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Tag: Artificial Intelligence (AI)

The Light and Dark Sides of Auto-GPT

The Light and Dark Sides of Auto-GPT with Jason Epstein

Auto-GPT is a new generative artificial intelligence application which autonomously “self-prompts” to engage beyond a human-chatbot discussion.

This takes us into a realm of AI self-prompted actions that do not need additional human inputs. It also potentially puts the “traditional” GPT models on a fast track to further reduce human interaction. The number of use cases as well as the number of legal and ethical questions is inevitable. For that reason, it’s becoming increasingly important for businesses to understand how Auto-GPT technologies use data, the potential for biased results, and how to responsibly leverage these powerful technologies.

Listen to my interview with Jason I. Epstein, Partner at Nelson Mullins Riley & Scarborough as we explore this emerging field. Jason is the co-head of the firm’s technology and procurement industry group which provides legal services to global buyers and sellers of technology in industries that include FinTech, HealthIT, and manufacturing. An experienced business and technology negotiator, Jason has dealt with a variety of matters, e.g., the metaverse, technology transfer, privacy, cryptocurrency, IoT, open-source code, and more. Jason received his JD from the University of Tennessee College of Law. He formerly taught “Law of Cyberspace” as an adjunct professor at Vanderbilt University Law School.

I hope you enjoy the episode. If so, give us a rating!

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This podcast is the audio companion to the Journal on Emerging Issues in Litigation. The Journal is a collaborative project between HB Litigation Conferences and the Fastcaselegal research family, which includes Full Court Press, Law Street Media, and Docket Alarm. The podcast itself is a joint effort between HB and our friends at Law Street Media. If you have comments or wish to participate in one our projects please drop me a note at Editor@LitigationConferences.com.

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Jason EpsteinNelson Mullins Riley & Scarborough

Jason Epstein is the co-head of the firm’s technology and procurement industry group. Jason and the technology team provide legal services to buyers and sellers of technology both domestically and internationally in various industries, from FinTech and HealthIT to auto and manufacturing

He often serves as outside general counsel and relationship partner to companies in a variety of industries. His areas of focus include board governance, technology, venture capital and private equity, mergers and acquisitions, reorganizations, international commerce, and litigation. Whether advising clients of Fortune 500, mid-market, or small businesses (including under the SBA), he serves as an advisor to the C-Suite and inside General Counsel regarding business-related law.

August 2, 2023
Does the European Union Commission’s Proposal on AI Liability Act as a Game Changer for Fault-Based Liability Regimes in the EU?

Guest Writer

Nils LölfingBird & Bird LLP

Does the European Union Commission’s Proposal on AI Liability Act as a Game Changer for Fault-Based Liability Regimes in the EU?

By Nils Lölfing

Photo by Christian Lue on Unsplash

Abstract: In this article, the author discusses increasing risks that artificial intelligence system providers, developers, and users will face from a liability directive proposed by the European Union Commission.

The AI Liability Directive proposed by the European Union Commission puts additional liability risks on providers, developers and users of specifically high-risk artificial intelligence (AI) systems. If enacted, it could become a game changer for fault-based liability regimes in the European Union, as it introduces a presumption of causality to prove fault and a right of access to evidence from companies and suppliers regarding high-risk AI systems. This will help victims enforce non-contractual civil law claims for damages caused by an AI system.

What this is about and how it increases the liability risk exposure of actors in the AI systems supply chain will be discussed in this article.

Background

On September 28, 2022, the EU Commission published its proposal for a Directive to establish new fault-based liability rules for AI systems (AI Liability Directive), along with a reform for the existing rules on the strict liability of manufacturers for defective products. The current article focuses on the draft AI Liability Directive, which complements the AI Act by facilitating fault-based civil liability claims for damages, which the AI Act as specific product safety Regulation does not offer.

On June 30, 2021, the EU Commission published an inception impact assessment road map on adapting civil liability rules to the digital age, in particular considering AI (based on the EU Commission’s White Paper on AI of February 19, 2020). With respect to AI in particular, the AI liability proposal is part of the approach by the EU Commission to develop an ecosystem of trust for AI (together with the proposed AI Act and the revised Product Safety and Machinery Directive).

