Tag: Artificial Intelligence

Recent Healthcare-Related Artificial Intelligence Developments

AI is here to stay. The development and use of artificial intelligence (“AI”) is rapidly growing in the healthcare landscape with no signs of slowing down.

From a governmental perspective, many federal agencies are embracing the possibilities of AI. The Centers for Disease Control and Prevention is exploring the ability of AI to estimate sentinel events and combat disease outbreaks and the National Institutes of Health is using AI for priority research areas. The Centers for Medicare and Medicaid Services is also assessing whether algorithms used by plans and providers to identify high risk patients and manage costs can introduce bias and restrictions. Additionally, as of December 2023, the U.S. Food & Drug Administration cleared more than 690 AI-enabled devices for market use.

From a clinical perspective, payers and providers are integrating AI into daily operations and patient care. Hospitals and payers are using AI tools to assist in billing. Physicians are using AI to take notes and a wide range of providers are grappling with which AI tools to use and how to deploy AI in the clinical setting. With the application of AI in clinical settings, the standard of patient care is evolving and no entity wants to be left behind.

From an industry perspective, the legal and business spheres are transforming as a result of new national and international regulations focused on establishing the safe and effective use of AI, as well as commercial responses to those regulations. Three such regulations are top of mind, including (i) President Biden’s Executive Order on the Safe, Secure, and Trustworthy Development and Use of AI; (ii) the U.S. Department of Health and Human Services’ (“HHS”) Final Rule on Health Data, Technology, and Interoperability; and (iii) the World Health Organization’s (“WHO”) Guidance for Large Multi-Modal Models of Generative AI. In response to the introduction of regulations and the general advancement of AI, interested healthcare stakeholders, including many leading healthcare companies, have voluntarily committed to a shared goal of responsible AI use.

U.S. Executive Order on the Safe, Secure, and Trustworthy Development and Use of AI

On October 30, 2023, President Biden issued an Executive Order on the Safe, Secure, and Trustworthy Development and Use of AI (“Executive Order”). Though long-awaited, the Executive Order was a major development and is one of the most ambitious attempts to regulate this burgeoning technology. The Executive Order has eight guiding principles and priorities, which include (i) Safety and Security; (ii) Innovation and Competition; (iii) Commitment to U.S. Workforce; (iv) Equity and Civil Rights; (v) Consumer Protection; (vi) Privacy; (vii) Government Use of AI; and (viii) Global Leadership.

Notably for healthcare stakeholders, the Executive Order directs the National Institute of Standards and Technology to establish guidelines and best practices for the development and use of AI and directs HHS to develop an AI Task force that will engineer policies and frameworks for the responsible deployment of AI and AI-enabled tech in healthcare. In addition to those directives, the Executive Order highlights the duality of AI with the “promise” that it brings and the “peril” that it has the potential to cause. This duality is reflected in HHS directives to establish an AI safety program to prioritize the award of grants in support of AI development while ensuring standards of nondiscrimination are upheld.

U.S. Department of Health and Human Services Health Data, Technology, and Interoperability Rule

In the wake of the Executive Order, the HHS Office of the National Coordinator finalized its rule to increase algorithm transparency, widely known as HT-1, on December 13, 2023. With respect to AI, the rule promotes transparency by establishing transparency requirements for AI and other predictive algorithms that are part of certified health information technology. The rule also:

  • implements requirements to improve equity, innovation, and interoperability;
  • supports the access, exchange, and use of electronic health information;
  • addresses concerns around bias, data collection, and safety;
  • modifies the existing clinical decision support certification criteria and narrows the scope of impacted predictive decision support intervention; and
  • adopts requirements for certification of health IT through new Conditions and Maintenance of Certification requirements for developers.

Voluntary Commitments from Leading Healthcare Companies for Responsible AI Use

Immediately on the heels of the release of HT-1 came voluntary commitments from leading healthcare companies on responsible AI development and deployment. On December 14, 2023, the Biden Administration announced that 28 healthcare provider and payer organizations signed up to move toward the safe, secure, and trustworthy purchasing and use of AI technology. Specifically, the provider and payer organizations agreed to:

  • develop AI solutions to optimize healthcare delivery and payment;
  • work to ensure that the solutions are fair, appropriate, valid, effective, and safe (“F.A.V.E.S.”);
  • deploy trust mechanisms to inform users if content is largely AI-generated and not reviewed or edited by a human;
  • adhere to a risk management framework when utilizing AI; and use of AI technology. Specifically, the provider and payer organizations agreed to:
  • develop AI solutions to optimize healthcare delivery and payment;
  • work to ensure that the solutions are fair, appropriate, valid, effective, and safe (“F.A.V.E.S.”);
  • deploy trust mechanisms to inform users if content is largely AI-generated and not reviewed or edited by a human;
  • adhere to a risk management framework when utilizing AI; and
  • research, investigate, and develop AI swiftly but responsibly.

WHO Guidance for Large Multi-Modal Models of Generative AI

On January 18, 2024, the WHO released guidance for large multi-modal models (“LMM”) of generative AI, which can simultaneously process and understand multiple types of data modalities such as text, images, audio, and video. The WHO guidance contains 98 pages with over 40 recommendations for tech developers, providers and governments on LMMs, and names five potential applications of LMMs, such as (i) diagnosis and clinical care; (ii) patient-guided use; (iii) administrative tasks; (iv) medical education; and (v) scientific research. It also addresses the liability issues that may arise out of the use of LMMs.

Closely related to the WHO guidance, the European Council’s agreement to move forward with a European Union AI Act (“Act”), was a significant milestone in AI regulation in the European Union. As previewed in December 2023, the Act will inform how AI is regulated across the European Union, and other nations will likely take note of and follow suit.

Conclusion

There is no question that AI is here to stay. But how the healthcare industry will look when AI is more fully integrated still remains to be seen. The framework for regulating AI will continue to evolve as AI and the use of AI in healthcare settings changes. In the meantime, healthcare stakeholders considering or adopting AI solutions should stay abreast of developments in AI to ensure compliance with applicable laws and regulations.

Copyright © 2024, Sheppard Mullin Richter & Hampton LLP.
For more on Healthcare, visit the NLR Health Law & Managed Care section.

