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Artificial Intelligence for Spectrum Sharing ‘Not Far Off,’ Says FCC Chair Rosenworcel

AI can be used to make congestion control decisions, a major opportunity for dynamic spectrum sharing.



Photo of Martin Doczkat of the FCC, Randall Berry of Northwestern University, Harold Feld of Public Knowledge, Lisa Guess of Ericsson, and Ness Schroff of NSF (left to right)

WASHINGTON, July 13, 2023 – The Federal Communications Commission is evaluating how artificial intelligence can be used in dynamic spectrum sharing, protect against harmful robocalls and improve the national broadband map.  

The FCC joined with the National Science Foundation in a forum Thursday to discuss how AI can be used to improve agency operations. Chairwoman Jessica Rosenworcel said that the points and solutions discussed during the event will spearhead the FCC’s August open meeting. 

She pointed to spectrum sharing optimization as a major improvement possible through AI optimization. “Smarter radios using AI can work with each other without a central authority dictating the best use of spectrum in every environment,” she said, claiming that the technology is “not far off.”  

AI can be used to make congestion control decisions, which is a major opportunity for dynamic spectrum sharing, said Ness Shroff, director of NSF AI institute, in a panel discussion. It can also be used to sense when federal agencies are using spectrum bands to allow commercial use on federally owned spectrum without disrupting high-priority use.  

This comes as the FCC is facing spectrum availability concerns. In its June open meeting, the FCC issued proposed rulemaking that explores how the 42 – 42.5 GHz spectrum band might be made available on a shared basis. 

As research progresses, we will see more uses of AI for the FCC and in the telecom field in general, Shroff concluded. 

Lisa Guess, senior vice president of solutions engineering at telecom Ericsson, said that AI can be an important tool for getting a more granular national broadband map by analyzing areas that are likely to be overreported and analyzing the data submitted for accuracy and consistency.  

Shroff added that AI could analyze federal grant programs to determine how successful they are and find solutions for problem areas. 

Illegal robocalls can also be addressed through AI which can flag certain patterns that are deemed suspicious and analyze voice biometrics for synthesized voices, said Alisa Valentin, senior director of technology and telecommunications policy at the National Urban League. Unfortunately, AI also makes it easier for bad actors to appear legitimate, she said, which is why the FCC needs to address new concerns as they appear.  

Harold Feld, senior vice president for consumer advocacy group Public Knowledge, added that the FCC needs to recognize that AI is a tool to be utilized but also a cause of potential concern that the agency needs to anticipate. He urged the FCC to develop regulations now that will prohibit its misuse in the future. 

Rosenworcel expressed her optimism about the future of AI in opening remarks. “Every day I see how communications networks power our world. I know how their expansion and evolution can change commercial and civic life. I also know the power of those communications networks can grow exponentially when we can use AI to understand how to increase the efficiency and effectiveness of our networks,” she said. 

Commissioner Nathan Simington added his support, emphasizing the need to maintain American headway as the technology leader of the world. “Most visions for a shared spectral future depend on one or another implementation of machine learning in automated frequency coordination,” he said. 

Simington added caution against casting regulatory solutions to problems that do not exist yet that may “be worse than the disease.” 

AI in telecommunications 

Not only is AI a game changer for the FCC, but it can also transform the way that telecommunications companies run their businesses, said Jorge Amar, senior partner at global management consulting firm, McKinsey and Company. AI can provide companies hyper personalization for consumer experience, improve labor productivity, and improve internal network operation. 

Generative AI “has potential to continue to disrupt how AI transforms telecom companies,” added Amar. Almost every telecom company is starting to work with AI, which is increasing the value of the industry, he said — “it is here to stay.” 

In fact, AI has a unique customer experience application for people with disabilities by predicting the likelihood that a particular customer will call customer service and preempt them by calling the consumer themselves and help address their pain points, said Amar.  

An easy application of AI that is already being deployed is chat bots that are able to respond to consumer’s concerns in real time and limit the amount of time waiting on hold or conversing with an employee, he added.  

