Artificial intelligence is suddenly everywhere. Fueled by huge technological advances in recent years and gobs of venture capitalist money, AI has become one of the hottest corporate buzzwords. Roughly 1 in 7 public companies mentioned "artificial intelligence" in their annual filings last year, according to a Washington Post analysis. But the term is fuzzy. "AI is purposefully ill-defined from a marketing perspective," said Alex Hanna, director of research at Distributed AI Research Institute.

This study examined the use of voice recognition technology in perioperative services (Periop) to enable Periop staff to record workflow milestones using mobile technology. The use of mobile technology to improve patient flow and quality of care could be facilitated if such voice recognition technology could be made robust. The goal of this experiment was to allow the Periop staff to provide care without being interrupted with data entry and querying tasks. However, the results are generalizable to other situations where an engineering manager attempts to improve communication performance using mobile technology. This study enhanced Google's voice recognition capability by using post-processing classifiers (i.e., bag-of-sentences, support vector machine, and maximum entropy). The experiments investigated three factors (original phrasing, reduced phrasing, and personalized phrasing) at three levels (zero training repetition, 5 training repetitions, and 10 training repetitions). Results indicated that personal phrasing yielded the highest correctness and that training the device to recognize an individual's voice improved correctness as well. Although simplistic, the bag-of-sentences classifier significantly improved voice recognition correctness. The classification efficiency of the maximum entropy and support vector machine algorithms was found to be nearly identical. These results suggest that engineering managers could significantly enhance Google's voice recognition technology by using post-processing techniques, which would facilitate its use in health care and other applications.

Advanced computer programs influence, and can even dictate, meaningful parts of our lives. Think of streaming services, credit scores, facial recognition software. As this technology becomes more sophisticated and more pervasive, it's important to understand the basic terminology. People often use "algorithm," "machine learning" and "artificial intelligence" interchangeably. There is some overlap, but they're not the same things.

New York police must now comply with a public records request related to its use of facial recognition and other surveillance on protestors. A judge has ordered the New York Police Department to release documents pertaining to its monitoring of Black Lives Matters protests during the summer of 2020, requiring it to release 2,700 emails and other documents to the public or state why it fall"and/or allege with specificity that each document falls within one of the enumerated exemptions of Public Officers Law." The NYPD previously rejected a Freedom of Information Law (FOIL) request by Amnesty International and the Surveillance Technology Oversight Project for records related to its use of facial recognition and surveillance tools on activists (as well as a subsequent appeal to that FOIL request), leading both groups to sue the law enforcement organization last year. The police agency has argued that the records request would cover over 30 million documents, and that following through would be "unreasonably burdensome." In a ruling issued on Friday, New York Supreme Court Justice Lawrence Love rejected the NYPD's reasoning.

A delivery driver who is suing Uber Eats in London over his dismissal from the company and claims its facial recognition technology is racially biased says the company treats couriers as "numbers rather than humans". Pa Edrissa Manjang worked for Uber Eats between November 2019 and April 2021 while employed full-time as a financial assistant. When Manjang first began working for the company he was not regularly asked to send in pictures of himself for verification purposes. However, these facial verification checks became more frequent. Manjang was eventually dismissed from the company by email, when it claimed there were "continued mismatches" between the pictures he took to register for a shift and the one on his Uber work profile.

Mobile technology has been revolutionized with the recent incorporation of artificial intelligence (AI). Nowadays, you can do many different things on your phone ranging from sending texts while you're driving to reading emails at the grocery store. There are so many ways AI has changed mobile life for the better: ordering groceries from home and taking care of important tasks during lunch breaks. This article describes how AI transforms mobile technology. AI refers to a computer's ability to perform tasks normally associated with human intelligence.

One of the disruptive technologies that has gained increasingly more attention after the turn of the century is Machine Learning. Machine Leaning – closely related and usually considered as a subfield of Artificial Intelligence (AI) – is the process of automatic detection of usable patterns within data. The detection of these patterns is performed with the help of machine learning algorithms which are specifically tailored to deal with complex and large data sets. Such powerful algorithms have the potential of drastically revolutionizing the way of doing business and how businesses operate. With this article I will provide an overview of opportunities that machine learning algorithms and Artificial Intelligence (AI) pose to the business environment.

With the help of a facial recognition system, federal agents could capture a man suspected of abuse. The tool detected him in the background of someone else's photo at the gym, in the mirror. So, the agents were able to get to that gym, ask about the man, and eventually capture him. This real-life story, and many others, encourage businesses to benefit from AI services and deploy facial recognition systems. The global facial recognition market size was evaluated at $3.8 billion in 2020 and is expected to reach $8.5 billion in 2025, growing at a CAGR of 17.2%.

The US national tax authority announced Monday that it will stop using facial recognition software to verify taxpayers' identities when they create online accounts, following a chorus of privacy concerns. Internal Revenue Service officials had put forth the authentication system as a security measure following years of growing fears over online scams and identity theft, but the program ended up also prompting worries. The initiative involved identity verification company ID.me, which won a nearly $90 million contract to make taxpayers' accounts more secure. The IRS said "it will transition away from using a third-party service for facial recognition to help authenticate people creating new online accounts." "The IRS will quickly develop and bring online an additional authentication process that does not involve facial recognition," it said, as the agency faces staffing shortages and significant backlogs.

Flying into Dallas Fort Worth International Airport from Mexico in December, I queued in the immigration line for US citizens and was taken aback when – rather than request my passport – the Customs and Border Protection (CBP) agent simply instructed me to look at the camera and then pronounced my first name: "Maria?" Feeling an abrupt violation of my entire bodily autonomy, I nodded – and reckoned that it was perhaps easy to lose track of the rapid dystopian devolution of the world when one had spent the past two years hanging out on a beach in Oaxaca. A CBP poster promoting the transparent infringement on privacy was affixed to the airport wall, and featured a grey-haired man smiling suavely into the camera along with the text: "Our policies on privacy couldn't be more transparent. In my case, the process was not so fast, as I had to hand over my passport for physical scrutiny after I raised the agent's suspicions by being unable to answer in any remotely coherent fashion the ...