Commerce Department Launches Cross-Sector Consortium on AI Safety — AI: The Washington Report

  1. The Department of Commerce has launched the US AI Safety Institute Consortium (AISIC), a multistakeholder body tasked with developing AI safety standards and practices.
  2. The AISIC is currently composed of over 200 members representing industry, academia, labor, and civil society.
  3. The consortium may play an important role in implementing key provisions of President Joe Biden’s executive order on AI, including the development of guidelines on red-team testing[1] for AI and the creation of a companion resource to the AI Risk Management Framework.

Introduction: “First-Ever Consortium Dedicated to AI Safety” Launches

On February 8, 2024, the Department of Commerce announced the creation of the US AI Safety Institute Consortium (AISIC), a multistakeholder body housed within the National Institute of Standards and Technology (NIST). The purpose of the AISIC is to facilitate the development and adoption of AI safety standards and practices.

The AISIC has brought together over 200 organizations from industry, labor, academia, and civil society, with more members likely to join in the coming months.

Biden AI Executive Order Tasks Commerce Department with AI Safety Efforts

On October 30, 2023, President Joe Biden signed a wide-ranging executive order on AI (“AI EO”). This executive order has mobilized agencies across the federal bureaucracy to implement policies, convene consortiums, and issue reports on AI. Among other provisions, the AI EO directs the Department of Commerce (DOC) to establish “guidelines and best practices, with the aim of promoting consensus…[and] for developing and deploying safe, secure, and trustworthy AI systems.”

Responding to this mandate, the DOC established the US Artificial Intelligence Safety Institute (AISI) in November 2023. The role of the AISI is to “lead the U.S. government’s efforts on AI safety and trust, particularly for evaluating the most advanced AI models.” Concretely, the AISI is tasked with developing AI safety guidelines and standards and liaising with the AI safety bodies of partner nations.

The AISI is also responsible for convening multistakeholder fora on AI safety. It is in pursuance of this responsibility that the DOC has convened the AISIC.

The Responsibilities of the AISIC

“The U.S. government has a significant role to play in setting the standards and developing the tools we need to mitigate the risks and harness the immense potential of artificial intelligence,” said DOC Secretary Gina Raimondo in a statement announcing the launch of the AISIC. “President Biden directed us to pull every lever to accomplish two key goals: set safety standards and protect our innovation ecosystem. That’s precisely what the U.S. AI Safety Institute Consortium is set up to help us do.”

To achieve the objectives set out by the AI EO, the AISIC has convened leading AI developers, research institutions, and civil society groups. At launch, the AISIC has over 200 members, and that number will likely grow in the coming months.

According to NIST, members of the AISIC will engage in the following objectives:

  1. Guide the evolution of industry standards on the development and deployment of safe, secure, and trustworthy AI.
  2. Develop methods for evaluating AI capabilities, especially those that are potentially harmful.
  3. Encourage secure development practices for generative AI.
  4. Ensure the availability of testing environments for AI tools.
  5. Develop guidance and practices for red-team testing and privacy-preserving machine learning.
  6. Create guidance and tools for digital content authentication.
  7. Encourage the development of AI-related workforce skills.
  8. Conduct research on human-AI system interactions and other social implications of AI.
  9. Facilitate understanding among actors operating across the AI ecosystem.

To join the AISIC, organizations were instructed to submit a letter of intent via an online webform. If selected for participation, applicants were asked to sign a Cooperative Research and Development Agreement (CRADA)[2] with NIST. Entities that could not participate in a CRADA were, in some cases, given the option to “participate in the Consortium pursuant to separate non-CRADA agreement.”

While the initial deadline to submit a letter of intent has passed, NIST has provided that there “may be continuing opportunity to participate even after initial activity commences for participants who were not selected initially or have submitted the letter of interest after the selection process.” Inquiries regarding AISIC membership may be directed to this email address.

Conclusion: The AISIC as a Key Implementer of the AI EO?

While at the time of writing NIST has not announced concrete initiatives that the AISIC will undertake, it is likely that the body will come to play an important role in implementing key provisions of Biden’s AI EO. As discussed earlier, NIST created the AISI and the AISIC in response to the AI EO’s requirement that DOC establish “guidelines and best practices…for developing and deploying safe, secure, and trustworthy AI systems.” Under this general heading, the AI EO lists specific resources and frameworks that the DOC must establish, including:

It is premature to assert that either the AISI or the AISIC will exclusively carry out these goals, as other bodies within the DOC (such as the National AI Research Resource) may also contribute to the satisfaction of these requirements. That being said, given the correspondence between these mandates and the goals of the AISIC, along with the multistakeholder and multisectoral structure of the consortium, it is likely that the AISIC will play a significant role in carrying out these tasks.

We will continue to provide updates on the AISIC and related DOC AI initiatives. Please feel free to contact us if you have questions as to current practices or how to proceed.

Endnotes

[1] As explained in our July 2023 newsletter on Biden’s voluntary framework on AI, “red-teaming” is “a strategy whereby an entity designates a team to emulate the behavior of an adversary attempting to break or exploit the entity’s technological systems. As the red team discovers vulnerabilities, the entity patches them, making their technological systems resilient to actual adversaries.”

[2] See “CRADAs – Cooperative Research & Development Agreements” for an explanation of CRADAs. https://www.doi.gov/techtransfer/crada.

Raj Gambhir contributed to this article.

©1994-2024 Mintz, Levin, Cohn, Ferris, Glovsky and Popeo, P.C. All Rights Reserved.
For more on AI Safety, visit the NLR Communications, Media & Internet section.

WHO Publishes Guidance for Ethics and Governance of AI for Healthcare Sector

The World Health Organization (WHO) recently published “Ethics and Governance of Artificial Intelligence for Health: Guidance on large multi-modal models” (LMMs), which is designed to provide “guidance to assist Member States in mapping the benefits and challenges associated with the use of for health and in developing policies and practices for appropriate development, provision and use. The guidance includes recommendations for governance within companies, by governments, and through international collaboration, aligned with the guiding principles. The principles and recommendations, which account for the unique ways in which humans can use generative AI for health, are the basis of this guidance.”

The guidance focused on one type of generative AI, large multi-modal models (LMMs), “which can accept one or more type of data input and generate diverse outputs that are not limited to the type of data fed into the algorithm.” According to the report, LMMs have “been adopted faster than any consumer application in history.” The report outlines the benefits and risks of LLMs, particularly the risk of using LLMs in the healthcare sector.

The report proposes solutions to address the risks of using LMMs in health care during development, provision, and deployment of LMMs and ethics and governance of LLMs, “what can be done, and by who.”

In the ever-changing world of AI, this is one report that is timely and provides steps and solutions to follow to tackle the risk of using LMMs.

