Diversity & Inclusion

Wayfair’s KeyAnna Schmiedl discusses how culture and inclusion are foundational to organizational learning.

Lyft’s Craig Martell talks education, eliminating bias, and cross-functional collaboration on machine learning projects.

Sponsors can play a role in growing and strengthening the pipeline of women leaders in organizations.

Making diversity and inclusion real, clarifying pandemic data, and how Amazon will innovate post-Bezos.

Why diversity and inclusion efforts often fail to produce the intended changes, and proactive approaches leaders can take.

It takes deep commitment and involvement to develop a brand strategy that embraces racial justice.

Digital transformation efforts are most effective when leadership priorities reflect an organization’s cultural values.

How to identify high-potential employees within your organization using an inclusive approach.

Latia Curry outlines the steps a brand should take to communicate their values to customers.

The most important factor in attracting and retaining women in the tech sector is having an inclusive workplace culture.

Siloed corporate social responsibility responses are insufficient to tackle structural inequities.

Last year’s challenges underscore that humans work best if they work as a team for a common purpose.

Crisis-driven innovation, self-sufficient production, and data to boost diversity.

Collecting and analyzing the right employee data can help leaders build more equitable workplaces.

The highlight of the 2019-20 NBA season was a player-led response to the Black Lives Matter movement.

To show respect for individuality, leaders should support the use of personal pronouns in communication.

Why words matter in crucial conversations, alarming U.S. job trends, and how to make data meaningful.

Being overweight is highly stigmatized, but companies can take steps to help combat weight discrimination.

Businesses distracted by the language around racism should instead focus on taking steps to actively prevent it.

Protocols that are used to root out bias in AI tools can— and must — be turned on the industry itself.