Artificial Intelligence (AI) and Data Visualization can seem like an unlikely marriage. AI techniques often work as a black box: we cannot know how the AI has reached its conclusion. This can raise uncomfortable questions: think of a medical diagnosis, or the screening of job applicants: if we cannot see inside the black box, we can’t know whether the AI made a serious mistake, or reflected our implicit bias. When the AI becomes a veil between us and the data it makes us uncomfortable and it takes our own intuition and insight out of the game.
But AI can help us see the data, becoming a crucial help to our own analysis and judgement.
Leo Meyerovich, CEO of Graphistry, discusses in this podcast interview a number of areas where AI-driven data visualization greatly facilitates the work of human analysts: from fraud prevention to health care, supply chain management, customer analysis, all the way to fighting human trafficking and spotting election-influencing tactics.
Across all these applications, says Leo Meyerovich, “The dream is some sort of a black box […but] I found zero systems that are fully automated.” There is always a human in the loop. Sometimes it’s to spot where the AI stumbles on a ‘false positive’, like a legitimate transaction flagged as fraudulent. Sometimes the analyst’s experience is invaluable to accelerate the process: the human knows what to look for and has a better sense of the context than the AI.
In all these fields, AI provides invaluable help. Human intuition, experience and decision-making continue to play the central role across economic activities. But now we have realized that data can help us make better decisions, and we have learnt to harvest and store prodigious quantities of data—so large that we struggle to make sense of them on our own.
Especially with the rise of complex global supply chains, most companies today are exposed to a very large number of evolving factors, from commodity prices to transportation costs to economic developments across the world (think of the recent impact of China’s growth slowdown). How can you capture the interrelated impact of all these factors on your business?