Copyright © 2024 Robinson & Cole LLP. All rights reserved.
For more news on AI in Healthcare, visit the NLR Health Law & Managed Care section.

Top Risks for Businesses in 2024

Just weeks into 2024, it is already clear that uncertainty will be the watchword. Will the economic soft landing of 2023 persist into 2024? Will labor unrest, strong in 2023, settle down as inflation cools? Will inflation remain tamed? Will the U.S. elections bring continuity or a new administration with very different views on the role of the U.S. in the world and in regulating business?

Uncertainty is also fueling a complex risk environment that will require monitoring global developments more so than in the past. As outlined below, geopolitical risks are present, multiple, interconnected and high impact. International relations have traditionally fallen outside the mandate of most C-Suites, but how the U.S. government responds to geopolitical challenges will impact business operations. Beyond additional disruptions to global trade, businesses in 2024 will face risks associated with expanding protectionist economic policies, climate change impacts, and AI-driven disruptors.

Geopolitical Tensions Disrupting Global Trade

The guardrails are coming off the international system that enshrines the ideals of preserving peace and security through diplomatic engagement, respecting international borders (not changing them through military might) and ensuring the free flow of global trade. In 2022, the world was shocked by Russia’s invasion of Ukraine, but it has taken time for the full impact to reverberate through the international system. While political analysts write on a “spillover of conflict,” the more insidious impact is that more leaders of countries and non-state groups are acting outside the guardrails because they are no longer deterred from using military force to achieve political goals, making 2024 ripe for new military conflicts disrupting global trade beyond the ongoing war in Europe.

In October 2023, Hamas launched a war from Gaza against Israel. Thus far, fighting has spread to the West Bank, between Israel and Lebanese Hezbollah in the north, and to the Red Sea, with Iranian-backed Houthis attacking shipping through the strategic Bab al Mandab strait. Container ships and oil tankers, to avoid the risks, are re-routing to the Cape of Good Hope, adding two weeks of extra sailing time, with the associated costs. Insurance premiums for cargo ships sailing in the eastern Mediterranean have skyrocketed, with some no longer servicing Israeli ports. Companies and retailers with tight delivery schedules are switching to airfreight, which is expected to drive up airfreight rates.

Iran, emboldened by its blossoming relationship with Russia as one of Moscow’s new arms suppliers, is activating its proxy armies in Yemen, Iraq, Syria and Lebanon to attack Western targets. In a two-day period in January 2024, the Iran Revolutionary Guards directly launched strikes in Syria, Iraq and Pakistan. Nuclear-armed Pakistan retaliated with a cross border strike in Iran. While there are many nuances to these incidents, it is evident that deterrence against cross-border military conflict is eroding in a region with deep, festering grievances among neighbors. Iran is in an escalatory mode and could resume harassing shipping in the Persian Gulf and the strategic Strait of Hormuz, where about a fifth of the volume of the world’s total oil consumption passes through on a daily basis.

In East Asia, North Korea is also emboldened by the changing geopolitical environment. Pyongyang, too, has become a major supplier of weaponry to Moscow for use in Ukraine. While Russia (and China) in the past have constructively contained North Korean predilection for aggression against its neighbors, Supreme Leader Kim Jong Un may believe the time is ripe to change the status quo. Ominously, in a Jan. 15 speech before the Supreme People’s Assembly (North Korea’s parliament), Kim rejected the policy of reunification with South Korea and proposed incorporating the country into North Korea “in the event of war.” While North Korean leaders frequently revert to brinksmanship and aggressive language, Kim’s speech reflects confidence of a nuclear power, aligned with Russia against a shared adversary – South Korea, which is firmly aligned with the G7 consensus on Russia. A war in the Korean peninsula would be felt around the world because East Asia is central to global shipping and manufacturing, disrupting supply chains, as well as the regional economy.

China is also waiting for the right moment to “unite” Taiwan with the mainland. Beijing has seen the impact of Western sanctions on Russia over Ukraine and has been deterred from aiding the Russian war effort. In many ways, China has benefited from these sanctions and the reorientation of global trade. Also, Russia, with its far weaker economy, has proven surprisingly resilient to sanctions, another lesson for China. Meanwhile, the Taiwanese people voted in January and returned for a third time the ruling party that strongly rejects Chinese territorial claims. Tensions are high, with the Chinese military once again harassing Taiwanese defenses. For Beijing, the “right moment” could fall this year should conflict break out on the Korean peninsula, which would tie the U.S. down because of the Mutual Defense Treaty.

The uncertainty here is not that there are global tensions, but how the U.S. will respond as they develop and how U.S. businesses can navigate external shocks. Will the U.S. be drawn into a new war in the Middle East? Can the U.S. manage multiple conflicts, already deeply involved in supporting Ukraine? Is the U.S. economy resilient enough to withstand trade disruptions? How can businesses strengthen their own resiliency?

Economic Protectionism Increasing Costs and Risks

Geopolitical tensions, the global pandemic and the unequal benefits of globalization are impacting economic policies of the U.S. and the political discourse around the merits of unrestrained free trade. Protectionist economic policies are creeping in, under the nomenclature of “secure supply chains,” “friend-shoring” and “home-shoring.” The U.S. has imposed tariffs on countries (even allies) accused of unfair trade practices and has foreclosed access to certain technologies by unfriendly countries, namely China.

While the response to some of these trade restrictions are new trade agreements with “friends” to regulate access under preferred terms, in essence creating multiple “friends” trade blocs for specific sectors, other responses are retaliatory, including counter tariffs and export restrictions or outright bans. In 2024, the U.S. economy will see the impact of these trade fragmentation policies in acute ways, with upside risks of new business opportunities and downside risks of supply chain disruptions, critical resource competition, increased input costs, compliance risks and increased reputational risks.

Trade with China, which remains significant and important to the stability of the U.S. economy, will pose new risks in 2024. While Washington and Beijing have agreed to some political and security guardrails to manage the relationship, economic competition is unrestrained and stability in the bilateral relations is not guaranteed. The December 2023 bipartisan report by the House Select Committee on the Strategic Competition Between the United States and the Chinese Communist Party, with its 150 recommendations on fundamentally resetting economic and technological competition with China, if even partially adopted, risks reigniting the trade war.

2024 is a presidential election year for the U.S. A change of control of the executive branch could result in many economic and regulatory policy reversals. The definition of “friend” could shift or narrow. Restrictions on trade with China could accelerate.

