New Jersey Diversity, Inclusion, and Elimination of Bias CLE Courses

This program will help attorneys understand the causes and forms of unconscious bias and give them the tools the need to confront and mitigate their own biases.

This seminar will explore Rule 8.4(g), bias, and civility in the legal profession.

This program will inform attorneys on how a harmful quid bro quo culture can be recognized in their workplace, and give practical instruction on how to break down these types of barriers if they exist.

From discrimination, harassment, and implicit bias, there are a number of legal and ethical challenges arise in having a workforce that spans multiple generations. This program will help lawyers address these challenges and support a work environment that is inclusive, productive, and legally compliant.

This program will help provide answers for creating and maintaining more tolerant, legally compliant workplaces and other organizations.

This seminar will delve into the school of thought of “if you have a brain, you have a bias”. We will explore bias in the legal profession from representing clients, managing a law firm, and internal promotions.

This course examines the constitutional foundations, evolution, and current status of affirmative action under the Equal Protection Clause of the 14th Amendment.

This seminar is designed to equip legal professionals with the knowledge and tools to recognize and address implicit biases, combat microaggressions, and cultivate inclusive workplace cultures.

This seminar provides an overview of the CROWN (Create a Respectful and Open World for Natural Hair) Act, which prohibits hair texture discrimination in the workplace and schools.

This program will focus on the the CROWN Act as it applies to employment law, covering current case law and pending CROWN Act legislation.

This course unpacks the origins and definitions of bias through legal, psychological, and sociopolitical lenses.

This course will provide an overview of algorithmic bias, including the basics of how biases can be embedded in AI algorithms and their general effects and their legal implications.