Responding to the COVID-19 Unemployment Crisis and Meeting the Future of Work Challenge
Summary
Due to technology’s disruptive force in society and on the labor force, voices representing business and state governments have recently emphasized the need to revisit the social contract among firms, employees, governments, and citizens. This need has only intensified with the COVID-19 pandemic. The economic emergency associated with the pandemic has left 21.5 million workers unemployed and an additional 11.5 million workers with reduced pay to date. Today’s unemployment numbers are far worse than during the 2008 Great Recession. Underscoring the racial disparity seen in this economic crisis, Black and Latinx workers are currently experiencing higher rates of unemployment than white workers.
The next president should immediately sign two Executive Orders (EOs) to address the current crisis in work and the urgent economic emergency that has left Americans evicted, unable to pay bills, make rent, or put food on the table. The first EO would modernize unemployment insurance nationwide by boosting state unemployment insurance programs. The second would establish a U.S. Future of Work Commission tasked with developing a new model of work that addresses the key challenges the Fourth Industrial Revolution presents to American workers today.
As cyber threats grow more complex and sophisticated, the nation’s ability to defend itself depends on developing a robust, adaptable, and highly skilled cybersecurity workforce.
For the United States to continue to be a competitive global power in technology and innovation, we need a workforce that understands how to use, apply, and develop new innovations using AI and Data Science.
Students, families and communities want and need more STEM learning experiences to realize the American Dream, and yet they cannot access them. Prioritizing STEM education must be an urgent priority for the federal government and the Department of Education.
The Department of Education must provide guidance for education decision-makers to evaluate AI solutions during procurement, to support EdTech developers to mitigate bias in their applications, and to develop new fairness methods.