The COVID-19 pandemic has created both speed bumps and accelerants for connected and automated vehicle (“CAV”) developments in the United States. In our Quarterly Update earlier this month, we covered recent legislative and regulatory activity around CAVs, both specifically targeted efforts and those impacting AI and IoT technologies generally. Although some CAV legislative efforts have been sidelined due to the government’s focus on COVID-19, the pandemic is incentivizing policymakers at the federal and state levels to support CAV-related initiatives.
On May 19, 2020, Representative Morgan Griffith (R-VA-9) introduced the Advancing Quantum Computing Act (AQCA), which would require the Secretary of Commerce to conduct a study on quantum computing. “We can’t depend on other countries . . . to guarantee American economic leadership, shield our stockpile of critical supplies, or secure the benefits of technological progress to our people,” Representative Griffith explained. “It is up to us to do that.”
Quantum computers use the science underlying quantum mechanics to store data and perform computations. The properties of quantum mechanics are expected to enable such computers to outperform traditional computers on a multitude of metrics. As such, there are many promising applications, from simulating the behavior of matter to accelerating the development of artificial intelligence. Several companies have started exploring the use of quantum computing to develop new drugs, improve the performance of batteries, and optimize transit routing to minimize congestion.
In addition to the National Quantum Initiative Act passed in 2018, the introduction of AQCA represents another important—albeit preliminary—step for Congress in helping to shape the growth and development of quantum computing in the United States. It signals Congress’s continuing interest in developing a national strategy for the technology.
Overall, the AQCA would require the Secretary of Commerce to conduct the following four categories of studies related to the impact of quantum computing:
- First, the Secretary would be required to analyze industry sectors that develop and use quantum computing, including public-private partnerships that support its adoption. This analysis would specify the advantages and disadvantages of quantum computing for U.S. businesses.
- Second, the Secretary would be required to address federal activity related to quantum computing, such as identifying “all interagency activities related to quantum computing” and establishing a list of agencies asserting jurisdiction over quantum-focused entities and sectors.
- Third, the Secretary would be required to examine “at least ten and not more than 15 countries” and their national strategies on quantum computing, with the overall goal of ranking U.S. efforts.
- Finally, the Secretary would be required to focus on “marketplace and supply chain of quantum computing,” such as assessing the risks posed by the technology and how foreign governments may exploit those risks.
Artificial Intelligence (AI) has played an important role in battling COVID-19 since the initial outbreak: HealthMap – an AI tool from Boston Children’s Hospital that scans news reports, social media, and other data for signs of disease outbreaks – first sounded the international alarm after picking up reports of an emerging virus in Wuhan, China. As the virus evolved into a global pandemic, scientists, researchers, and medical professionals have increasingly integrated AI into their efforts to combat the disease.
The following are just a few examples of recent AI developments and AI’s role in the fight against COVID-19.
AI as a Partner in COVID-19 Testing Efforts
AI might help leverage population data to help assess patients’ symptoms: A group of researchers from King’s College London, Massachusetts General Hospital, and health science company ZOE developed an AI tool that compares a patient’s symptoms against crowd-sourced symptom data from the COVID Symptom Study app to predict whether that patient is likely to have COVID-19. This tool is set to enter clinical trials in the U.S. and U.K., and the researchers believe that this AI tool may be particularly useful for populations with limited access to testing.
AI also is being used to analyze medical imaging and differentiate between diagnoses with symptoms similar to those of COVID-19. Researchers from the University of Chicago and Argonne National Laboratory, relying on a grant from the new c3.ai Digital Transformation Institute, are developing an AI tool to analyze chest X-rays and thoracic CT scans in order to spot the disease and differentiate between its various stages. UCSD Professor Albert Hsiao has applied his own AI approach to chest X-rays from patients in a research study enabled by a cloud services provider. In China, radiologists are working on a learning model that can distinguish between COVID-19 and community-acquired pneumonia based on chest CT scans.
