A new story from MarTech Podcast

MarTech Podcast


Was maybe a one and needed to go to 5. And then psychology just became known as this thing that helps people who are very seriously ill. And we forgot about that aspect. So everyone in that aspect was like, oh, you're fine. Even though you're operating at a one and not a ten, you'll find you're not at minus ten. Algorithms have been operating in this minus area because they've only been benefiting certain people white men. Therefore, they have been able to build a large followings and build up this audience. So when the people who have been not benefiting from algorithms and systems come along, they're starting at a disadvantage. But it's not always transparent. However, don't quit me on where it came from, but there is some research out there that says individuals from marginalized backgrounds. When they do have a following, even if it's smaller, they're following tends to be higher engaged because there's less of those people to look to. That's an interesting thought that the algorithms that have been working for the last ten, 15 years in these social networks, bias towards people that they think are going to be able to help the social platforms, which are people that basically had an unfair advantage because of their demographics. Here's the other hard part that was figuring out our algorithm is let's say the score is a one out of a hundred score where a hundred is like we got to get this person on the podcast they're a real influencer and the average person is 50. I was sitting here saying how do I evaluate if we're going to give a boost towards people from diverse backgrounds or we want to be supportive of women in the martech industry? How do I quantify what type of boost they should get to be inclusive in our marketing efforts? Is it a 10% boost? Is it a 100% boost?.

Coming up next