Hiring managers already are using artificial intelligence with social media profiles to supplement general background screening. But now, a new artificial intelligence service, DeepSense by Frrole, enables professionals to do even more. The service creates an entire personality profile to give business leaders a bigger picture about the kind of individual you are, such as introverted, organized or which news media you prefer. It even offers tips about the communication style others should use with you.
What sets this particular AI apart
DeepSense's CEO, Amarpreet Kalkat, explains that DeepSense is fundamentally different from other AI services in that it doesn't focus merely on aggregating, cleaning and structuring data. Rather, it focuses on using the data it collects to make predictions. Employers thus aren't merely looking backward to figure out if you have something to hide--they're getting a sense of how you'd act in situations that haven't even happened yet.
DeepSense has clear value as an AI hiring software. Hiring managers can look at your profile, for example, to see if your personality and habits would fit well into the company culture, vision and goals.
"We are very sharply focused on helping organizations hire faster and better at this point of time. Our analysis suggests that DeepSense can provide a 20-30% improvement in recruiter productivity while also lowering 'overall time to hire' by a non-trivial, measurable margin as well. DeepSense makes it possible by letting AI do part of the evaluation (esp. that around cultural fit and personality) and weeding out the wrong candidates even before recruiters have to spend time speaking to them. It also makes this evaluation more objective and consistent, removing human bias.
We do believe that DeepSense would help organizations recruit employees who are a better role & organizational fit and would therefore show better performance and retention eventually. However, measuring this would require analysis of data from 12-18 months post an employee joining an organization. It is something that we have not had a chance to do yet."
But the artificial intelligence profiles also are especially handy for customer care. For example, if the profile tells a service representative you're more sensitive, the representative might be more careful of how they phrase what they tell you or offer more reassurance during the service process.
Kalkat also notes that, while it's not currently a major focus point, DeepSense does have potential marketing value, as well.
"A company could use DeepSense to create 360 degree profiles for all of their customers or potential prospects," he says. "The company would need to have either email ID or phone number of the customer as an identifier. DeepSense can potentially match these identifiers to publicly available social profiles and then use the public social data to construct a profile for each individual. The profiles can then be made available to the company through the DeepSense APIs."
But can you trust it?
To date, DeepSense has raised roughly $500K via angel investors and seed funds. And the list of customers already includes big names like eBay, the Department of State, Kantar and the Smithsonian Institution. Part of that attention comes from the fact that DeepSense, while not perfect, has a decent degree of accuracy. Kalkat says the company only makes attributes available that have demonstrated an F-Score of at least 80 percent. As machine learning is part of DeepSense's processes, the product likely only will improve.
Tips for protection and authenticity
As the applications of artificial intelligence continue to expand, DeepSense isn't the only company exploring an artificial intelligence hiring process. For example, Unilever is testing algorithm-based sorting for job applications, combining AI with online games and video submissions. Services like DeepSense demonstrate that leaders also are taking AI in social media analytics seriously, and that consumers have to deal with the reality that companies are looking at public online data. To that end, Kalkat offers some advice.
"Try to be the same way online as you tend to be offline. If there is something that you would not say publicly in the real world, then you should perhaps not say the same thing publicly online, either. It is a fair assumption to make that your data would be analyzed either for in-house optimizations by the product that you are using or for 3rd party analysis if it is publicly available.
You should also demand more transparency around data analysis and redistribution from the products that you use. This would help ensure that the data collected gets used for creating experiences that truly benefit the consumer."