siliconindia | | December 20188From self-driving cars, to robo-advisors, to facial recognition on mobile devices, it seems as if AI algorithms have taken over as the backbone of our new digital economy. The reality is that algorithms have always played a key role in our economy.From decades old navigational algorithms that routed planes, trains, and ships, to putting a man on the moon, the evolution of decision-making from human `gut-instinct' to a reliable and repeatable process has always been powered by sophisticated mathematical models and algorithms. Yet, recently, a `trust gap' has emerged and is starting to rattle the core foundation of mathematical modeling and algorithmic decision-making. One of the critical factors that seems to drive this trust gap is the inequality of skills between industries, when it comes to algorithmic know-how. The technology sector has been investing for decades in creating environments amenable and accessible to engineers, data scientists and mathematicians, while other industries have not necessarily focused on adopting the same conducive operating model where algorithmic science can live in harmony with lines of business. The result has been a deterioration of trust, fed by fear of the unknown around AI-technologies.Another important reason trust in data science and AI is being questioned is related to the issue of Algorithmic Fragility. Algorithmic fragility refers to the instability of algorithmic outcomes when the input data deviates ever so slightly from normalcy. The well acclaimed `Cat Classifier' by Google, known for the Deep Learning HAVE WE LOST TRUST IN AI-ENABLED MACHINES?By Sreekar Krishna, Managing Director - Data Science, Artificial Intelligence and Innovation, KPMG USIN MYOPINION
< Page 7 | Page 9 >