Data Annotators: The Unsung Heroes Of Artificial Intelligence Development

How do you create a smart algorithm? Where and how do you get the data for it? What do you need for a pattern recognizing program to work well and what are the challenges? Nowadays, everyone seems to be building artificial intelligence-based software, also in healthcare, but no one talks about one of the most important aspects of the work: data annotation and the people who are undertaking this time-consuming, rather monotonous task without the flare that usually encircles A.I. Without their dedicated work, it is impossible to develop algorithms, so we thought it is time to sing an ode to the superheroes of algorithm development: data annotators. Pattern recognizers in the quest to make healthcare better By now, there’s no corner of the universe where artificial intelligence and smart algorithms have not appeared. Or at least the hype around them. The IDC projected that global spending on A.I. will reach $35.8 billion in 2019. The technology parades as the next Mozart you’ll listen to in awe, the next Cézanne you admire in the MoMA, as a compliant servant built into the oven, who texts the family when dinner is ready, or as a teaching assistant responding to your routine queries in an online course. There’s even an app which “helps you” judge the attractiveness of thousands of faces taken from This Person Does Not Exist, which generates fake portraits by mimicking details found in real photos. Obviously, artificial intelligence or rather its most feasible ...
Source: The Medical Futurist - Category: Information Technology Authors: Tags: Artificial Intelligence in Medicine Future of Medicine AI algorithm annotation data data annotation doctor Health Healthcare physician smart algorithm technology Source Type: blogs