think they could accomplish.  Sometimes, it means making them uncomfortable.  

Employers need to be focused on understanding the quality of the minds they hire, not just the batch of immediately applicable skills that person brings to the table.  By that, I don't mean focusing on GPA or test scores alone.  I mean that employers need to assess how applicants think through tough problems.  How do they frame an issue, explore alternatives, analyze ambiguous data, and draw conclusions backed by strong supporting logic?

As I think about these issues at the end of this academic year, I'm reminded of one of my favorite movie scenes about teaching and education.  The movie is The Paper Chase, starring John Houseman as a professor teaching first-year students at Harvard Law School.  He offers a beautiful soliloquy about his approach to teaching during an early scene in the movie.   My favorite quote: "We do brain surgery here. You teach yourselves the law, but I train your minds. You come in here with a skull full of mush, and you leave thinking like a lawyer." 

Perseverance & Focus When Work is Hectic

As I teach college students, I notice that some cope with adversity with a steady hand, demonstrating calm and resilience.  They ask for help when needed, but they don't make excuses.  They push through difficult situations.  Others become overwhelmed when something goes wrong in one facet of their life, and they allow those challenges to disrupt other aspects of their life.  They struggle to compartmentalize and push through when their usual routines are disrupted.  They often make things worse by falling further behind on key commitments, and then becoming increasingly anxious about how behind they have gotten. Of course, many of us have found ourselves in both situations in life, sometimes coping well with adversity, and in other cases, becoming overwhelmed.  

Karina Mangu-Ward wrote a great column recently for Fast Company.   She examined how high-performing teams remain steady and composed during crises.  Specifically, I thought her point about tradeoffs bears emphasis. She writes, 

One reason teams get frantic is that they try to optimize for everything at once: speed and perfection, quality and scale, consensus and velocity, innovation and risk. In calm periods that fantasy is inefficient. In turbulent periods it becomes fatal. Strong teams make explicit trade-offs early. They decide what matters most when good values collide.

I believe the same can be said for individuals.  Identifying our priorities and making tough tradeoffs can help us when things get a bit hectic.  Think back to my example with students.  Sometimes, submitting the assignment that is less than perfect is better than repeatedly missing deadlines in a course. Coming to class on time each day can pay huge dividends during a crisis, even if you are perhaps missing some assignments.  Communicating clearly with your faculty members is critical, perhaps more important than the work you do.  After all, if you ghost your professor, they will be far less likely to exercise leniency or offer extra support.  In short, you have to pick your spots when times get a bit hectic.  Too many students simply stop everything when they become overwhelmed, and then they begin a vicious downward spiral in which it becomes more and more difficult to bounce back.   The lesson is clear: Choose how to spend your time wisely, prioritize well, and then focus on those priorities.  Communicate clearly to those to whom you are accountable. Show up even if you can't always complete every task.  If students learn these habits in school, they will be far more successful in the workplace.  

Asking AI Chatbots to Adopt an Expert Persona Doesn't Work

Conventional wisdom suggests that we should ask AI chatbots to adopt an expert persona to elicit better answers. According to this advice, prompts will yield better responses if they include statements such as "Imagine that you are a world class statistician" or "Think like an expert engineer." Some of the major models (such as Claude and ChatGPT) advise users to engage in this type of prompt engineering. Yet, new research suggests that asking the models to behave as an expert does not work.

Savir Basil, Ina Shapiro, Dan Shapiro, Ethan Mollick, Lilach Mollick, and Lennart Meincke have published a report at Wharton titled "Playing Pretend: Expert Personas Don’t Improve Factual Accuracy."  Knowledge@Wharton summarized their findings:

The researchers tested several ways of instructing AI to answer nearly 200 PhD-level questions in one test and a further 300 similarly demanding ones in another. Some prompts framed the model as a subject matter expert, others as a different kind of expert, or as a child or layperson. But the results were consistent.  Expert personas did not lift performance and in most cases were no better than a simple baseline with no persona at all, while less knowledgeable roles often hurt accuracy.  Any gains were small and tied to specific models, not a general pattern, and even matching the persona to the task — using a “physics expert” for physics questions, for example — made little difference.