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Research for the Public Utility Law Project (PULP) has been released which details 'how Verizon deliberately moves back and forth between regulatory regimes, classifying its infrastructure either like a heavily regulated telephone network or a deregulated information service depending on its needs. The chicanery has allowed Verizon to raise telephone rates, all the while missing commitments for high-speed internet deployment' (PDF). In short, Verizon pushed for the government to give it common carrier privileges under Title II in order to build out its fiber network with tax-payer money. Result: increased service rates on telephone users to subsidize Verizon's 'infrastructure investment.' When it comes to regulations on Verizon's fiber network, however, Verizon has been pushing the government to classify its services as that of information only — i.e., beyond Title II. Verizon has made about $4.4 billion in additional revenue in New York City alone, 'money that's funneled directly from a Title II service to an array of services that currently lie beyond Title II's reach.' And it's all legal. An attorney at advocacy group Public Knowledge said it best: 'To expect that you can come in and use public infrastructure and funds to build a network and then be free of any regulation is absurd....When Verizon itself is describing these activities as a Title II common carrier, how can the FCC look at broadband internet and continue acting as though it's not a telecommunication network?'"

While there is considerable telecom hubris regarding the 5G rollout and increasing speculation that the next generation of wireless is not yet ready for Prime Time, the industry continues to make promises to Rural America that it has no intention of fulfilling. Decades-long promises to deliver digital Utopia to rural America by T-Mobile, Verizon and AT&T have never materialized.  

In 2017, the USDA reported that 29% of American farms had no internet access. The FCC says that 14 million rural Americans and 1.2 million Americans living on tribal lands do not have 4G LTE on their phones, and that 30 million rural residents do not have broadband service compared to 2% of urban residents.  It’s beginning to sound like a Third World country. Despite an FCC $4.5 billion annual subsidy to carriers to provide broadband service in rural areas, the FCC reports that ‘over 24 million Americans do not have access to high-speed internet service, the bulk of them in rural area”while a  Microsoft Study found that  “162 million people across the US do not have internet service at broadband speeds.” At the same time, only three cable companies have access to 70% of the market in a sweetheart deal to hike rates as they avoid competition and the FCC looks the other way.  The FCC believes that it would cost $40 billion to bring broadband access to 98% of the country with expansion in rural America even more expensive.  While the FCC has pledged a $2 billion, ten year plan to identify rural wireless locations, only 4 million rural American businesses and homes will be targeted, a mere drop in the bucket. Which brings us to rural mapping: Since the advent of the digital age, there have been no accurate maps identifying where broadband service is available in rural America and where it is not available.  The FCC has a long history of promulgating unreliable and unverified carrier-provided numbers as the Commission has repeatedly ‘bungled efforts to produce accurate broadband maps” that would have facilitated rural coverage. During the Senate Commerce Committee hearing on April 10th regarding broadband mapping, critical testimony questioned whether the FCC and/or the telecom industry have either the commitment or the proficiency to provide 5G to rural America.  Members of the Committee shared concerns that 5G might put rural America further behind the curve so as to never catch up with the rest of the country

On the 21st floor of a high-rise hotel in Cleveland, in a room full of political operatives, Microsoft’s Research Division was advertising a technology that could read each facial expression in a massive crowd, analyze the emotions, and report back in real time. “You could use this at a Trump rally,” a sales representative told me. At both the Republican and Democratic conventions, Microsoft sponsored event spaces for the news outlet Politico. Politico, in turn, hosted a series of Microsoft-sponsored discussions about the use of data technology in political campaigns. And throughout Politico’s spaces in both Philadelphia and Cleveland, Microsoft advertised an array of products from “Microsoft Cognitive Services,” its artificial intelligence and cloud computing division. At one exhibit, titled “Realtime Crowd Insights,” a small camera scanned the room, while a monitor displayed the captured image. Every five seconds, a new image would appear with data annotated for each face — an assigned serial number, gender, estimated age, and any emotions detected in the facial expression. When I approached, the machine labeled me “b2ff” and correctly identified me as a 23-year-old male.

“Realtime Crowd Insights” is an Application Programming Interface (API), or a software tool that connects web applications to Microsoft’s cloud computing services. Through Microsoft’s emotional analysis API — a component of Realtime Crowd Insights — applications send an image to Microsoft’s servers. Microsoft’s servers then analyze the faces and return emotional profiles for each one. In a November blog post, Microsoft said that the emotional analysis could detect “anger, contempt, fear, disgust, happiness, neutral, sadness or surprise.” Microsoft’s sales representatives told me that political campaigns could use the technology to measure the emotional impact of different talking points — and political scientists could use it to study crowd response at rallies.

Facial recognition technology — the identification of faces by name — is already widely used in secret by law enforcement, sports stadiums, retail stores, and even churches, despite being of questionable legality. As early as 2002, facial recognition technology was used at the Super Bowl to cross-reference the 100,000 attendees to a database of the faces of known criminals. The technology is controversial enough that in 2013, Google tried to ban the use of facial recognition apps in its Google glass system. But “Realtime Crowd Insights” is not true facial recognition — it could not identify me by name, only as “b2ff.” It did, however, store enough data on each face that it could continuously identify it with the same serial number, even hours later. The display demonstrated that capability by distinguishing between the number of total faces it had seen, and the number of unique serial numbers. Photo: Alex Emmons