In this episode of Uncanny Valley, we discuss our scoop about how the Department of Homeland Security illegally collected Chicago residents' data for month, as well as the news of the week. In today's episode, host Zoë Schiffer is joined by executive editor Brian Barrett to discuss five stories you need to know about this week--from how AI affairs can now be grounds for divorce, to why Google is suing one of the largest networks of text scammers. Then, we dive into how the Department of Homeland Security illegally gathered the data of hundreds of Chicago residents. If the US Has to Build Data Centers, Here's Where They Should Go This Is the Platform Google Claims Is Behind a'Staggering' Scam Text Operation AI Relationships Are on the Rise. Please help us improve Uncanny Valley by filling out our listener survey. Write to us at uncannyvalley@wired.com. You can always listen to this week's podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here's how: If you're on an iPhone or iPad, open the app called Podcasts, or just tap this link. Note: This is an automated transcript, which may contain errors. Today on the show, we're bringing you five stories that you need to know about this week, including our scoop about how the Department of Homeland Security, or DHS, collected Chicago residents' data for months in violation of domestic espionage rules. I'm joined today by WIRED's executive editor Brian Barrett.

Update, August 15, 5:50PM ET: The US Department of Homeland Security has issued a statement disputing some of MIT Technology Review's reporting. We've updated our post below with its statement and more details. The US Department of Homeland Security (DHS), which is looking to improve its facial recognition algorithms, is reportedly planning to use the facial data of migrant children entering the country for training. According to MIT Technology Review, the agency intends to collect and analyze facial captures of kids younger than 14. John Boyd, the assistant director of Homeland Security's Office of Biometric Identity Management who's involved in the development of biometric services for the government, told the publication that the collection will include children "down to the infant."

The Department of Homeland Security (DHS) on Thursday unveiled new guardrails for its use of artificial intelligence in carrying out its mission to secure the border. The new policies were developed by DHS Artificial Intelligence Task Force (AITF), which DHS Secretary Alejandro Mayorkas created in April. In announcing these new policies, DHS noted that AI has been critical to its missions, including combating fentanyl trafficking, strengthening supply chain security, countering sexual exploitation, and protecting critical infrastructure. The Department of Homeland Security logo is seen during a news conference in Washington. Mayorkas writes in the AI policy memo, expected to be released later Thursday, that the US must ensure AI is "rigorously tested to be effective [and] safeguards privacy, civil rights, and civil liberties while avoiding inappropriate biases."

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The Department of Homeland Security said its Science and Technology Directorate has developed a portable gunshot detection system in collaboration with the Massachusetts-based Shooter Detection Systems company. The department said that the system, known as SDS Outdoor, could provide "critical information about outdoor shooting incidents almost instantaneously to first responders." The new system is reportedly an enhancement to the commercial, off-the-shelf Guardian Indoor Active Shooter Detection System.

The U.S. Department of Homeland Security opened industry applications for its 2022 Biometric Technology Rally. The department's Science and Technology directorate is emphasizing discerning people in groups and their level of consent to face biometric scanning. Competitors are to address the challenge of reliably screening small groups of people opting in to facial recognition from among bystanders who have not consented. The competition will be an unattended "high throughput" scenario where group-processing systems must rapidly capture biometrics from multiple subjects. Companies will have to match photographs and identify faces, acquire only needed biometric images and meet performance benchmarks for demographic groups.

Paul Rosenzweig is the founder of Red Branch Consulting PLLC, a homeland security consulting company and a Senior Advisor to The Chertoff Group. Mr. Rosenzweig formerly served as Deputy Assistant Secretary for Policy in the Department of Homeland Security. He is a Professorial Lecturer in Law at George Washington University, a Senior Fellow in the Tech, Law & Security program at American University, and a Board Member of the Journal of National Security Law and Policy.

The Department of Homeland Security issued a request for comment for 11 proposed research topics the agency intends to pursue, with hopes that eligible small business partners will become more aware and attuned to those areas of study. The research areas were announced in a Nov. 16 pre-solicitation through Homeland's Science and Technology Directorate Small Business Innovation Research (SBIR) Program. These proposed areas include automated artificial intelligence sensing technology, counterfeit microelectronic detection, a broadband interoperability platform, biological hazard detection, a mass fatality tracking system, a wearable detector for chemical threats, low cost diagnostic devices, and streamlined airport checkpoint technology for passengers with limited mobility. "The topics span a broad range of homeland security needs that give small businesses the opportunity to partner with DHS and turn their ideas into effective solutions," Dusty Lang, the DHS SBIR director, said in a press release. "I encourage all innovative small businesses to review the topics in the Pre-Solicitation to better understand our research and development needs."

The terms "artificial intelligence," "machine learning" and "robotic process automation" (RPA) get thrown around synonymously, but differentiating between them is important to understanding how best to use them. Brian Campo, deputy chief technology officer at the Department of Homeland Security, clarified that RPA is essentially "automation" -- the act of putting manual tasks into a context or system where the same action can be done automatically and intrinsically. As for AI and machine learning, the difference comes down to how the data is used. "So machine learning is trying to take data and make it intrinsically more informative, trying to take those automated insights and figure them out and find them in new and interesting ways, uncovering things that we wouldn't necessarily be thinking about or something that wouldn't occur to the operator," he said on Federal Monthly Insights -- Cloud and Artificial Intelligence. "Now, artificial intelligence is sort of different than that, in that it's not about driving insights -- it's about actually making impacts to some operational activity."

Federal agencies are getting better at buying advanced technologies like artificial intelligence but still lag in deploying those tools due to security concerns, according to a Homeland Security Department procurement official. "We're doing a really good job at procuring things," Jessica Clark, an official on the Acquisition Systems Team in DHS's Office of the Chief Procurement Officer, said Tuesday during the Professional Services Council's annual Tech Trends conference. "But getting it up and running safely is always going to be an issue for our program managers." Clark said DHS takes a different procurement strategy when looking at new and innovative technologies, preferring a phased approach where a relatively large pool of vendors is whittled down over the course of multiple prototypes and demonstrations, with each subsequent phase using larger datasets that are more and more relevant to the program. She cited the department's work integrating AI into the Contractor Performance Assessment Reporting System, or CPARS, which contracting officers use to gauge a vendor's past performance on government contracts. For the CPARS AI effort, DHS started with nine vendors, which was then down-selected to six and then four.

By now, most people who run small and midsize businesses know that they ought to take advantage of artificial intelligence to make their companies competitive in the digital age. But many don't know how to go about it. To meet this demand, Northeastern, which invested $50 million in a new artificial intelligence research institute last year, will lead a new Massachusetts program, AI Jump Start, to connect small business owners in the state with academic faculty experts to learn how machine learning can grow their companies. The initiative is aimed at a broad range of small and midsize enterprises in defense, manufacturing, health, and other industries whose leaders would like to incorporate artificial intelligence but aren't quite sure where to turn. It's open also to companies that want to upgrade data-driven computing to glean new insights into customers, suppliers, and competitors.