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On-Demand

Breaking Implicit Bias: Leveraging Narratives to Counteract Bias in the Judicial System

Credits: –
Credit Type: General Credit
Participation: On-Demand
Practice Areas: Access to Justice, Diversity and Inclusion, Diversity, Inclusion and Elimination of Bias, Equity in Justice (NM), Equity, Diversity and Inclusivity (EDI), Equity, Inclusion and Mitigation of Implicit and Explicit Bias (WA), Ethics, Implicit Bias, Professional Conduct, Professionalism
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Part 1. Implicit bias plays a significant — yet often unrecognized — role at nearly every stage of the legal system, influencing decisions from initial police contact through charging, pretrial determinations, trial strategy and sentencing.

Even well-intentioned legal professionals may unknowingly rely on unconscious assumptions shaped by personal experience, cultural exposure, and systemic norms, leading to unequal outcomes and diminished confidence in the justice system. This course explores the pervasive role of implicit bias in the U.S. judicial system and introduces narrative tools as strategies to counteract these biases. Drawing on psychological research, legal data, narrative theory, and real-world case studies, the session guides attorneys in identifying decision points where implicit bias can affect outcomes and offers practical interventions, including the use of client narratives and videos.

Learning Objectives

* Define implicit bias and distinguish it from explicit bias

* Identify key decision points in the legal process where implicit bias may emerge

* Understand how implicit bias impacts decisions at arrest, charging, pretrial & sentencing

* Recognize the influence of personal experience and background on legal decision- making

* Use narrative-based mitigation strategies to humanize clients and challenge biased assumptions

* Apply the Implicit Association Test (IAT) to assess and reflect on personal implicit bias

The speakers include: Rebecca Grace, Professor Matthew Claire, PhD., Hon. Judge Mark W. Bennett, Prof. Leticia Saucedo, Shawn Marsh, PhD., Omkari Williams and Shari Rusk.


Credit Type
General Credit

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