understand what outputs it is giving you , and whether that compares with what you expect . “ That ' s no different with an AI model or AI system ,” he added .
“ It ’ s important for inputs to any AI system to be properly understood . We call that , in a technical sense , exploratory data analysis , which looks at the statistical variance and gaps with the data set to understand what we can reasonably do with this data and what we cannot ?”
Software should be lawful , ethical and technically robust “ As technology and AI are becoming part of our lives more and more , we have to ensure that people view these tools , and the companies and institutions that utilise them , as lawful , ethically adherent and technically
“ MOST MODERN-DAY AI IS JUST A BLACK BOX ”
RAMPRAKASH RAMAMOORTHY DIRECTOR OF AI RESEARCH , MANAGEENGINE robust ,'' said Benedetta Cevoli , Data Science Engineer , Speechmatics .
“ AI should be honest and , consequently , trustworthy at all levels – from its inception to deployment . Creating such a system requires a deep understanding of its application in the real world and the extent to which individual differences of users , such as age , race , gender , location and language , influence their experience with the tech . Keeping these differences right at the centre of product development with a genuine drive to address these issues , before technology is disseminated throughout society , is a way to build trust with the public ,” she said .
Bias has multiple shapes and forms , existing in many different aspects . Oftentimes , we are not even aware of it ,
132 August 2022