CREW Network Webinar: Data Fairness and Why it Matters in CRE

Date June 16, 2023
Location Zoom
Time 11 AM - Noon(CDT)

Gain insight into algorithmic bias, why it matters in commercial real estate, and what you can do

In this thought-provoking session, Revathi Greenwood, Head of Real Estate Optimization at Cushman & Wakefield, will provide valuable insight into:

  • The intersection of bias and data
  • How this bias impacts women and people of color
  • How embedded bias in data is perpetuating systemic issues, specifically bias/discrimination in algorithms and the impact of the outcomes
  • The definition of algorithmic bias and how it relates to commercial real estate
  • How to identify data biases in CRE and eliminate them

 

Registration details
Registration closes at midnight (Central) on Thursday, June 15th. A link to access the webinar will be sent to all registrants prior to the session. All registrants will also receive a link to the session recording.

PLEASE NOTE: This session will not be recorded or available after the webinar.
Be sure to attend live at 11:00 AM CDT on June 16 to view the webinar live.

Pair the webinar with networking
Gather a group of CREW members in your market and participate in the webinar and networking together for a flat fee.
Reminder: this session will not be recorded or available after the session.

$79 USD – individual member viewing
$179 USD – non-member individual viewing
$179 USD – unlimited member/group viewing
$279 USD – non-member group viewing

For assistance, please contact CREW Network at crewnetworkevents@crewnetwork.org or (785) 832-1808.

 

Moderated by:

Wendy Mann, CAE
CEO, CREW Network

Wendy Mann

 

Featured Speaker

Revathi Greenwood
Head of Real Estate Optimization
Cushman & Wakefield

Revathi Greenwood

Greenwood is the Head of Real Estate Optimization for Cushman & Wakefield with overall responsibility for the data strategy for the company. She leads an agile team of data analysts and scientists who are responsible for creating strategies, roadmaps, policies, and procedures that guide all decisions related to data.

READ BIO

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