“It’s easier to program bias out of a machine than out of a mind.” That’s an emerging conclusion of research-based findings – including my own – that could lead to AI-enabled decision-making systems being less subject to bias and better able to promote equality. This is a critical possibility, given
Sometimes people get ill because something goes wrong with their body. Very often, the body self-heals by directing regulatory controls to rectify and normalize the thing that is making you feel poorly. This is the body’s autonomic nervous system and its actions are carried out while the human being is largely unconscious of events taking place. When an illness can’t be rectified autonomically, you take medicine, or go to the doctor.
Sometimes, computers go wrong too.
Rather than calling a doctor, we usually call an IT support engineer or attempt to reinstall and ‘patch’ the software code issues causing the performance defect to occur. Increasingly though, through the use of Machine Learning (ML) and an ability to codify best-practice methods for addressing software performance scenarios, we are able to allow software systems to self-heal in much the same way that the body flushes out problems. This is called autonomic computing and it happens while the human being (let’s call them the ‘user’) is largely unconscious of events taking place.