How to win at work in the age of AI
Re-skilling and developing cognitive flexibility
Cognitive flexibility is one of the building blocks of acquiring new knowledge and functioning effectively in a dynamic business ecosystem. It’s an essential trait that hiring managers
increasingly are looking for as the cadence of innovation accelerates and the need to be able to pick up new ideas and bring them into practice becomes ever more urgent. With the changes that artificial intelligence is expected to wreak on industry and society, the nature of what is required of the workforce will change even faster. If you want to stay competitive, and win at work in the age of AI, you need to retrain your brain so that you can learn faster and bring that learning to bear in a context relevant to your workplace.
Unfortunately, the conventional manners in which we are taught are ill-suited to keep up with the accelerating pace at which we are expected to learn new facts and absorb new ideas. Many aspects of the educational system have not changed in substance since about 1100 AD.
You have a wise person at the front of the room, delivering information from a prepared text. You have rows and rows of students, sitting on uncomfortable, creaky wooden benches, trying to take this word-stream and turn it into something they can use. This scene would look no more out of place in a medieval church than it would in a twenty-first century university auditorium at most of the world’s 26,000 or so higher education institutions. Interestingly enough, the University of Oxford was born out of a centre of ecclesiastical teaching on the same site about 850 years ago, but has since become renowned for its ‘tutorial’ system, where two or three students engage in active dialog with a professor about work they have prepared beforehand.
The way the tutorial works is that you complete an assignment and show up to meet with your tutorial partners and your Fellow (your professor). You get feedback on your assignment, discuss a topic and lead up to the next assignment, which you then work on independently. The tutorial system, also used at Cambridge, incorporates some of the techniques of what is considered ‘best practice’ based on study of cognitive and neuroscience, but was developed more than 130 years ago. Unfortunately, most universities don’t operate that way. It’s more cost-efficient to jam five hundred students into a large lecture hall and have one instructor at the front broadcasting material. It’s more efficient to grade multiple-choice exams than to have the student assessed based on their ability to speak and communicate effectively about their Ideas.
The COVID-19 crisis laid bare the limitations of the conventional learning model when, overnight, universities worldwide had to instantly convert into delivering over video-conference. One educator shared with me that she was counseled to simply deliver her standard three-hour lectures on Zoom, and that no other preparation was required. Spoiler alert: it’s not going to go well. Another educator shared with me that he feels that students in the back half of the semester, the virtual part, got about 20 per cent of the learning value that they should have.
A better way is needed. This chapter will help you begin to understand what is wrong with the old way of doing things, and what the new way looks like. Later on in the book we’ll talk about how artificial intelligence is beginning to be used to improve the ability of students to learn and work in small groups, including (in a nifty sleight of meta hand) to learn about artificial intelligence.
The problem with education
Our current educational system does a good job of training creativity and mental agility out of us, by punishing those who ‘colour outside the lines’ and rewarding conformity. When we were children, we possessed a great deal of cognitive flexibility. We were able to invent and play, creating stories with our friends and imagining new worlds. Then, as we enter conventional education systems, we are trained out of our cognitive flexibility. Almost every major educational system currently extant puts people into rules-driven environments dictating what you learn, how long you learn, how quickly you learn it and how you spend your day.
To a greater or lesser degree, this extends all the way through our undergraduate educations. It also lines up with graduate education, to such a degree that I often say it takes a couple of years to retrain graduate students for useful employment. I say this only half-facetiously; I have taught a number of graduate students, particularly MBA students, who are exceptional executives and who use the university environment as a carefully calibrated tool to achieve the next step in their careers. I also see many students who get lost in the constructs of academia, who overvalue their market value based on the nature of positive reinforcement they’ve obtained in a top graduate program, and who then flounder a bit for a couple of years after graduating until they find their footing (I watched in horror as one student rejected a high-profile summer internship working directly with the CEO of a $5 billion growth company in her exact field, doing exactly the kind of work she said she wanted to do after MBA, in favour of joining a somewhat shady startup engaged in a somewhat shady part of industry). All too often I feel we do our students a disservice, by providing theoretical constructs and intellectually interesting ideas, but then failing to connect those to management practice. We reward those students who agree with our epistemologies and leave them with an abstraction of work rather than the ability to work. For my part, I try to make sure my classes bridge between seriousness of intent of academic respectability, providing perspectives and facts grounded in rigorous academic research, and useful applicability in real settings, delivering practical tools and real-world examples so that my students may take theory into practise.
Now let’s think of the successful professional in today’s competitive jobs environment. Twenty- five years ago you needed to understand what the Internet was and what it meant. Ten years ago you needed to understand the cloud and why it was changing networked systems. Today you have to assimilate information about technologies like blockchain and artificial intelligence, as well as the business process changes necessitated by the pandemic. In five years it’ll be some other disruption, perhaps quantum or nano or something else. Most of my students have been working professionals who need to keep pace with disruptive, technology-driven change, but who also need to excel at their day jobs while doing so. They aren’t taking two years off to pursue knowledge. They are trying to pick up innovative skills and capabilities while still employed and building their careers.
How can you keep working and also keep up?
You need to develop better skills for acquiring new information. You need to acquire it faster,
you need to understand it more deeply, and you need to stay on top of what is relevant so you can pick up the next set of skills. Education is no longer a fixed duration event (perhaps four years of undergraduate and two years of graduate studies). In the AI-enabled future, you need to be able to acquire new knowledge every six to twelve months.
Sound impossible? It isn’t. But it may require retraining your brain. Computer systems can help and we will discuss this later in the book. In order to truly augment your career, however, you need to begin by augmenting the human computer, your mind.
Augmenting Your Career: How to Win at Work In the Age of AI is available from Amazon and all book stores
