With the much heralded GDPR, General Data Protection Regulation, now in place, a great deal has been revealed about what good data privacy hygiene looks like. That involves collecting and storing as little information as possible so that exposure is minimal and ensuring consumer rights to revocation or transportation can be accommodated easily. This marks a U-turn for most forward-leaning organizations. These companies are transitioning from taking snapshot backups every hour and storing those backups in ever-cheaper cloud storage, worrying about the exposure later, to now actively changing policies to take more thoughtful backups and not retain that information longer than necessary.
Now, shift the focus to IoT. IoT is everywhere, from Industrial to Healthcare to Consumer, and the one crucial ingredient that underpins the success of AI with IoT is large swathes of data. The more data there is, the better the algorithms can be trained. Autonomous cars are a great example. In order for these cars to determine a street light from a tall, thin man, they need to have seen enough street lights in daylight, dusk, and night. The tall, thin men should represent all races so the car has enough skin-color data sets to make the algorithm effective. And that requires lots of data.
Therein lies the conflict. The regulation and privacy gurus will be advocating for limiting the amount of data collected in order to provide for a safer and more trustworthy customer experience. The IoT and AI engineers and business owners will be pulling the wagon in the opposite direction in order to make the AI more effective and extract ROI from their IoT deployments.
12:40PM - Day 1