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V-Soft's Corporate Headquarters

101 Bullitt Lane, Suite #205
Louisville, KY 40222

502.425.8425
TOLL FREE: 844.425.8425
FAX: 502.412.5869

Denver, Colorado

6400 South Fiddlers Green Circle Suite #1150
Greenwood Village, CO 80111

TOLL FREE: 844.425.8425

Chicago, Illinois

311 South Wacker Dr. Suite #1710, Chicago, IL 60606

TOLL FREE: 844.425.8425

Madison, Wisconsin

8401 Greenway Boulevard Suite #100
Middleton, WI 53562

TOLL FREE: 844.425.8425

Atlanta, Georgia

1255 Peachtree Parkway Suite #4201
Cumming, GA 30041

TOLL FREE: 844.425.8425

Cincinnati, Ohio

Spectrum Office Tower 11260
Chester Road Suite 350
Cincinnati, OH 45246

Phone: 513.771.0050

Raritan, New Jersey

216 Route 206 Suite 22 Hillsborough Raritan, NJ 08844

Phone: 513.771.0050

Toronto, Canada

1 St. Clair Ave W Suite #902, Toronto, Ontario, M4V 1K6

Phone: 416.663.0900

Hyderabad, India

Incor 9, 3rd Floor, Kavuri Hills
Madhapur, Hyderabad – 500033 India

PHONE: 040-48482789

Bangalore, India

GINSERV, CA Site No 1, HAL
3rd Stage Behind Hotel Leela Palace
Kodihalli, Bangalore - 560008 India

Is Your Data Biased?

With more data available to us now than ever before, how we collect and interpret that data to make decisions has come under scrutiny. It's become clear that a factor known as Data Bias can negatively impact the decisions we thought we were making purely based on facts. During an episode of the weekly Virtual30 webinar series, Director of V-Soft Labs, Manoj Iragavarapu, shares more about what Data Bias is and how to prevent it.

What is Data Bias?

As strictly a definition, Data Bias is when a set of data points don't accurately represent the real population or environment. While it may not seem like a big deal, Data Bias can cause many problems. If the data is wrong, poor decisions can be made. 

For example, customer service virtual agents are trained on data points that help predict if a customer is happy or sad. If the virtual agent was given data points that say showing teeth and an upturned smile is the only way to know if someone is happy, that will exclude all people who have a neutral/resting face. This can cause agents to think that customers are mad or upset, which leads to inaccurate responses.

Three people with resting or neutral facial expressions.

Types of Data Bias

There are even different types of Data Bias ranging from biases in data points to biases of opinions of the interpreter or decision maker. Watch the video above to let Manoj explain the different types of Data Bias [Timestamp: 6:36].

  • Confirmation Bias 
  • Simpson's Paradox
  • Stereotype Bias
  • Modeling Bias
  • Sample Bias 

How to Prevent Data Bias

Now that it's understood how important it is to avoid Data Bias, there are a couple ways to prevent creating biased data. Data governance programs can be implemented to define how data is collect and used. Be proactive and strategic about ensuring all sample data is representative of the real environment. Use multiple sources of data to diversify the modeling. Make sure to define everything clearly in the collection process and get multiple people to review results. By following these steps you have less chance of creating biased data, which allows for more accurate decision making and automation processes.

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Topics: Automation, Healthcare chatbots, Video Blog

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