Dummy data is smart 💡 business. Why?

Responsible AI development and implementation requires tinkering, validation, and bias reduction strategies.

Synthetic data – dummy data as I like to call it, also referred to as human-engineered or mock data – helps with quick prototyping, demos, and also sandbox ⏳ training.

Most importantly, synthetic data can help ensure Responsible AI and smart business practices by:

1️⃣ PROTECTING PRIVACY

Synthetic data can shield sensitive info like medical records or financial data when performing demos or sprint reviews, for example.

45% of Americans have had their personal information compromised by a data breach in the last five years according to RSA Security so any productive measure to combat privacy violations is helpful.

2️⃣ REDUCING BIAS

Leveraging synthetic data creation to generate diverse datasets can aid in combatting the biased output of AI systems crunching historical data.

“Bias is the garbage in, garbage out problem of AI.” – Cathy O’Neil

3️⃣ FOSTERING RESPONSIBLE AI INNOVATION

Everyone wants to infuse operations with AI NOW. Dummy, or mock, data can accelerate development and experimentation safely – reducing data collection costs.

PROS AND CONS OF SYNTHETIC DATA

Of course, with 2 sides to every issue, concerns around synthetic data manifest. Please share your concerns when it comes to synthetic data in AI application development via the comments 👇!