AI as a Triage Tool
As hospital systems face an influx of COVID-19 patients, major players in the healthcare industry are turning more and more to AI tools to assist with patient management. Of course, providers already use AI to offer clinical decision support: for example, in 2015, Stanford University Professor Ron Li worked with electronic health record vendor Epic to develop a “Deterioration Index” to identify patients whose condition is likely to deteriorate. With the onset of COVID-19, Professor Li and his team have begun to test the Deterioration Index for triage of COVID-19 patients.
On the payer side, Israel’s Maccabi Healthcare Services partnered with AI company Medial EarlySign to identify which of its 2.4 million members were high risk for severe COVID-19 complications so those patients could be fast-tracked for testing. The organization says it is currently talking to U.S. entities about using the system to fast-track their own patients.
AI as a Research Assistant
AI also can serve as a critical tool in the search for reliable treatments for COVID-19. A research team at Northwestern University developed a machine model that allows researchers to bypass conventional prediction markets and more quickly identify and dedicate resources to the most promising research studies for treatments and vaccines for COVID-19.
Researchers also are using AI to scour molecular modelling data and EHR data to evaluate whether existing drugs may be repurposed as treatments for COVID-19. AI already has identified at least one prospect. Specifically, BenevolentAI, a London startup, used AI to identify the rheumatoid arthritis drug baricitinib as a possible treatment for severe symptoms of COVID-19. Based on this research, a major pharmaceutical company announced that it will conduct a large-scale clinical trial of the drug as a treatment for COVID-19, in collaboration with the U.S. National Institute of Allergy and Infectious Diseases.
Creating Trustworthy AI
AI development, which was already a high-activity sector pre-COVID-19, has ramped up further in the effort to battle the virus. At the same time, stakeholders have continued to focus on AI trustworthiness. Lee Tiedrich and Lala R. Qadir share “10 Steps to Creating Trustworthy AI Applications” in an article for Law360.
For more information about AI, please see our “AI Toolkit.”
This post was originally published on the Covington Digital Health blog.
Yesterday, with vocal support from fellow Commissioner Brendan Carr, FCC Chairman Ajit Pai released a draft Declaratory Ruling and Notice of Proposed Rulemaking (“DR” and “NPRM”) to promote the use of broadcast spectrum for internet services (referred to by the FCC as “Broadcast Internet”). The full, five-member Commission will vote on adoption of the DR and NPRM at the agency’s next monthly public meeting on Tuesday, June 9.
Policymakers and other stakeholders continue to promote the development and adoption of artificial intelligence (“AI”) worldwide. For example, the European Commission recently released a white paper describing a proposed framework for regulating AI. In the United States, lawmakers have considered AI legislation and President Trump signed an Executive Order on AI that, among other things, promotes investment in AI and directed the National Institute of Standards and Technology to establish AI standards, including for AI trustworthiness. Over the past year, consistent with the Executive Order, the federal government has invested significantly in AI, as detailed in an annual report recently released by the Trump Administration.
NHSX recently published “A Buyer’s Checklist for AI in Health and Care” (Guidance) that sets out 10 key questions which will be of use to parties deploying AI solutions or conducting data driven projects (in a health and care setting or otherwise). For example, the Guidance highlights:
- key data-related considerations, such as can the outcome of AI solutions trained on a given dataset be validated against other data, accounting for bias in training data, and reflecting the value of data as an input to an AI product in commercial terms; and
- the importance of assessing regulatory considerations at the outset of a digital health project, such as the potential need for a research ethics committee approval, a CE mark (if a medical device is to be used in the project), and a data protection impact assessment.
The Guidance’s 10 questions are:
- Is AI the right solution for the type of problem you need to solve?
- Can this technology be procured through a transparent, fair, competitive process?
- Can this product do what it claims it can?
- Are the users of this product primed to use it?
- Does this product meet regulatory standards?
- What information sharing and data protection protocols would need to be in place to comply with your information governance policy?
- What agreements should you put in place to protect any intellectual property generated by your organisation through its use of this AI product?
- Do you have the necessary storage and computing requirements?
- Will your existing systems work effectively alongside the new technology to ensure a clear and reliable workflow?