Rosenworcel highlighted network resiliency in her remarks, saying that AI “can help proactively diagnose difficulties, orchestrate solutions, and heal networks on its own,” especially in response to weather events that create unforeseen technical problems. “That means operators can fix problems before they reach customers, and design them with radically improved intelligence and efficiency.” 

The House Subcommittee on Communications and Technology passed a bill Wednesday that would require the NTIA to examine accountability standards for AI systems used in communications networks as a greater push to enhance transparency of government’s use of AI to communicate with the public. 

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Artificial Intelligence

Companies Must Be Transparent About Their Use of Artificial Intelligence

Making the use of AI known is key to addressing any pitfalls, researchers said.



WASHINGTON, September 20, 2023 – Researchers at an artificial intelligence workshop Tuesday said companies should be transparent about their use of algorithmic AI in things like hiring processes and content writing. 

Andrew Bell, a fellow at the New York University Center for Responsible AI, said that making the use of AI known is key to addressing any pitfalls AI might have. 

Algorithmic AI is behind systems like chatbots which can generate texts and answers to questions. It is used in hiring processes to quickly screen resumes or in journalism to write articles. 

According to Bell, ‘algorithmic transparency’ is the idea that “information about decisions made by algorithms should be visible to those who use, regulate, and are affected by the systems that employ those algorithms.”

The need for this kind of transparency comes after events like Amazons’ old AI recruiting tool showed bias toward women in the hiring process, or when OpenAI, the company that created ChatGPT, was probed by the FTC for generating misinformation. 

Incidents like these have brought the topic of regulating AI and making sure it is transparent to the forefront of Senate conversations.

Senate committee hears need for AI regulation

The Senate’s subcommittee on consumer protection on September 12 heard about proposals to make AI use more transparent, including disclaiming when AI is being used and developing tools to predict and understand risk associated with different AI models.

Similar transparency methods were mentioned by Bell and his supervisor Julia Stoyanovich, the Director of the Center for Responsible AI at New York University, a research center that explores how AI can be made safe and accessible as the technology evolves. 

According to Bell, a transparency label on algorithmic AI would “[provide] insight into ingredients of an algorithm.” Similar to a nutrition label, a transparency label would identify all the factors that go into algorithmic decision making.  

Data visualization was another option suggested by Bell, which would require a company to put up a public-facing document that explains the way their AI works, and how it generates the decisions it spits out. 

Adding in those disclaimers creates a better ecosystem between AI and AI users, increasing levels of trust between all stakeholders involved, explained Bell.

Bell and his supervisor built their workshop around an Algorithm Transparency Playbook, a document they published that has straightforward guidelines on why transparency is important and ways companies can go about it. 

Tech lobbying groups like the Computer and Communications Industry Association, which represent Big Tech companies, however, have spoken out in the past against the Senate regulating AI, claiming that it could stifle innovation. 

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Artificial Intelligence

Congress Should Mandate AI Guidelines for Transparency and Labeling, Say Witnesses

Transparency around data collection and risk assessments should be mandated by law, especially in high-risk applications of AI.



Screenshot of the Business Software Alliance's Victoria Espinel at the Commerce subcommittee hearing

WASHINGTON, September 12, 2023 – The United States should enact legislation mandating transparency from companies making and using artificial intelligence models, experts told the Senate Commerce Subcommittee on Consumer Protection, Product Safety, and Data Security on Tuesday.

It was one of two AI policy hearings on the hill Tuesday, with a Senate Judiciary Committee hearing, as well as an executive branch meeting created under the National AI Advisory Committee.

The Senate Commerce subcommittee asked witnesses how AI-specific regulations should be implemented and what lawmakers should keep in mind when drafting potential legislation. 

“The unwillingness of leading vendors to disclose the attributes and provenance of the data they’ve used to train models needs to be urgently addressed,” said Ramayya Krishnan, dean of Carnegie Mellon University’s college of information systems and public policy.

Addressing problems with transparency of AI systems

Addressing the lack of transparency might look like standardized documentation outlining data sources and bias assessments, Krishnan said. That documentation could be verified by auditors and function “like a nutrition label” for users.