Impacts of Climate Change and Sustainability Policies

2023 was the hottest year on record, and El Niño conditions are expected to further boost the warming trend. Many regions experienced record-breaking wildfire activity in 2023, including Canada where 18 million hectares of land burned. Extreme storms caused life-threatening flooding in Europe, Asia and the Americas. 2024 is expected to bring even more climate hazards. The impacts will be physical and financial, including growing insurance losses and adverse impacts on operations and value chain. Analysts expect that in 2024, the economic and financial costs of adverse health impacts from climate change will increase, with risks related to the spread of infectious disease, insufficient access to clean water, and physical harm to the elderly and vulnerable. The direct economic effect will be on health systems, but also loss of productivity due to extreme weather incidents and effects of epidemics.

Energy transition to low-carbon emissions is underway in the U.S., but it is uneven and still uncertain. The financial market is investing in an impressive number of startups and large-scale projects revolving around cleantech. Still, there is hesitancy on the opportunity and risks of sustainability. Thus far, progress towards sustainability goals has been private sector-led and government-enabled. There is a risk that government incentive programs encouraging the transition to low-carbon energy could be reversed or curtailed under a new administration.

In 2024, some companies will face more climate disclosure compliance requirements. The Securities and Exchange Commission (SEC) is expected to release its final rule on climate change disclosures. The final action has been delayed several times because of pushback by public companies on some of the requirements, including Scope 3 greenhouse gas emission disclosures (those linked to supply chains and end users). California has not waited for the SEC’s final rule: In October 2023, Gov. Gavin Newsom signed into law legislation that will require large companies to disclose greenhouse gas emissions. The California climate laws go into effect in 2026, but companies will need to start much earlier to build the capabilities to plan, track and report their carbon footprint. For U.S. companies doing business in the European Union, they will need to comply with the EU Corporate Sustainability Reporting Directive, with the rules coming into force mid-2024.

Disruptive Technology

In 2023, generative AI was the talk of the town; in 2024, it will be the walk. Companies are popping up with new tools for every imaginable sector, to increase efficiency, task automation, customization, personalization and cost reduction. Business leaders are scrambling to integrate AI to gain a competitive edge, while navigating the everyday risks related to privacy, liability and security. While there are concerns that AI will displace humans, there is a growing consensus that while some jobs will disappear, people will focus on higher value work. That said, new rounds of labor disruptions linked to workforce transition are likely in 2024.

2024 will also bring AI-generated misinformation and disinformation. Bad actors will spread “synthetic” content, such as sophisticated voice cloning, doctored images and counterfeit websites, seeking to manipulate people, damage companies and economies, and foment dissent.

In 2024, around 2 billion people in more than 50 countries will vote in elections at risk of manipulation by misinformation and disinformation, which could destabilize the real and perceived legitimacy of newly elected governments, risking political unrest, violence, terrorism and erosion of democratic processes. Large democracies will hold elections in 2024, including the U.S., the EU, Mexico, South Korea, India, Pakistan, Indonesia and South Africa. Synthetic content can be very difficult to detect, while easy to produce with AI tools.

This is not a theoretical threat; synthetic content is already being disseminated in the U.S., targeting New Hampshire voters with robocalls that share fake recorded messages from President Biden encouraging people not to vote in the primary election. The U.S. is already polarized with citizens distrustful of the government and media, a ready vulnerability. Businesses are not immune. Notably, CEOs have stood apart, with higher ratings for trustworthiness and risk being called upon to vouch for “truth” (and becoming collateral damage in the fray).

AI-powered malware will make 2023 cyber risks look like child’s play. Attackers can use AI algorithms to find and exploit software vulnerabilities, making attacks precise and effective. AI can help hackers quickly identify security measures and evade them. AI-created phishing attacks will be more sophisticated and difficult to detect because the algorithms can assess larger amounts of piecemeal information and craft messages that mimic communication styles.

The role of states backing cyber armies to spread disinformation or steal information is growing and is part and parcel of the erosion of the existing international order. States face little deterrence from digital cross-border attacks because there are yet to be established mechanisms to impose real costs.

© 2024 Bradley Arant Boult Cummings LLP
For more on Business Risks, visit the NLR Corporate & Business Organizations section.

Can Artificial Intelligence Assist with Cybersecurity Management?

AI has great capability to both harm and to protect in a cybersecurity context. As with the development of any new technology, the benefits provided through correct and successful use of AI are inevitably coupled with the need to safeguard information and to prevent misuse.

Using AI for good – key themes from the European Union Agency for Cybersecurity (ENISA) guidance

ENISA published a set of reports earlier last year focused on AI and the mitigation of cybersecurity risks. Here we consider the main themes raised and provide our thoughts on how AI can be used advantageously*.

Using AI to bolster cybersecurity

In Womble Bond Dickinson’s 2023 global data privacy law survey, half of respondents told us they were already using AI for everyday business activities ranging from data analytics to customer service assistance and product recommendations and more. However, alongside day-to-day tasks, AI’s ‘ability to detect and respond to cyber threats and the need to secure AI-based application’ makes it a powerful tool to defend against cyber-attacks when utilized correctly. In one report, ENISA recommended a multi-layered framework which guides readers on the operational processes to be followed by coupling existing knowledge with best practices to identify missing elements. The step-by-step approach for good practice looks to ensure the trustworthiness of cybersecurity systems.

Utilizing machine-learning algorithms, AI is able to detect both known and unknown threats in real time, continuously learning and scanning for potential threats. Cybersecurity software which does not utilize AI can only detect known malicious codes, making it insufficient against more sophisticated threats. By analyzing the behavior of malware, AI can pin-point specific anomalies that standard cybersecurity programs may overlook. Deep-learning based program NeuFuzz is considered a highly favorable platform for vulnerability searches in comparison to standard machine learning AI, demonstrating the rapidly evolving nature of AI itself and the products offered.

A key recommendation is that AI systems should be used as an additional element to existing ICT, security systems and practices. Businesses must be aware of the continuous responsibility to have effective risk management in place with AI assisting alongside for further mitigation. The reports do not set new standards or legislative perimeters but instead emphasize the need for targeted guidelines, best practices and foundations which help cybersecurity and in turn, the trustworthiness of AI as a tool.

