By Jane McGonigal, PhD, Director of Game Research and Development at the Institute for the Future and lead instructor of the Futures Thinking. The COVID-19 pandemic has changed the way we work, learn, and live in ways that seemed unthinkable and unimaginable until they actually happened. All of these changes happened faster, and at a more global scale, than nearly anyone thought possible.
If the year 2020 has shown us anything so far, it’s that we all need to get better at expecting the unexpected.
The COVID-19 pandemic has changed the way we work, learn, and live in ways that seemed unthinkable and unimaginable until they actually happened. All of these changes happened faster, and at a more global scale, than nearly anyone thought possible.
But what if you’d started imagining how you would adapt to a pandemic earlier? What if you’d had three months, six months, or even a year to prepare for the reality we’re all living through now?
What would you have done with that extra time to prepare for the future? Whom could you have helped sooner?
These aren’t hypothetical questions. The first 10,000 students in the Institute for the Future’s new Futures Thinking Specialization (a collection of skills-building courses I teach on Coursera) were given exactly this kind of “get prepared early” opportunity. Last summer, months before anyone had diagnosed the first case of the new coronavirus, the Institute for the Future launched the course Simulation Skills: This is Your Brain on the Future. In Simulation Skills, students learn why the brain has a hard time accurately predicting the future, and they practice habits that increase their ability to anticipate and prepare for surprising events. As part of the course, students tackled this assignment:
At the time we launched Simulation Skills, no one knew we would be living this possible “future” so soon. Pandemics are just one of the urgent futures—alongside climate change, mass migration, automation of work, and deepfake technologies – that the Institute for the Future has been researching for years and helping learners prepare for. It just so happens this one particular future actually happened almost exactly as we forecasted it would.
This is why, months before the global lockdowns and stay-at-home orders, Coursera students were _pre-thinking _how their lives would change during a pandemic. By starting to practice futures thinking, they were preparing to take action. So when the reality of COVID-19 caught up to our “possible future,” our students were faster to adapt and less prone to getting stuck in old ways of doing things. Since early January, I’ve been receiving messages from Coursera students who participated in the pandemic simulation. They’ve said things like, “I’m not freaking out, because I already worked through the panic and anxiety when we imagined it in the class,” and “I’m starting to prepare for this now, I remember what it was like when we simulated it.”
The basic skills of futures thinking can help you prepare for whatever comes after COVID-19. It’s not just this pandemic—it’s all the rapid technological, social and climate changes that are coming faster than we realize.
Here are four simple futures thinking techniques anyone can practice. I teach all of these skills, and more, in the Simulation Skills course that is part of the five-course Futures Thinking Specialization available on Coursera.
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Today you're going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates. We gonna use Python OS remove( ) method to remove the duplicates on our drive. Well, that's simple you just call remove ( ) with a parameter of the name of the file you wanna remove done.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc.. You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like __init__, __call__, __str__ etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).