Alejandro Saucedo, engineering director at Seldon, discusses the need for fit-for-purpose regulation when it comes to humane AI
AI can be humanity’s greatest tool in eliminating systemic bias, but we’ll need to be honest with ourselves and each other to confront our pre-existing biases.
The railway sector is facing new risks - the recent adoption of artificial intelligence (AI) and deep learning systems have introduced new challenges.
If there are biases inherent in real-world data, AIs trained on that data get inculcated with those biases. We asked leading researchers 5 key questions about building AIs that behave with ...
In order to avoid bias in artificial intelligence, fair and transparent decisions will be needed to build confidence in AI systems.
Ideas, updates and news about the CDEI
The research papers introduced in 2019 define comprehensive terminology for communicating about ML fairness, go from general AI principles to specific tensions that arise when implementing ...
I’m amazed at how rapidly the process of hiring employees and looking for work is changing. For generations, a big part of that process has been a person’s connections.
Algorithms must be responsibly created to avoid discrimination and unethical applications.
Tech companies that have implemented algorithms meant to be an objective, bias-free solution to recruiting more female talent have learned this the hard way.
Human bias is often developed into AI. To fix this, we need a fundamental rethink of the assumptions underpinning this vital technology.
Companies “need to change the way they motivate people in environments where parts of their jobs are done by AI,” argues a Stanford economics professor.
AI has powerful potential in business, but before you implement it, you need to consider the risks and how to mitigate them.