The proposal addresses the peculiarities tied to AI such as autonomous behavior and limited predictability, when applying fault-based liability rules. According to the EU Commission, the peculiarities of AI create legal uncertainties for businesses and make it difficult for consumers and other injured parties to receive compensation. In fact, in a representative survey of 2021, liability ranked among the top three barriers to the use of AI by European companies that are planning to but have not yet adopted AI.

These new requirements, such as a presumption of the burden of proof, have the potential to fundamentally change the EU’s liability regime and will increase the exposure to liability risks for businesses who are involved in manufacturing, distributing, or using AI.

What Is It All About and Why Is It a Potential Game Changer?

The AI Liability Directive proposal intends to enable consumers and businesses injured by AI-based products like robots, drones, or smart-home systems to claim compensation more easily by way of non-contractual civil law claims for damages caused by such AI systems. The proposal generally covers any type of AI system (although, like the AI Act, it seems to predominantly intend to cover highrisk AI) and obliges providers, developers, and users of AI systems to compensate any type of damage covered by national law (life, health, property, privacy, discrimination, etc.) and for any type of victim (individuals, companies, organizations, etc.). This requires errors made by someone from within the supply chain, such as a provider, developer, or user of an AI system who caused the damages. Because of the peculiarities mentioned in AI systems, it will typically be difficult to prove a wrongful action or omission by a provider, developer, or user of an AI system.

Therefore, the AI Liability Directive proposal recommends two groundbreaking changes, which will modify common liability rules, as we currently know them across most of the European Union:

• Presumption of causality to prove fault. The proposed AI Liability Directive establishes a rebuttable presumption of causality, to enable claimants to be able to demonstrate a causal link between a failure of an AI system (e.g., in the form of flawed output) and any damage caused to the claimant as the individual or business using the AI system. For example, where certain obligations under the AI Act are not complied with, fault of the relevant person that developed, provided, or used the AI system will be presumed. The presumed fault occurs only if it is reasonably likely, from the circumstances in which the damage occurred, that such fault has influenced the output produced by the AI system or the failure of the AI system to produce an output that gave rise to the damage. Such a fault can also be presumed
by a court of law, on the basis of non-compliance, which would lead to a court order for disclosure or preservation of evidence (detailed in the next point). The presumption of causality generally applies to all AI systems, but in the case of non-high-risk AI systems it only applies where a court determines that it is excessively difficult for the claimant to prove the causal link. If the presumption is triggered, the burden is on the defendant to show that its system is not the cause of the harm suffered.
• Right to access evidence from companies and suppliers regarding high-risk AI. When claiming damages from a high-risk AI system provider, developer, or user, claimants have disclosure powers and may ask the court to order the disclosure of relevant evidence about specific high-risk AI systems that are suspected of having caused damage. For this to happen, the claimant must make its claim plausible and show to a court that the damages were potentially caused by a high-risk AI system. The right to access evidence will ease the proving of claims and identify non-responsible actors in the supply chain much faster. However, commercially sensitive information (like trade secrets) is still protected. The access right does not pertain to AI systems that are not considered high-risk under the AI Act.

What Are the Resulting Risks for Providers, Developers, and Users of AI Systems and How to Protect Against Them?

The proposed AI Liability Directive significantly helps victims that suffered damages through AI systems with the presumption of causality and the right to access evidence, specifically with regard to high-risk AI systems.

Risks for providers, developers, and users of (specifically highrisk) AI systems are not negligible in this regard. Claims brought by the AI Liability Directive can be very broad and far-reaching, as they include any type of damage covered by national law, and therefore typically also include non-material damages, such as for discrimination or potentially even privacy harms resulting from, for example, ad targeting. With the prospect of mass claims, providers, developers, and users of AI systems may see big obstacles in the future.

If the proposed AI Liability Directive is enacted, it will be much more difficult for providers, developers, and users of AI to adequately protect themselves against damage claims due to acts or omissions of their AI systems. Nevertheless, providers, developers, and users of AI systems should find strategies to protect themselves
against the presumption of causality by showing that a fault of their specific AI system could not have caused the damage. Additionally, strategies on how their information can be protected from being disclosed to claimants are sensible to mitigate disproportionate liability risk exposure.

Outlook

Specifically, developers of high-risk AI systems will face additional burden going forward. They not only have to comply with the complementary future AI Act, which is likely to put in place a couple of onerous obligations before their AI systems can be brought on the EU market. Under the AI Liability Directive, developers will also have to find strategies to defend themselves against potential claims as another layer of AI-related legal burdens on top of the AI Act.