Amongst other factors, cybersecurity management should consider accountability, accuracy, privacy, resiliency, safety and transparency. It is not enough to rely on traditional cybersecurity software especially where AI can be readily implemented for prevention, detection and mitigation of threats such as spam, intrusion and malware detection. Traditional models do exist, but as ENISA highlights they are usually designed to target or’address specific types of attack’ which, ‘makes it increasingly difficult for users to determine which are most appropriate for them to adopt/implement.’ The report highlights that businesses need to have a pre-existing foundation of cybersecurity processes which AI can work alongside to reveal additional vulnerabilities. A collaborative network of traditional methods and new AI based recommendations allow businesses to be best prepared against the ever-developing nature of malware and technology based threats.

In the US in October 2023, the Biden administration issued an executive order with significant data security implications. Amongst other things, the executive order requires that developers of the most powerful AI systems share safety test results with the US government, that the government will prepare guidance for content authentication and watermarking to clearly label AI-generated content and that the administration will establish an advanced cybersecurity program to develop AI tools and fix vulnerabilities in critical AI models. This order is the latest in a series of AI regulations designed to make models developed in the US more trustworthy and secure.

Implementing security by design

A security by design approach centers efforts around security protocols from the basic building blocks of IT infrastructure. Privacy-enhancing technologies, including AI, assist security by design structures and effectively allow businesses to integrate necessary safeguards for the protection of data and processing activity, but should not be considered as a ‘silver bullet’ to meet all requirements under data protection compliance.

This will be most effective for start-ups and businesses in the initial stages of developing or implementing their cybersecurity procedures, as conceiving a project built around security by design will take less effort than adding security to an existing one. However, we are seeing rapid growth in the number of businesses using AI. More than one in five of our survey respondents (22%), for instance, started to use AI in the past year alone.

However, existing structures should not be overlooked and the addition of AI into current cybersecurity system should improve functionality, processing and performance. This is evidenced by AI’s capability to analyze huge amounts of data at speed to provide a clear, granular assessment of key performance metrics. This high-level, high-speed analysis allows businesses to offer tailored products and improved accessibility, resulting in a smoother retail experience for consumers.

Risks

Despite the benefits, AI is by no-means a perfect solution. Machine-learning AI will act on what it has been told under its programming, leaving the potential for its results to reflect an unconscious bias in its interpretation of data. It is also important that businesses comply with regulations (where applicable) such as the EU GDPR, Data Protection Act 2018, the anticipated Artificial Intelligence Act and general consumer duty principles.

Cost benefits

Alongside reducing the cost of reputational damage from cybersecurity incidents, it is estimated that UK businesses who use some form of AI in their cybersecurity management reduced costs related to data breaches by £1.6m on average. Using AI or automated responses within cybersecurity systems was also found to have shortened the average ‘breach lifecycle’ by 108 days, saving time, cost and significant business resource. Further development of penetration testing tools which specifically focus on AI is required to explore vulnerabilities and assess behaviors, which is particularly important where personal data is involved as a company’s integrity and confidentiality is at risk.

Moving forward

AI can be used to our advantage but it should not been seen to entirely replace existing or traditional models to manage cybersecurity. While AI is an excellent long-term assistant to save users time and money, it cannot be relied upon alone to make decisions directly. In this transitional period from more traditional systems, it is important to have a secure IT foundation. As WBD suggests in our 2023 report, having established governance frameworks and controls for the use of AI tools is critical for data protection compliance and an effective cybersecurity framework.

Despite suggestions that AI’s reputation is degrading, it is a powerful and evolving tool which could not only improve your business’ approach to cybersecurity and privacy but with an analysis of data, could help to consider behaviors and predict trends. The use of AI should be exercised with caution, but if done correctly could have immeasurable benefits.

___

* While a portion of ENISA’s commentary is focused around the medical and energy sectors, the principles are relevant to all sectors.

Copyright © 2024 Womble Bond Dickinson (US) LLP All Rights Reserved.
For more on Artificial Intelligence, visit the NLR Communications, Media & Internet section

Exploring the Future of Information Governance: Key Predictions for 2024

Information governance has evolved rapidly, with technology driving the pace of change. Looking ahead to 2024, we anticipate technology playing an even larger role in data management and protection. In this blog post, we’ll delve into the key predictions for information governance in 2024 and how they’ll impact businesses of all sizes.

  1. Embracing AI and Automation: Artificial intelligence and automation are revolutionizing industries, bringing about significant changes in information governance practices. Over the next few years, it is anticipated that an increasing number of companies will harness the power of AI and automation to drive efficient data analysis, classification, and management. This transformative approach will not only enhance risk identification and compliance but also streamline workflows and alleviate administrative burdens, leading to improved overall operational efficiency and effectiveness. As organizations adapt and embrace these technological advancements, they will be better equipped to navigate the evolving landscape of data governance and stay ahead in an increasingly competitive business environment.
  2. Prioritizing Data Privacy and Security: In recent years, data breaches and cyber-attacks have significantly increased concerns regarding the usage and protection of personal data. As we look ahead to 2024, the importance of data privacy and security will be paramount. This heightened emphasis is driven by regulatory measures such as the California Consumer Privacy Act (CCPA) and the European Union’s General Data Protection Regulation (GDPR). These regulations necessitate that businesses take proactive measures to protect sensitive data and provide transparency in their data practices. By doing so, businesses can instill trust in their customers and ensure the responsible handling of personal information.
  3. Fostering Collaboration Across Departments: In today’s rapidly evolving digital landscape, information governance has become a collective responsibility. Looking ahead to 2024, we can anticipate a significant shift towards closer collaboration between the legal, compliance, risk management, and IT departments. This collaborative effort aims to ensure comprehensive data management and robust protection practices across the entire organization. By adopting a holistic approach and providing cross-functional training, companies can empower their workforce to navigate the complexities of information governance with confidence, enabling them to make informed decisions and mitigate potential risks effectively. Embracing this collaborative mindset will be crucial for organizations to adapt and thrive in an increasingly data-driven world.
  4. Exploring Blockchain Technology: Blockchain technology, with its decentralized and immutable nature, has the tremendous potential to revolutionize information governance across industries. By 2024, as businesses continue to recognize the benefits, we can expect a significant increase in the adoption of blockchain for secure and transparent transaction ledgers. This transformative technology not only enhances data integrity but also mitigates the risks of tampering, ensuring trust and accountability in the digital age. With its ability to provide a robust and reliable framework for data management, blockchain is poised to reshape the way we handle and secure information, paving the way for a more efficient and trustworthy future.
  5. Prioritizing Data Ethics: As data-driven decision-making becomes increasingly crucial in the business landscape, the importance of ethical data usage cannot be overstated. In the year 2024, businesses will place even greater emphasis on data ethics, recognizing the need to establish clear guidelines and protocols to navigate potential ethical dilemmas that may arise. To ensure responsible and ethical data practices, organizations will invest in enhancing data literacy among their workforce, prioritizing education and training initiatives. Additionally, there will be a growing focus on transparency in data collection and usage, with businesses striving to build trust and maintain the privacy of individuals while harnessing the power of data for informed decision-making.

