Traditional software development focuses on building applications to perform well defined tasks, whereas building artificial intelligence application requires teaching a computer to draw conclusions from provided information and act accordingly. Therefore Artificial Intelligence relies on giving a machine the right training data to learn for itself. If we teach a machine on biased training data we will emphasise the bias in today’s world.
It’s becoming more apparent that the ethical issues need to be addressed with recent case studies like Microsoft’s bot Tay which was trained on the Twittersphere and took less than 24 hrs for the AI to become a racist, sexist bigot. As well as Joy Buolamwini, MIT Media Lab researcher who found that a robot recognised her black face better when she wore a white mask and has since set up the Algorithmic Justice League.
We’ll also hear about the Why Women in AI initiative. In April 2017 Tabitha, CognitionX’s Co-Founder launched the campaign to encourage men and women to think about the risks of an imbalance in the training data, creation of and deployment of AI.You can watch the first event and read more here: https://cognitionx.com/women-ai-highlights/.