We like to think of data as being objective, but the answers we get are often shaped by the questions we ask. Beyond that, the data sets themselves could also be limited or biased. As algorithms take over many of our decision-making processes, it matters more than ever which assumptions we build our models on. If data containing inherent bias is used in self-learning systems, the bias will be magnified. Beyond deciding which music you listen to, other impacts could include your next job, your health care eligibility, insurance premiums and credit ratings.

Our SheSays NY team is hosing this panel and by joining this great discussion you will:

Understand data bias
Deep dive into 1-2 examples
Learn more about what you can do to influence or change this paradigm

Panelists include:

Amy Bucher, VP Behavior Change Design @ Mad*Pow (Boston)

Tiffany Johnson, Senior Director, Tech & Data Analytics @ Wunderman (NYC)

Adah Parris, Futurist, Keynote Speaker, Cultural Strategist (London)

Arielle Patrick, Executive VP & Transaction Director @ Edelman (NYC)

Jennifer L. Williams, Principal @ The J.L. Solution (NYC)

Panel moderated by SheSays NY Board Member:

Elizabeth Kiehner, Digital Transformation Officer @ Memorial Sloan Kettering

Looking forward to seeing you there.

The SheSays Global team

Link to this event will be available at the start time (on the online event page). Start time by zones for this event are:

1pm EDT (East Coast US)

6pm BST (UK)

10am PDT (West Coast US)

AI & Bias: Closing The Data Gap