We're currently in a new era of data collection -- and that's for the better.

That's according to Angela Benton, the founder and CEO of Streamlytics, a company that collects first-party consumer data transparently and aims to disrupt the current model of third-party mining of data from cookies and other methods that raise privacy and ethics concerns. Most recently, she was named one of Fast Company's Most Creative People for helping consumers learn what major companies know about them and paying them for the data they create while using streaming services like Netflix or Spotify.

In the latest Inc. Real Talk streaming event, Benton explains that she founded the company with minorities in mind, particularly the Black and Latinx communities, because of the disproportionate way they've been affected by data and privacy. For example, she points to the recent controversy over facial recognition data being sold to the police, which has a much higher error rate when comparing data of Black and Asian male faces, which could potentially lead to wrongful arrests.

"That becomes extremely important when you think of what artificial intelligence is used for in our day-to-day world," she says, noting that A.I. is used for everyday interactions like loan applications, car applications, mortgages, and credit cards. Using her company's methods, Benton says, clients can secure ethically sourced data, so that algorithms won't negatively affect communities that have historically suffered from discriminatory practices.

Here are a few suggestions from Benton for finding data ethically without relying on third-party cookies.

Do your own combination of data sets.

"How [Streamlytics] gets data is very old school," Benton says. Instead of relying on tech to combine data points, she says, you can manually compare data you already own and make assumptions using your best judgment. You may have data from a Shopify website, for example, about the demographic of your customers, and then you can go to a specific advertiser, like Hulu, for instance, to then target people that fit that profile. 

Use your data to discover new products.

You can also look to your data to find common searches or overlapping interests to get ideas for new products, Benton says. Often, she says, she receives data requests from small-business owners to discover ideas that aren't currently on the market, for example, a vegan searching for a vitamin.

This combination method surprised Benton when she presented clients with data. "I thought it was going to be more focused on just like, 'How can I make more money?' " she says. "But we are hearing from folks that they want access to data to use it in more creative ways."

Don't take social-media data at face value.

Benton and her company purposely do not source social-media data because she thinks the data leave too much out of the full picture. You may get a customer's age and "likes" from a social-media page, but that doesn't tell you what they're searching for or what their habits are.

"That's not, to me, meaningful data. That's not where the real value lies," she says. "We're not focused on what people are doing on social media, we're focused on all of the activities outside of that." She gave a scenario where a consumer is watching Amazon Prime while also scrolling on Uber Eats to find dinner. Data signals are happening at the same time, but they're not unified. It's up to businesses to connect the dots. To Benton, that's more meaningful than what you're posting and what you're liking on social media.