The future of information governance will be shaped by technology, regulations, and ethical considerations. Businesses that adapt to these changes will thrive in a data-driven world. By investing in AI and automation, prioritizing data privacy and security, fostering collaboration, exploring blockchain technology, and upholding data ethics, companies can prepare for the challenges and opportunities of 2024 and beyond.

Jim Merrifield, Robinson+Cole’s Director of Information Governance & Business Intake, contributed to this report.

Copyright © 2023 Robinson & Cole LLP. All rights reserved.
For more on Information Governance, visit the NLR Communications, Media & Internet section.

5 Trends to Watch: 2024 Emerging Technology

  1. Increased Adoption of Generative AI and Push to Minimize Algorithmic Biases – Generative AI took center stage in 2023 and popularity of this technology will continue to grow. The importance behind the art of crafting nuanced and effective prompts will heighten, and there will be greater adoption across a wider variety of industries. There should be advancements in algorithms, increasing accessibility through more user-friendly platforms. These can lead to increased focus on minimizing algorithmic biases and the establishment of guardrails governing AI policies. Of course, a keen awareness of the ethical considerations and policy frameworks will help guide generative AI’s responsible use.
  2. Convergence of AR/VR and AI May Result in “AR/VR on steroids” The fusion of Augmented Reality (AR) and Virtual Reality (VR) technologies with AI unlocks a new era of customization and promises enhanced immersive experiences, blurring the lines between the digital and physical worlds. We expect to see further refining and personalizing of AR/VR to redefine gaming, education, and healthcare, along with various industrial applications.
  3. EV/Battery Companies Charge into Greener Future. With new technologies and chemistries, advancements in battery efficiency, energy density, and sustainability can move the adoption of electric vehicles (EVs) to new heights. Decreasing prices for battery metals canbatter help make EVs more competitive with traditional vehicles. AI may providenew opportunities in optimizing EV performance and help solve challenges in battery development, reliability, and safety.
  4. “Rosie the Robot” is Closer than You Think. With advancements in machine learning algorithms, sensor technologies, and integration of AI, the intelligence and adaptability of robotics should continue to grow. Large language models (LLMs) will likely encourage effective human-robot collaboration, and even non-technical users will find it easy to employ robotics to accomplish a task. Robotics is developing into a field where machines can learn, make decisions, and work in unison with people. It is no longer limited to monotonous activities and repetitive tasks.
  5. Unified Defense in Battle Against Cyber-Attacks. Digital threats are expected to only increase in 2024, including more sophisticated AI-powered attacks. As the international battle against hackers wages on, threat detection, response, and mitigation will play a crucial role in staying ahead of rapidly evolving cyber-attacks. As risks to national security and economic growth, there should be increased collaboration between industries and governments to establish standardized cybersecurity frameworks to protect data and privacy.
©2023 Greenberg Traurig, LLP. All rights reserved.
For more news on emerging technologies, visit the NLR Communications, Media & Internet section.

Algorithmic Pricing Agents and Price-Fixing Facilitators: Antitrust Law’s Latest Conundrum

Are machines doing the collaborating that competitors may not?

It is an application of artificial intelligence (“AI”) that many businesses, agencies, legislators, lawyers, and antitrust law enforcers around the world are only beginning to confront. It is also among the top concerns of in-house counsel across industries. Competitors are increasingly setting prices through the use of communal, AI-enhanced algorithms that analyze data that are private, public, or a mix of both.

Allegations in private and public litigation describe “algorithmic price fixing” in which the antitrust violation occurs when competitors feed and access the same database platform and use the same analytical tools. Then, as some allege, the violations continue when competitors agree to the prices produced by the algorithms. Right now, renters and prosecutors are teeing off on the poster child for algorithmic pricing, RealPage Inc., and the many landlords and property managers who use it.

PRIVATE AND PUBLIC LITIGATION

A Nov. 1, 2023 complaint filed by the Washington, DC, Attorney General’s office described RealPage’s offerings this way: “[A] variety of technology-based services to real estate owners and property managers including revenue management products that employ statistical models that use data—including non-public, competitively sensitive data—to estimate supply and demand for multifamily housing that is specific to particular geographic areas and unit types, and then generate a ‘price’ to charge for renting those units that maximizes the landlord’s revenue.”

The complaint alleges that more than 30% of apartments in multifamily buildings and 60% of units in large multifamily buildings nationwide are priced using the RealPage software. In the Washington-Arlington-Alexandria Metropolitan Area that number leaps to more than 90% of units in large buildings. The complaint alleges that landlords have agreed to set their rates using RealPage.

Private actions against RealPage have also been filed in federal courts across the country and have been centralized in multi-district litigation in the Middle District of Tennessee (In re: RealPage, Inc., Rental Software Antitrust Litigation [NO. II], Case No. 3:23-md-3071, MDL No. 3071). The Antitrust Division of the Department of Justice filed a Statement of Interest and a Memorandum in Support in the case urging the court to deny the defendants’ motion to dismiss.

Even before the MDL, RealPage had attracted the Antitrust Division’s attention when the company acquired its largest competitor, Lease Rent Options for $300 million, Axiometrics for $75 million, and On-Site Manager, Inc. for $250 million.

The Antitrust Division has been pursuing the use of algorithms in other industries, including airlines and online retailers. The DOJ and FTC are both studying the issue and reaching out to experts to learn more.

JOURNALISTS AND SENATORS

Additionally, three senators urged DOJ  to investigate RealPage after reporters at ProPublica wrote an investigative report in October 2022. The journalists claim that RealPage’s price-setting software “uses nearby competitors’ nonpublic rent data to feed an algorithm that suggests what landlords should charge for available apartments each day.” ProPublica speculated that the algorithm is enabling landlords to coordinate prices and in the process push rents above competitive levels in violation of the antitrust laws.

Senators Amy Klobuchar (D-MN), Dick Durban (D-IL) and Cory Booker (D-NJ) wrote to the DOJ concerned that the RealPage enables “a cartel to artificially inflate rental rates in multifamily residential buildings.”

