McDonald's is being sued for recording customers' biometric data at its new artificially intelligent-powered drive-thru windows without getting their consent. In court filings, Shannon Carpenter, a customer at a McDonald's in Lombard, Illinois, claims the system violates Illinois' Biometric Information Privacy Act, or BIPA, by not getting his approval before using voice-recognition technology to take his order. BIPA requires companies to inform customers their biometric information--including voiceprints, facial features, fingerprints and other unique physiological features--is being collected. Illinois is only one of a handful of states with biometric privacy laws, but they are considered the most stringent. A McDonald's customer in Chicago is suing the burger chain, claiming it records and stores users' voiceprints without their written consent, in violation of Illinois strict biometric privacy law In 2020, the fast-food chain began testing out using voice-recognition software in lieu of human servers at 10 locations in and around Chicago.
Sadly, I haven't been near Chicago lately and that's where the burger chain is testing this as yet imperfect system -- McDonald's confesses the robot only grasps your order 85% of the time. "Welcome to McDonald's," began exactly the same female robot voice you've heard every time you've tried to get through to a customer service operative at every internet provider/cellphone carrier/just about every business these days. The robot then asks if the customer wants anything else and invites the customer to "please full forward," because no mere human would know to do that. McDonald's is now being sued for allegedly recording voiceprint details of its customers at the robot drive-thru. The lawsuit claims that McDonald's makes the recordings "to be able to correctly interpret customer orders and identify repeat customers to provide a tailored experience."
But in the biggest ever study of real-world mortgage data, economists Laura Blattner at Stanford University and Scott Nelson at the University of Chicago show that differences in mortgage approval between minority and majority groups is not just down to bias, but to the fact that minority and low-income groups have less data in their credit histories. This means that when this data is used to calculate a credit score and this credit score used to make a prediction on loan default, then that prediction will be less precise. It is this lack of precision that leads to inequality, not just bias. The implications are stark: fairer algorithms won't fix the problem. "It's a really striking result," says Ashesh Rambachan, who studies machine learning and economics at Harvard University, but was not involved in the study.
AI can transform sourcing and screening from investors' pack mentality, to funding more female founders who build better products and services -- and create higher returns for investors. Venture capitalists know that their advantage lies in identifying the most promising opportunities before their competitors do. This is confirmed by a University of Chicago study by Morten Sorensen, which shows that investors create 60% of their value from the upper part of the funnel, specifically from sourcing and screening. In which case, sourcing and screening must be a constant target for improvement, right? No -- apart from a few VCs who have reinforced their sourcing with web crawlers, sourcing and screening practices have remained the same since the inception of the VC asset class around 1940.
The fast food giant has been testing out a Siri-like voice-recognition system at ten drive-thru locations in Chicago, CEO Chris Kempczinski revealed during a Wednesday investor conference attended by Nation's Restaurant News. The system can handle about 80 percent of the orders that come its way and fills them with about 85 percent accuracy -- probably annoying for the customers who just want to drive off with their burger -- but Kempczinski says a national rollout could happen in as soon as five years. It raises some interesting questions about the role that AI technology will play in various industries and, more importantly, the seemingly endless debate over whether raising the minimum wage to a livable salary will motivate CEOs to replace humans with machines -- or whether they'd do so to cut costs anyway. Part of the challenge in automating the drive-thru, Kempczinski said, is that human workers have been too eager to help out while supervising the technology that might one day replace them, preventing it from accruing the real-world data crucial for further improving the system. But as restaurant automation grows increasingly common, answering the question of how much responsibility a company has to continue employing people it could technically replace with machines will only grow more important and dire.
Next time you hit up a McDonald's drive-thru, you might find yourself leaning out your window to bark your order to a robot rather than a pimply teenager. The fast food giant has been testing out a Siri-like voice-recognition system at ten drive-thru locations in Chicago, CEO Chris Kempczinski revealed during a Wednesday investor conference attended by Nation's Restaurant News. The system can handle about 80 percent of the orders that come its way and fills them with about 85 percent accuracy -- probably annoying for the customers who just want to drive off with their burger -- but Kempczinski says a national rollout could happen in as soon as five years. It raises some interesting questions about the role that AI technology will play in various industries and, more importantly, the seemingly endless debate over whether raising the minimum wage to a livable salary will motivate CEOs to replace humans with machines -- or whether they'd do so to cut costs anyway. Part of the challenge in automating the drive-thru, Kempczinski said, is that human workers have been too eager to help out while supervising the technology that might one day replace them, preventing it from accruing the real-world data crucial for further improving the system.
Exhibitioners at the Century of Progress International Exposition held in Chicago from 1933-1934 touted washing machines and air conditioners as capable of bringing vast changes to our everyday lives. This optimism for future generations is inherent within the human psyche. As such, we often speak of artificial intelligence ("AI") as a lofty, almost dream-like reality that awaits us in the not-so-distant future. But AI proliferates today and extends beyond the entertainment-based efficiencies embedded within Netflix and TikTok that we read about; attorneys apply AI to document review projects; vehicle manufacturers use AI to control a vehicle's acceleration, speed and steering; hospitals and doctors are using AI to triage and diagnose patients; and biotech companies increasingly rely on AI to model the potential success of newly developed therapies and vaccines. Insurance carriers remain optimistic about the efficiencies to be gained by implementing AI-based applications into their workflows.
Angela Mitchell still remembers the night she nearly died. It was almost one year ago in July. Mitchell--who turns 60 this June--tested positive for covid-19 at her job as a pharmacy technician at the University of Illinois Hospital in Chicago. She was sneezing, coughing, and feeling dizzy. The hospital management offered her a choice.
I know I should be happy. I know I should be loving this idea as a sign of human progress. Why, then, am I a little concerned? Please forgive this apparently tangential meandering, but when you've been used to something being done a certain way, it's often hard to imagine a successful alternative. Yet here we are -- or, more precisely, here are a lot of people in Chicago -- about to face one of the more severe inevitabilities of our modern world: McDonald's is removing humans from taking your order at the drive-thru, in favor of a machine.
CHICAGO, April 15, 2021 (GLOBE NEWSWIRE) -- ModelOp, the pioneer of ModelOps software for major enterprises, today announces release of the first annual State of ModelOps report. Conducted by independent research firm Corinium Intelligence, the report summarizes the first ever research into the state of model operationalization and details the challenges faced by AI-focused executives from top global financial services companies as they scale their AI initiatives. Findings show that while AI is already widely deployed in many large enterprises and investments are growing, nearly 80 percent of surveyed executives reported difficulty managing risk as a barrier to AI adoption, and cite ModelOps as a key enterprise discipline that is receiving significantly increased attention and investment. The report is based on interviews with 100 executives from top global financial services companies in early 2021, providing a unique snapshot of the practices and future plans of large enterprises to govern and scale mission-critical AI initiatives. The findings were combined with commentary and insight from seven industry experts from organizations including Wells Fargo Asset Management, NY Life Insurance, BNY Mellon, FICO and others.