)
Practical solutions to combating bias & discrimination in lending decisions
Dec 06, 2023
Room 1A22
Finance Stage
- Though AI is beneficial from an automation standpoint, it can sustain bias and unfair lending practices and prevent historically disenfranchised groups from participating equally in our financial ecosystem
- What are the ways we can combat this?
- Discussion centers around data augmentation with synthetic data models, regular bias testing, building fair and transparent algorithms for training and education and more
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
)
)
){kind=logo}
){kind=logo}
){kind=logo}
)
)
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
)
){kind=logo}
)
){kind=logo}
)
){kind=logo}
)
)
-(1).png/fit-in/500x500/filters:no_upscale()){kind=logo}
){kind=logo}
){kind=logo}
)
.svg){kind=logo}
)
)
){kind=logo}
.jpg/fit-in/500x500/filters:no_upscale())
){kind=logo}
.jpg/fit-in/500x500/filters:no_upscale())
)
)
){kind=logo}
)
){kind=logo}
){kind=logo}
)
)
)
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
.png/fit-in/500x500/filters:no_upscale())
)
.png/fit-in/500x500/filters:no_upscale())
){kind=logo}
){kind=logo}
.png/fit-in/500x500/filters:no_upscale())
