Since the dawn of the age of computers, human beings have wondered what will happen when the machines eventually learn how to "think" like humans do. The consensus among science fiction writers is "nothing good." Whether they rise and destroy humanity outright, or insert our consciousness into a giant simulation of the late 1990's to turn us into biomechanical batteries, depends on the creative imaginations and special effects budget of whoever's telling the story. But rare is the writer or director who tells a story about how human beings built thinking machines -- and everything turned out just great. Until recently, however, these were mostly the concerns of those who worked in fiction -- since the technology available wasn't up to causing an apocalypse.

No, when it comes to the biggest immediate impact that artificial intelligence (AI) will have upon the world, financial services will likely take that honor -- a looming prize that provides fresh opportunity to consider how machines will overcome bias. Anyone who reads the news or follows science fiction knows how important AI is becoming to business, and how much change it will almost certainly bring to civilization. However, Sunil Madhu, founder and chief strategy officer of online security and predictive analytics firm Socure, told Karen Webster during a recent podcast interview that bias remains a vital issue for the future of AI and machine learning. After all, he said, "human bias cannot be trained out," especially since the majority of human decision making, according to the latest scientific findings, is governed by the biological, chemical and electrical mechanics of the subconscious. People don't even know what they know, or how they end up knowing what they know.

Socure CEO Sunil Madhu will discuss the powerful impact that artificial intelligence and machine learning are having on the world of financial services and online businesses at this week's Connect:ID exhibition. Entitled "Leapfrogging: The Impact of Machine Learning on ID Verification", the session is scheduled for May 1st at 10:50 a.m., and will be held in the Silver Room of the Walter E. Washington Convention Center. In a statement announcing the talk, Socure asserted that AI and machine learning "far exceed human intelligence and intuition, and can verify the identity of the person on the other end of an online transaction and detect fraud." Indeed, particularly when applied to biometrics, AI and machine learning technologies are proving to be highly effective across a range of identification applications, from remote customer onboarding to mobile payments. But, as Madhu will explain in his session, "there are limitations, shortcomings and misapplications of data science which can impact results." Madhu's session promises to delve into the AI and machine learning approaches that work best.

Predictive analytics for digital identity verification firm Socure has announced CEO Sunil Madhu will present at the upcoming connect:ID 2018 conference in Washington, D.C. Madhu will discuss the impact of artificial intelligence and machine learning on online identity verification and fraud prevention. "Artificial Intelligence and machine learning are leapfrog technologies, transforming the way banks, online businesses, and others are interacting with current and prospective customers". In this presentation, Sunil will explain which AI and machine learning approaches, techniques, and data elements are necessary to produce the most reliable and accurate results. He will also discuss how advances in data science are facilitating a transformational shift in online identification and fraud prevention, and what future impacts they will have on online banking, retail and more. In four years, connect:ID, powered by Science Media Partners and the International Biometrics Identity Association (IBIA), has become the world's premier event dedicated to all aspects of human identity technology and its implementation in the digital, mobile, and physical domains.

How do machines learn to learn? In Episode Three of PYMNTS' machine learning podcast, Socure CEO Sunil Madhu and PYMNTS CEO Karen Webster get technical as they explore the methods and processes that are making machines progressively smarter. In Episode Two, Madhu and Webster talked about different kinds of artificial intelligence (AI) and how each is equipped to handle certain kinds of jobs. An artificial neural network is good at pattern recognition, computer vision and speech or text processing, but the system lacks transparency, making it a no-go for financial institutions that are looking to detect fraud. For fraud prevention, an AI with linear pattern recognition is more useful.

Recently, Nasdaq Inc. announced the launch of a new service that looks to put a subset of artificial intelligence technologies toward growing investor profit. Called the Nasdaq Analytics Hub, the new service will leverage machine learning to sift through social media, central bank, retail sentiment and end-of-day trading data, deriving insight that fund managers and traders can then leverage to enhance investment strategies. "We back test the data using a number of strategies," Mike O'Rourke, global head of Machine Intelligence and Data Services at Nasdaq, told Reuters in an interview. "Then we use machine intelligence to add value-added analytics to the data that allows firms to make it more actionable." The newswire noted that financial technology startup Lucena Research scrutinizes the data, sourced from Nasdaq as well as a number of third-party providers.