Sen. Sherrod Brown (D-OH) also wrote to the Federal Trade Commission with concerns “about collusion in the rental market,” urging the FTC to “review whether rent setting algorithms that analyze rent prices through the use of competitors’ private data … violate antitrust laws.” The Ohio senator specifically mentioned RealPage’s YieldStar and AI Revenue Management programs.

THE EUROPEANS

The European Commission has enacted the Artificial Intelligence Act, which includes provisions on algorithmic pricing, requiring algorithmic pricing systems be transparent, explainable, and non-discriminatory with regard to consumers. Companies that use algorithmic pricing systems will be required to implement compliance procedures, including audits, data governance, and human oversight.

THE LEGAL CONUNDRUM

An essential element of any claimed case of price-fixing under the U.S. antitrust laws is the element of agreement: a plaintiff alleging price-fixing must prove the existence of an agreement between two or more competitors who should be setting their prices independently but aren’t. Consumer harm from collusion occurs when competitors set prices to achieve their maximum joint profit instead of setting prices to maximize individual profits. To condemn algorithmic pricing as collusion, therefore, requires proof of agreement.

It may be difficult for the RealPage plaintiffs to prove that the RealPage’s users agreed among themselves to adhere to any particular price or pricing formula, but not impossible. End users are likely to argue that RealPage’s pricing recommendations are merely aggregate market signals that RealPage is collecting and disseminating. The use of the same information service, their argument will go, does not prove the existence of an agreement for purposes of Section 1 of the Sherman Act.

The parties and courts embroiled in the RealPage litigation are constrained to live under the law as it presently exists, so the solution proposed by Michal Gal, Professor and Director of the Forum on Law and Markets at the University of Haifa, is out of reach. In her 2018 paper, “Algorithms as Illegal Agreements,” Professor Gal confronts the agreement problem when algorithms set prices and concludes that it is time to “rethink our laws and focus on reducing harms to social welfare rather than on what constitutes an agreement.” Academics have been critical of the agreement element of Section 1 for years, but it is unlikely to change anytime soon, even with the added inconvenience it poses where competitors rely on a common vendor of machine-generated pricing recommendations.

Nonetheless, there is some evidence that autonomous machines, just like humans, can learn that collusion allows sellers to charge monopoly prices. In their December 2019 paper, “Artificial Intelligence, Algorithmic Pricing and Collusion,” Emilio Calvano, Giacomo Calzolari, Vincenzo Denicolo, and Sergio Pastorello at the Department of Economics at the University of Bologna showed with computer simulations that machines autonomously analyzing prices can develop collusive strategies “from scratch, engaging in active experimentation and adapting to changing environments.” The authors say indications from their models “suggest that algorithmic collusion is more than a remote theoretical possibility.” They find that “relatively simple [machine learning] pricing algorithms systematically learn to play collusive strategies.” The authors claim to be the first to “clearly document the emergence of collusive strategies among autonomous pricing agents.”

THE AGREEMENT ELEMENT IN THE MACHINE PRICING CASE

For three main reasons, the element of agreement need not be an obstacle to successfully prosecuting a price-fixing claim against competitors that use a common or similar vendor of algorithmic pricing data and software.

First, there is significant precedent for inferring the existence of an agreement among parties that knowingly participate in a collusive arrangement even if they do not directly interact, sometimes imprecisely referred to as a “rimless wheel hub-and-spoke” conspiracy. For example, in Toys “R” Us, Inc. v. F.T.C., 221 F.3d 928 (9th Cir. 2000), the court inferred the necessary concerted action from a series of individual agreements between toy manufacturers and Toys “R” Us in which the manufacturers promised not to sell the toys sold to Toys “R” Us and other toy stores to big box stores in the same packaging. The FTC found that each of the manufacturers entered into the restraint on the condition that the others also did so. The court found that Toys “R” Us had engineered a horizontal boycott against a competitor in violation of Section 1, despite the absence of evidence of any “privity” between the boycotting manufacturers.

The Toys “R” Us case relied on the Supreme Court’s decision in Interstate Circuit v. United States, 306 U.S. 208 (1939), in which movie theater chains sent an identical letter to eight movie studios asking them to restrict secondary runs of certain films. The letter disclosed that each of the eight were receiving the same letter. The Court held that a direct agreement was not a prerequisite for an unlawful conspiracy. “It was enough that, knowing that concerted action was contemplated and invited, the distributors gave their adherence to the scheme and participated in it.”

The analogous issue in the algorithmic pricing scenario is whether the vendor’s end users that their competitors are also end users. If so, the inquiry can consider the agreement element satisfied if the algorithm does, in fact, jointly maximize the end users’ profits.

The second factor overcoming the agreement element is related to the first. Whether software that recommends prices has interacted with the prices set by competitors to achieve joint profit maximization—that is, whether the machines have learned to collude without human intervention—is an empirical question. The same techniques used to uncover machine-learned collusion by simulation can be used to determine the extent of interdependence in historical price setting. If statistical evidence of collusive pricing is available, it is enough that the end users knowingly accepted the offer to set its prices guided by the algorithm. The economics underlying the agreement element in the first place lies in prohibition of joint rather than individual profit maximization, so direct evidence that market participants are jointly profit maximizing should obviate the need for further evidence of agreement.

A third reason the agreement element need not stymie a Section 1 action against defendants engaged in algorithmic pricing is based on the Supreme Court’s decision in American Needle v. NFL, 560 U.S. 183 (2010). In that case the Court made clear that arrangements that remove independent centers of decision-making from the market run afoul of Section 1, if the net effect of the algorithm is to displace individual decision-making with decisions outsourced to a centralized pricing agent, the mechanism should be immaterial.

The rimless wheel of the so-called hub-and-spoke conspiracy is an inadequate analogy because the wheel in these cases does have a rim, i.e., a connection between the conspirators. In the scenarios above in which the courts have found Section 1 liability i) each of the participants knew that its rivals were also entering into the same or similar arrangements, ii) the participants devolved pricing authority away from themselves down to an algorithmic pricing agent, and iii) historical prices could be shown statistically to have exceeded the competitive level in a way consistent with collusive pricing. These elements connect the participants in the scheme, supplying the “rim” to the spokes of the wheel. If the plaintiffs in the RealPage litigation can establish these elements, they will have met their burden of establishing the requisite element of agreement in their Section 1 claim.

