JB
Jennifer Brown
Founder of Jennifer Brown Consulting
Dolly Chugh
Professor at NYU Stern School of Business and Author of The Person You Mean to Be
Behavioral Science · Bias · Ethical Leadership
Speaking Fee
Fee on request
Based In
United States
Signature Topic
The Psychology of Good People
Format
Keynote and Workshop
About Dolly
Dolly Chugh studies a problem that most bias training is badly designed for: the gap between the person someone believes themselves to be and the decisions they actually make.
Her research is on what she calls the psychology of good people. The finding that organizes it is that the strength of someone's belief in their own fairness is not evidence of fairness, and can work against it, because a person committed to being unbiased has a strong incentive to avoid evidence that they were. That is why training built on persuading people that bias is bad so often changes nothing: the audience already agrees, and agreeing is the defense.
The Person You Mean to Be: How Good People Fight Bias reframes the goal from being a good person, which is an identity to be defended, to being a good-ish person, which is a practice with room to be wrong in. It is a small shift in wording that makes the material usable, because it lets someone examine a decision without their self-image being the thing at stake. Her second book, A More Just Future, applies the same tools to reckoning with uncomfortable history.
She is the Jacob B. Melnick Term Professor at New York University's Stern School of Business, where she teaches leadership and management to MBA students and is faculty director of the NYU Stern Leadership Accelerator. Her TED talk on the subject has been widely viewed.
She suits an organization that has run inclusion training before and watched it produce agreement without change. The session is evidence-based rather than exhortative, which also makes it a comfortable booking for technical and analytical audiences who tend to resist the genre.
Keynote Topics
The Person You Mean to Be: How Good People Fight Bias
Good-ish: Why Believing You Are Unbiased Gets in the Way
Making Better Decisions Under Bounded Ethicality
A More Just Future: Reckoning With Difficult History
Best For
- Leadership development and MBA-style executive programs
- Technical and analytical audiences resistant to standard DEI training
- Company-wide inclusion and belonging events
- Ethics, compliance and decision-making conferences
- Manager cohorts and hiring committee training
Booking Dolly Chugh: Frequently Asked Questions
What is Dolly Chugh's speaking fee?
Dolly Chugh's fee is not published here and is quoted per event. It is driven by event date, location and travel, session length, and whether a workshop, executive session or advisory follow-up is added to the keynote. Submit an inquiry with your date and audience size for a current quote and availability.
What does good-ish mean?
A deliberate replacement for good person. Being a good person is an identity, and identities get defended, which is why evidence of a biased decision is so often rejected by exactly the people most committed to fairness. Being good-ish is a practice that assumes error, which lets someone examine a decision without their self-image being at stake.
How is this different from standard unconscious bias training?
Most bias training sets out to persuade an audience that bias is bad, and the audience already agrees, so agreement becomes the defense and nothing changes. This material starts from the finding that a strong belief in one's own fairness can work against fairness, and addresses decisions and processes rather than attitudes.
Does the research suit a skeptical or technical audience?
It is often chosen for exactly that room. The content is drawn from social psychology, behavioral science and organizational research and is presented as evidence rather than exhortation, which tends to land with analytical audiences who resist the usual register of the genre.
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Dolly Chugh
Professor at NYU Stern School of Business and Author of The Person You Mean to Be
Fee on request
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