As the number of applications for artificial intelligence and machine learning increases and the reach of those products increases, the importance of diversity in the industry remains critical. Capital One sponsors the Women in Data & Artificial Intelligence Breakfast Panel.
JoAnn was the Chief Data Officer at Mastercard. It is important that we have a variety of thought in the data. If we want our products to reflect the society that we all want to live in, we need data scientists and other data professionals at the design sessions.
Mastercard's data design principles show the baseline that employees need to aim for when designing with data Privacy and security, accountability and transparency are just some of the things that are important to innovation and integrity. They have added a new addition to the list.
She said that inclusion means inclusive data sets of all the right kinds of data, inclusive inquiry to get to the right type of inputs, and then to get the right answers about what you're trying to solve. A lot of detail goes into that. They created an inclusive methodology for our data practices and for our artificial intelligence.
"We're trying to tailor the best, most personalized, most helpful experience for our customers."
Staying sensitive to harmful biases is something that needs to be done.
Humans are the best way to do that. It is the best way to represent the people we are talking to on the other side of the device. We have gotten machines to a place where we can train them and they are doing all of these things in less than an hour. Before it can meet a customer, it needs to be inspectability and that human-trained angle.
The head of data and artificial intelligence at LinkedIn said that responsible design approach is the foundation of everything.
She said that it wasn't just about checking if the data is balanced. Is there a responsible design concept to begin with? It is this human-centered approach that JoAnn and Molly have used. It is so critical that we look at how we are building and evaluating.
She said that you need to think about how this is affecting your customer. Every feature launch at LinkedIn is evaluated by the team to see how it will affect segments.
As we continue to evolve and improve our product, we want to make sure we don't introduce these consequences. It is ingrained in the way we develop our products.
It costs a lot to not increase diversity in the space. The other outcome is alienating half of your customers or members. There is an attempt to correct bias without actually looking at the source. Regulation will affect innovation.
The biggest risk for Stonier is getting it right. People don't want to get fraud right. One of the easiest ways to get an artificial intelligence to be wrong is to not pay attention to biases. Laddering up to constant gender-coding, which boxes kids into very specific roles, and eventually into very specific careers and opportunities, is something as simple as an artificial panda image.
"If we don't want that future, then we have to pull those types of proxy variables out of our thinking." We need to look at all of the subtle ways that global societies have made gender and other biases part of our language. Things are limited by getting it right.
The call for gender diversity in the industry needs to be unified according to thePanelists. The tech industry is only 20% to 25% women, so it's a must to bring along male allies, and a must that they are as passionate and excited by this as women. Men are worried about making mistakes.
She said that they are a little worried about how they are seen. Everyone is going to make mistakes. It is difficult to do responsible artificial intelligence and this space. Men and women will both say the wrong things. We all want to achieve the same things.
It's a huge part of getting it right to include inclusion into the dialogue. That is what we need to promote, whether that is with regulators or with our partners. She says that there is still bias around who should contribute and who should have the louder voice.
The call to action is something she likes a lot. How do we get all of the voices out so we get the best design? That is part of the way that we build.
A woman-led inclusion conversation can be powerful, but real diversity is where the most power is.
I like that the Mastercard team is all different faces. She said that there were different races and different ethnicities. All of you should invite your colleagues to the table to have a conversation with you about this topic.
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