- Can you manage the maintenance burden of this new technology?
Though it seems like the distant past now, in this update we detail the notable legislative events from the first quarter of 2020 on artificial intelligence (“AI”), the Internet of Things (“IoT”), cybersecurity as it relates to AI and IoT, and connected and autonomous vehicles (“CAVs”). Prior to the slowdown in non-COVID related legislation that accompanied the pandemic during the first quarter, federal and state policymakers continued their focus on AI and IoT, including by introducing substantive bills that would regulate the use of such technology and by supporting bills aimed at further study of how such technology may impact different sectors. And it is important to note that this activity has slowed, not ceased—we will continue to update you on meaningful developments between these quarterly updates across our blogs. Continue Reading
Yesterday, the Federal Communications Commission (“FCC”) granted GE Healthcare (“GEHC”) a waiver of its equipment authorization rules to allow for the importation, marketing, and operation of certain medical devices that have yet to receive authorization under applicable FCC requirements. The GEHC devices at issue include bedside and wearable patient monitors; telemetry transmitters; antenna infrastructure; wireless sensors; diagnostic testing ECG analysis systems; mobile radiology equipment; and portable X-rays.
The FCC granted the waiver due to the “unprecedented strain” that the COVID-19 pandemic has placed on the U.S. healthcare system. In doing so, the FCC recognized that GEHC now has to rely on alternative component suppliers to maintain a robust supply chain of devices, and that doing so has and will continue to require GEHC to pursue and secure new or modified equipment authorizations under the FCC’s rules. By waiving these rules for a temporary period, subject to certain conditions, the FCC enabled GEHC to import, market, and operate these devices before they are fully authorized, thereby improving the speed at which GEHC can bring them to market. Continue Reading
Poison prevention has been one of several top priorities of the U.S. Consumer Product Safety Commission (“CPSC”) during the COVID-19 pandemic. President Trump’s recent speculation about the ingestion of disinfectants as a potential COVID-19 treatment prompted the agency to tweet an urgent safety warning the following day, and product manufacturers have issued similar warning statements about proper use of household cleaning products.
Even before this “ingestion incident,” the CPSC had focused on poison prevention as a top COVID-19 product safety priority. Under the Poison Prevention Packaging Act, originally passed by Congress in 1952 (then the “Poisons Act”) and exclusively enforced by the CPSC, manufacturers are required to test, certify conformance with, and market household cleaning products containing toxic chemicals, as well as prescription drugs and certain over-the-counter drugs (such as aspirin), in special child-resistant packaging.
The U.S. Environmental Protection Agency enforces similar packaging requirements for certain EPA-registered disinfectant products, such as products that exceed specified toxicity levels, under the Federal Insecticide, Fungicide, and Rodenticide Act. Under the Federal Hazardous Substances Act (“FHSA”), enforced by the CPSC, products containing toxic substances must contain precautionary warning statements, such as “Danger” and “Harmful if Swallowed.”
Products that are not compliant with special packaging and labeling requirements are considered misbranded under the Food, Drug, and Cosmetic Act or the FHSA and can trigger mandatory hazard reporting to the CPSC, as well as corrective action such as recalls. Failure to report or late reporting of hazardous or noncompliant products also can trigger government investigations, enforcement actions, and civil or criminal penalties under the Consumer Product Safety Act.
COVID-19 has required the consumer product industry to confront an array of challenges, as businesses seek to protect the health of their employees and consumers, while navigating major supply-chain disruptions, testing lab closures, and unanticipated changes in production and consumer demand for products. Consumer product manufacturers, importers, and retailers should remain vigilant about product safety compliance during this extraordinary time.
Summarized below are the top five points for consumer product companies to keep in mind during the COVID-19 pandemic:
Trustworthy AI has garnered attention from policymakers and other stakeholders around the globe. How can organizations operationalize trustworthy #AI for Covid-19 and other AI applications, as the legal landscape continues to evolve? Lee Tiedrich and Lala R. Qadir share ten steps in this article with Law360. For more information about AI, please see our “AI Toolkit.”