It's unclear how many law-enforcement groups are currently using Amazon's technology; it has been used by police departments in Florida and Oregon. An Amazon spokesperson said the company doesn't share customers' names or use cases without their permission. The company also said it supports "calls for an appropriate national legislative framework that protects individual civil rights and ensures that governments are transparent in their use of facial recognition technology." Amazon is the latest major tech company to indicate its support for such legislation. Microsoft has also said it is in favor of laws that regulate how facial-recognition technology can be used.

A new WIPO flagship study has documented a massive recent surge in artificial intelligence-based inventions, with U.S.-based companies IBM and Microsoft leading the pack as AI has moved from the theoretical realm toward the global marketplace in recent years. The first publication in the "WIPO Technology Trends" series defines and measures innovations in artificial intelligence (AI), uncovering more than 340,000 AI-related patent applications and 1.6 million scientific papers published since AI first emerged in the 1950s, with the majority of all AI-related patent filings published since 2013. This inaugural Technology Trends report provides a common information base on AI for policy and decision makers in government and business, as well as concerned citizens across the globe, who are grappling with the ramifications of a new technology that promises to upend many areas of economic, social and cultural activity. "Patenting activity in the artificial intelligence realm is rising at a rapid pace, meaning we can expect a very significant number of new AI-based products, applications and techniques that will alter our daily lives – and also shape future human interaction with the machines we created," said WIPO Director General Francis Gurry. "AI's ramifications for the future of human development are profound. The first step in maximizing the widespread benefit of AI, while addressing ethical, legal and regulatory challenges, is to create a common factual basis for understanding of artificial intelligence. In unveiling the first in our "WIPO Technology Trends" series, WIPO is pleased to contribute evidence-based projections, thereby informing global policymaking on the future of AI, its governance and the IP framework that supports it," said Mr. Gurry.

For the ongoing series, Code Word, we're exploring if -- and how -- technology can protect individuals against sexual assault and harassment, and how it can help and support survivors. You walk through the door and set your bags on the floor. You pose for a selfie with your hotel room in the background, uploading it to Instagram with seemingly random hashtags. For your followers, the photo is a means of documenting your travels. For investigators, you've just taken a crime scene photo that might one day help them to track down victims of human trafficking.

This book has been adapted in large part from the author's doctoral thesis [Shortliffe, l 974b]. Portions of the work appeared previously in Computers And Biomedical Research [Shortliffe, 1973, l 975b], Mathematical Biosciences [Shortliffe, 1975a], and the Proceedings Of The Thirteenth San Diego Biomedical Symposium [Shortliffe, l 974a]. To Stanford's Medical Scientist Training Program, which is supported by the National Institutes of Health Contents

Edward H. Shortliffe Chapter 6 Details of the Revised Therapy Algorithm

Shelf-mounted cameras paired with artificial intelligence facial recognition software that can identify a person's age, gender, and ethnicity were one of the emerging systems being pitched to retail companies during this year's National Retail Federation Big Show in New York in January. The idea was to give physical stores demographic information that could guide how they market to individual customers. It's something that could give them a competitive edge against online retailers such as Amazon, that have been leveraging customer data all along. But using cameras to capture photos of your customers in a way they may not even notice seems like it could be crossing that line between cool technology and creepy technology. Beyond that, there could be other problems, too. What if the software misidentifies a man as a woman and offers him a discount on feminine hygiene products?

One photo of a child in a hotel room can often be the only clue to a trafficked child's whereabouts. An artificial intelligence is now helping investigators to identify these hotel rooms, leading to the rescue of a number of sexually exploited children. Globally, an estimated 4.8 million people have been forced into sexual exploitation. More than 1 million are under 18. In the US, exploited children often appear pictured in hotel rooms in online adverts.

With version 2.1, IBM Machine Learning for z/OS is rebranded to IBM Watson Machine Learning for z/OS. It offers a hybrid cloud approach to model development and model deployment lifecycle management and collaboration that is designed to help organizations innovate and transform on an enterprise scale. It helps data scientists more quickly develop, deploy, and monitor behavioral models that continually learn as new data is introduced. IBM Db2 AI for z/OS, V1.2, a separately licensed product, uses machine learning to improve the operational performance of Db2 for z/OS systems. Watson Machine Learning for z/OS, V2.1 is a key component for operationalizing machine learning models on z/OS. It provides the ability to deploy models on z/OS that were developed and trained in the cloud, on IBM Z or on non IBM Z platforms. This provides greater deployment flexibility through a new architecture where model management, administration, and scoring services install and execute on z/OS. The new version includes capabilities that were previously separately available through IBM Open Data Analytics for z/OS to help simplify the acquisition, installation, and configuration of the product. Watson Machine Learning for z/OS provides an environment that fosters collaboration to enable innovation and transformation on an enterprise scale.

Google CEO Sundar Pichai brought good tidings to investors on parent company Alphabet's earnings call last week. Alphabet reported $39.3 billion in revenue last quarter, up 22 percent from a year earlier. Pichai gave some of the credit to Google's machine learning technology, saying it had figured out how to match ads more closely to what consumers wanted. One thing Pichai didn't mention: Alphabet is now cautioning investors that the same AI technology could create ethical and legal troubles for the company's business. The warning appeared for the first time in the "Risk Factors" segment of Alphabet's latest annual report, filed with the Securities and Exchange Commission the following day: "New products and services, including those that incorporate or utilize artificial intelligence and machine learning, can raise new or exacerbate existing ethical, technological, legal, and other challenges, which may negatively affect our brands and demand for our products and services and adversely affect our revenues and operating results."

Overinnovation can be a distinct problem, and it may be infecting the fast-growing and competitive AI industry, said Shawn Rogers, senior director of global enablement, digital content and analytic strategy at integration and analytics vendor Tibco Software Inc. Businesses in just about every sector are deploying AI and intelligent automation in their workflows, and a growing number of vendors sell AI products and services. As AI users and AI vendors seek to beat the competition by offering the latest and the best, they risk overinnovating -- knowingly or inadvertently sacrificing safe and ethical practices to better meet the perceived needs of their clients. An AI user, for example, may replace human workers with automated ones or use a recommendation system that provides more personalized choices to customers but collects and uses more of their information. Conversely, an AI vendor might train a machine learning model with biased data or create AI-assisted healthcare software that doesn't comply with the HIPAA privacy standards established under the Health Insurance Portability and Accountability Act. President Donald Trump has now ordered U.S. government agencies to develop new regulatory approaches on AI.