© MoginRubin LLP
For more news on AI in the context of Antitrust Law, visit the NLR’s Communications, Media & Internet section.

What Employers Need to Know about the White House’s Executive Order on AI

President Joe Biden recently issued an executive order devised to establish minimum risk practices for use of generative artificial intelligence (“AI”) with focus on rights and safety of people, with many consequences for employers. Businesses should be aware of these directives to agencies, especially as they may result in new regulations, agency guidance and enforcements that apply to their workers.

Executive Order Requirements Impacting Employers

Specifically, the executive order requires the Department of Justice and federal civil rights offices to coordinate on ‘best practices’ for investigating and prosecuting civil rights violations related to AI. The ‘best practices’ will address: job displacement; labor standards; workplace equity, health, and safety; and data collection. These principles and ‘best practices’ are focused on benefitting workers and “preventing employers from undercompensating workers, evaluating job applications unfairly, or impinging on workers’ ability to organize.”

The executive order also requested a report on AI’s potential labor-market impacts, and to study and identify options for strengthening federal support for workers facing labor disruptions, including from AI. Specifically, the president has directed the Chairman of the Council of Economic Advisers to “prepare and submit a report to the President on the labor-market effects of AI”. In addition, there is a requirement for the Secretary of Labor to submit “a report analyzing the abilities of agencies to support workers displaced by the adoption of AI and other technological advancements.” This report will include principles and best practices for employers that could be used to mitigate AI’s potential harms to employees’ well-being and maximize its potential benefits. Employers should expect more direction once this report is completed in April 2024.

Increasing International Employment?

Developing and using generative AI inherently requires skilled workers, which President Biden recognizes. One of the goals of his executive order is to “[u]se existing authorities to expand the ability of highly skilled immigrants and nonimmigrants with expertise in critical areas to study, stay, and work in the United States by modernizing and streamlining visa criteria, interviews, and reviews.” While work visas have been historically difficult for employers to navigate, this executive order may make it easier for US employers to access skilled workers from overseas.

Looking Ahead

In light of the focus of this executive order, employers using AI for recruiting or decisions about applicants (and even current employees) must be aware of the consequences of not putting a human check on the potential bias. Working closely with employment lawyers at Sheppard Mullin and having a multiple checks and balances on recruiting practices are essential when using generative AI.

While this executive order is quite limited in scope, it is only a first step. As these actions are implemented in the coming months, be sure to check back for updates.

Copyright © 2023, Sheppard Mullin Richter & Hampton LLP.
By Carina L. Novell of Sheppard, Mullin, Richter & Hampton LLP
For more news on the Impact of the Executive Order on AI for Employers, visit the NLR Communications, Media & Internet section.

The FCC Approves an NOI to Dive Deeper into AI and its Effects on Robocalls and Robotexts

AI is on the tip of everyone’s tongue it seems these days. The Dame brought you a recap of President Biden’s orders addressing AI at the beginning of the month. This morning at the FCC’s open meeting they were presented with a request for a Notice of Inquiry (NOI) to gather additional information about the benefits and harms of artificial intelligence and its use alongside “robocall and robotext”. The following five areas of interest are as follows:

  • First, the NOI seeks, on whether and if so how the commission should define AI technologies for purposes of the inquiry this includes particular uses of AI technologies that are relevant to the commission’s statutory response abilities under the TCPA, which protects consumers from nonemergency calls and texts using an autodialer or containing an artificial or prerecorded voice.
  • Second, the NOI seeks comment on how technologies may impact consumers who receive robocalls and robotexts including any potential benefits and risks that the emerging technologies may create. Specifically, the NOI seeks information on how these technologies may alter the functioning of the existing regulatory framework so that the commission may formulate policies that benefit consumers by ensuring they continue to receive privacy protections under the TCPA.
  • Third, the NOI seeks comment on whether it is necessary or possible to determine at this point whether future types of AI technologies may fall within the TCPA’s existing prohibitions on autodial calls or texts and artificial or prerecorded voice messages.
  • Fourth, NOI seeks comment on whether the commission should consider ways to verify the authenticity and legitimately generate AI voice or text content from trusted sources such as through the use of watermarks, certificates, labels, signatures, or other forms of labels when callers rely on AI technology to generate content. This may include, for example, emulating a human voice on a robocall or creating content in a text message.
  • Lastly, seeks comment on what next steps the commission should consider to further the inquiry.

While all the commissioners voted to approve the NOI they did share a few insightful comments. Commissioner Carr stated “ If AI can combat illegal robocalls, I’m all for it” but he also expressed that he does “…worry that the path we are heading down is going to be overly prescriptive” and suggests “…Let’s put some common-sense guardrails in place, but let’s not be so prescriptive and so heavy-handed on the front end that we end up benefiting large incumbents in the space because they can deal with the regulatory frameworks and stifling the smaller innovation to come.”

Commissioner Starks shared “I, for one, believe this intersectionality is clinical because the future of AI remains uncertain, one thing is clear — it has the potential to impact if not transform every aspect of American life, and because of that potential, each part of our government bears responsibility to better understand the risks, opportunities within its mandate, while being mindful of the limits of its expertise, experience, and authority. In this era of rapid technological change, we must collaborate, lean into our expertise across agencies to best serve our citizens and consumers.” Commissioner Starks seemed to be particularly focused on AI’s ability to facilitate bad actors in schemes like voice cloning and how the FCC can implement safeguards against this type of behavior.

“AI technologies can bring new challenges and opportunities. responsible and ethical implementation of AI technologies is crucial to strike a balance, ensuring that the benefits of AI are harnessed to protect consumers from harm rather than amplifying the risks in increasing the digital landscape” Commissioner Gomez shared.

Finally, the topic around the AI NOI wrapped up with Chairwoman Rosenworcel commenting “… I think we make a mistake if we only focus on the potential for harm. We needed to equally focus on how artificial intelligence can radically improve the tools we have today to block unwanted robocalls and robotexts. We are talking about technology that can see patterns in our network traffic, unlike anything we have today. They can lead to the development of analytic tools that are exponentially better at finding fraud before it reaches us at home. Used at scale, we cannot only stop this junk, we can use it to increase trust in our networks. We are asking how artificial intelligence is being used right now to recognize patterns in network traffic and how it can be used in the future. We know the risks this technology involves but we also want to harness the benefits.”

© 2023 Troutman Amin, LLP
For more news on AI and its Impact on Robocalls and Robotexts, visit the NLR Communications, Media & Internet section.