Remote Work and Well-Being

Subscribers:
351,000
Published on ● Video Link: https://www.youtube.com/watch?v=7Vz53pEN7h0



Duration: 4:49
657 views
8


This video accompanies our accepted paper for the New Future of Work Symposium 2020. The paper is entitled "Remote Work and Well-Being" and is co-authored by Shamsi Iqbal, Jina Suh, Mary Czerwinski, Gloria Mark, Jaime Teevan. You can read our full paper at http://aka.ms/nfw2020.

See more at https://www.microsoft.com/en-us/research/video/remote-work-and-well-being-2/




Other Videos By Microsoft Research


2020-08-03Microsoft Urban Futures Summer Workshop | Policy and Social Impact [Day 3]
2020-08-03Microsoft Urban Futures Summer Workshop | Sensors and Data [Day 2]
2020-08-03Microsoft Urban Futures Summer Workshop | Data Driven Urban Transformation [Day 1]
2020-07-31Managing Tasks Across the Work-Life Boundary: Opportunities, Challenges, and Directions
2020-07-31Phong Surface: Efficient 3D Model Fitting using Lifted Optimization
2020-07-30How Work From Home Affects Collaboration: Information Workers in a Natural Experiment During COVID19
2020-07-30Empowering and Supporting Remote Software Development Team Members through a Culture of Allyship
2020-07-30Impact of COVID-19 crisis on the future of work in India
2020-07-30Towards a Practical Virtual Office for Mobile Knowledge Workers
2020-07-30Challenges and Gratitude of Software Developers During COVID-19 Working From Home
2020-07-30Remote Work and Well-Being
2020-07-30Early Indicators of the Effect of the Global Shift to Remote Work on People with Disabilities
2020-07-29Hope Speech and Help Speech: Surfacing Positivity Amidst Hate
2020-07-28Frontiers in Machine Learning: Security and Machine Learning
2020-07-28Frontiers in Machine Learning: Climate Impact of Machine Learning
2020-07-28Frontiers in ML: Learning from Limited Labeled Data: Challenges and Opportunities for NLP
2020-07-28Frontiers in Machine Learning: Saving Lives with Interpretable ML
2020-07-28Frontiers in Machine Learning: Machine Learning Reliability and Robustness
2020-07-28Frontiers in Machine Learning: Big Ideas in Causality and Machine Learning
2020-07-28Frontiers in Machine Learning: Beyond Fairness: Pushing ML Frontiers for Social Equity [Panel]
2020-07-28Frontiers in Machine Learning: Accelerating Machine Learning with Confidential Computing



Tags:
New Future of Work Symposium 2020
remote work
Shamsi Iqbal
Jina Suh
Mary Czerwinski
Gloria Mark
Jaime Teevan
Microsoft Research