Why the need for Regulation?
Algorithmic decisions are already crucially affecting our lives. The last few year, news like the ones listed below are becoming more and more common:
- “There’s software used across the country to predict future criminals. And it’s biased against blacks”, 2016 [source: ProPublica].
- “Amazon reportedly scraps internal AI recruiting tool that was biased against women”, 2018 [source: The Verge]
- “Apple Card is being investigated over claims it gives women lower credit limits”, 2019 [source: MIT Technology Review]
- “Is an Algorithm Less Racist Than a Loan Officer?”, 2020 [source: NY Times]
The controversy
Twitter was in the headlines recently for apparent racial bias in the photo preview of some tweets. More specifically, Twitter’s machine learning algorithm that selects which part of an image to show in a photo preview favors showing the faces of white people over black people. For example the following tweet, contains an image of Mitch McConnell (white male) and Barack Obama (black male) twice, but Twitter selects Mitch McConnell both times in the tweet’s preview photo.
This tweet went viral with (currently) 81K retweets, almost 200K likes and was covered in articles by BBC and CNN. It also…
Machine Learning models or “Black-Boxes”
There is no doubt, that machine learning (ML) models are being used for solving several business and even social problems. Every year, ML algorithms are getting more accurate, more innovative and consequently, more applicable to a wider range of applications. From detecting cancer to banking and self-driving cars, the list of ML applications is never ending.
However, as the predictive accuracy of ML models is getting better, the explainability of such models is seemingly getting weaker. Their intricate and obscure inner structure forces us more often than not to treat them as “black-boxes”, that is, getting their predictions in a…
Code4thought
Software, Software Testing, Algorithms,
