In the previous two blogs, we showed how Artificial Intelligence and Machine Learning are useful tools only when used with good intentions, with cyber criminals actively employing current technology to their own advantage.
We ended by saying that AI and ML technology should be used not only to create better, faster and more advanced computers, but also to create better people.
But what does that mean exactly? How can we use a machine's learning ability to learn ourselves?
Everything you need to know about how AI and ML technology can help you protect your data: "Good cop, bot cop: the truth about AI, ML and your privacy"
To find out what we need to learn from Machine Learning, let's consider the relationship between us and computers. It actually boils down to this: machines make mistakes humans don't, and vice versa.
For example, a computer is perfect for calculating the square root of 4871 while us humans have the amazing power to ask why broccoli is green.
Somewhere in the middle is the sweet spot where the unimaginative power of a computer negates our own fantastic flaws. Knowing how to use Machine Learning to thwart cyber crime is merely knowing where the shortcomings of humans and machines meet.
When it comes to cybersecurity, the main cause of data breaches is human error (in 82% of the cases, according to the latest Verizon report). Accidentally sending an email to the wrong person, confusing the CC field for the BCC field, or attaching the wrong file by mistake are the main reasons sensitive data ends up falling in the wrong hands.
We often don't realize we're making a mistake when sending an email. Fortunately, Machine Learning is very capable in spotting possible errors and warning people of them, before it's too late.
Here's how something as complex and advanced as Machine Learning is used to make us better humans, by meeting us at that sweet spot where humans and computers perfectly complement each other:
Imagine you're writing an email on a very busy day. You can't really be bothered to check what you're doing, but luckily your computer constantly checks your content and determines what type of security is needed to send it safely.
The result of this kind of Machine Learning in action is that you, as a user, don't have to worry about email security. Every time the computer senses the slightest hint of a security risk, you simply get a notification that your email will be sent securely.
Better yet, the more you're backed by a computer that prevents you from making any errors, the more aware you'll become of basic best practices that help prevent data breaches. In other words, use Machine Learning technology long enough, and it'll turn you into a cyber security expert of sorts.
If you're familiar with using Smartlockr, you'll already know it allows you to send emails as you normally would. Only when our Machine Learning technology picks up content that could be sensitive, or when you're about to send an email to an unfamiliar address, does the Smartlockr toggle come into action:
Considering the average data breach costs USD 4.4 million, it's difficult to overstate the importance of the toggle that prevents this.
As an extra benefit, the more people use Machine Learning to prevent human error, the better algorithms will get at detecting it. We use Machine Learning technology to help us become better people, but by the same token we improve the effectiveness of Machine Learning technology, simply by using it.
And the best part: there's nothing cyber criminals can do about it!
Want to know everything about how to use Artificial Intelligence and Machine Learning to prevent data breaches? Click on the link below to download our free whitepaper: "Good cop, bot cop: the truth about AI, ML and your privacy".