Witnesses from both private industry and human rights advocacy agreed legally binding guidelines – both for transparency and risk management – will be necessary. 

Victoria Espinel, CEO of the Business Software Alliance, a trade group representing software companies, said the AI risk management framework developed in March by the National Institute of Standards and Technology was important, “but we do not think it is sufficient.”

“We think it would be best if legislation required companies in high-risk situations to be doing impact assessments and have internal risk management programs,” she said.

Those mandates – along with other transparency requirements discussed by the panel – should look different for companies that develop AI models and those that use them, and should only apply in the most high-risk applications, panelists said.

That last suggestion is in line with legislation being discussed in the European Union, which would apply differently depending on the assessed risk of a model’s use.

“High-risk” uses of AI, according to the witnesses, are situations in which an AI model is making consequential decisions, like in healthcare, hiring processes, and driving. Less consequential machine-learning models like those powering voice assistants and autocorrect would be subject to less government scrutiny under this framework.

Labeling AI-generated content

The panel also discussed the need to label AI-generated content.

“It is unreasonable to expect consumers to spot deceptive yet realistic imagery and voices,” said Sam Gregory, director of human right advocacy group WITNESS. “Guidance to look for a six fingered hand or spot virtual errors in a puffer jacket do not help in the long run.”

With elections in the U.S. approaching, panelists agreed mandating labels on AI-generated images and videos will be essential. They said those labels will have to be more comprehensive than visual watermarks, which can be easily removed, and might take the form of cryptographically bound metadata.

Labeling content as being AI-generated will also be important for developers, Krishnan noted, as generative AI models become much less effective when trained on writing or images made by other AIs.

Privacy around these content labels was a concern for panelists. Some protocols for verifying the origins of a piece of content with metadata require the personal information of human creators.

“This is absolutely critical,” said Gregory. “We have to start from the principle that these approaches do not oblige personal information or identity to be a part of them.”

Separately, the executive branch committee that met Tuesday was established under the National AI Initiative Act of 2020, is tasked with advising the president on AI-related matters. The NAIAC gathers representatives from the Departments of State, Defense, Energy and Commerce, together with the Attorney General, Director of National Intelligence, and Director of Science and Technology Policy.

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Artificial Intelligence

Tech Policy Group CCIA Speaks Out Against AI Regulation

The trade group represents major tech companies like Amazon and Google.



WASHINGTON, September 12, 2023 – A policy director at the Computer and Communications Industry Association spoke out on Tuesday against impending artificial intelligence regulations in the European Union and United States.

The CCIA represents some of the biggest tech companies in the world, with members including Amazon, Google, Meta, and Apple.

“The E.U. approach will focus very much on the technology itself, rather than the use of it, which is highly problematic,” said Boniface de Champris, CCIA’s Europe policy manager, at a panel hosted by the Cato Institute. “The requirements would basically inhibit the development and use of cutting edge technology in the E.U.”

This echoes de Champris’s American counterparts, who have argued in front of Congress that AI-specific laws would stifle innovation.

The European Parliament is aiming to reach an agreement by the end of the year on the AI Act, which would put regulations on all AI systems based on their assessed risk level. 

The E.U. also adopted in August the Digital Services Act, legislation that tightens privacy rules and expands transparency requirements. Under the law, users can opt to turn off artificial intelligence-enabled content recommendation.

U.S. President Joe Biden announced in July that seven major AI and tech companies – including CCIA members Amazon, Meta, and Google – made voluntary commitments to various AI safeguards, including information sharing and security testing.

Multiple U.S. agencies are exploring more binding AI regulation. Both the Senate Judiciary committee and Senate consumer protection subcommittee held hearings on potential AI policy later on Tuesday. The judiciary hearing will include testimony from Microsoft president Brad Smith and AI and graphics company NVIDIA’s chief scientist William Daly.

The House Energy and Commerce Committee passed in July the Artificial Intelligence Accountability Act, which gives the National Telecommunications and Information Administration a mandate to study accountability measures for artificial intelligence systems used by telecom companies.

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