However, there is still enough time for providers, developers, and users of AI systems to influence the AI Liability Directive proposal. The European Parliament and the Council will soon start discussing and negotiating the Commission’s proposal. This may still not be the end of the road, at all. For now, the EU Commission has refrained from proposing strict liability regimes for AI systems, although the public consultations have highlighted a preference for such a regime among its respondents (whether with or without insurance).

However, the EU Commission also highlighted that if AI systems could affect the public at large, namely putting a risk to important legal rights, such as the right to life, health, and property, then such strict liability regime will be reconsidered. To monitor developments, the EU Commission put in place a program to obtain information of incidents involving AI systems.

With this information the EU Commission intends to assess whether additional measures would be needed, such as introducing a strict liability regime and/or mandatory insurance. This space must be closely watched!

June 22, 2023
The Blueprint for an “AI Bill of Rights”

Authors

Peter SchildkrautArnold & Porter Kaye Scholer LLP.

Peter Schildkraut is a co-leader of the firm’s Technology, Media & Telecommunications industry team and provides strategic counsel on artificial intelligence, spectrum use, broadband, and other TMT regulatory matters. Mr. Schildkraut helps clients navigate the ever-changing opportunities and challenges of technology, policy, and law to achieve their business objectives at the US Federal Communications Commission (FCC) and elsewhere. He is the author of “AI Regulation: What You Need To Know To Stay Ahead of the Curve.

James KimArnold & Porter Kaye Scholer LLP.

James W. Kim is a nationally recognized expert in procurement law that regularly advises companies that do business with the US government, with a focus on professional services organizations and the life sciences industry. He is a regular speaker and author on procurement and drug pricing matters and his work is regularly featured in nationally-distributed industry print and digital media.

Mr. Kim provides clients with strategic counsel related to US government funding and US market access, including assistance with more than $5 billion in procurement and grant awards and regulatory counsel related to more than $40 billion in successful M&A transactions.

Marne MarottaArnold & Porter Kaye Scholer LLP.

Marne Marotta works with clients facing complex challenges to develop and implement dynamic government relations strategies. Drawing from her experience in the Senate and the executive branch, she provides clients with strategic guidance and counseling, devises and implements comprehensive advocacy campaigns, and builds coalitions with allied stakeholders. Focused on the intersection between business and public policy, Marne uses a multidisciplinary approach to help clients achieve their legislative and agency goals.

James Courtney, Jr.Arnold & Porter Kaye Scholer LLP.

James Courtney focuses his work on a variety of policy areas, including technology, national security, education, and energy and environmental. He conducts research and monitors developing policy issues to aid clients and engage with members of Congress and the Executive Branch. Mr. Courtney works closely with and advises clients on a wide range of regulatory and legislative issues related to technology, privacy, education, workforce development, and energy.

Paul WatersArnold & Porter Kaye Scholer LLP.

Paul Waters focuses on a variety of policy areas, including financial services, tax, digital asset regulation, technology, and defense. He monitors policy developments and analyzes legislation to support client strategy development and stakeholder outreach in Congress and the Executive branch.

First Published inThe Journal of Robotics, Artificial Intelligence & Law

The Journal of Robotics, Artificial Intelligence & Law (RAIL) is the ﬂagship publication of Full Court Press, an imprint of Fastcase. Since 1999, Fastcase has democratized the law and made legal research smarter. Now, Fastcase is proud to publish books and journals that are pioneering, topical, and visionary, written by the law’s leading subject matter experts. Look for more Full Court Press titles available in print, as eBooks, and in the Fastcase legal research service, or at www.fastcase.com/fullcourtpress.

Blueprint for an “Artificial Intelligence Bill of Rights”

Photo by Possessed Photography on Unsplash

Abstract: In this article, the authors discuss the blueprint for an “AI Bill of Rights” unveiled recently by the Biden administration. The blueprint provides a clear indication of the Biden administration’s artificial intelligence regulatory policy goals. This article was first published in The Journal of Robotics, Artificial Intelligence & Law by Fastcase Full Court Press.

More and more, artificial intelligence (AI) and other automated systems make decisions affecting our lives and economy. These systems are not broadly regulated in the United States—although that will change this year in several states. President Biden recently unveiled a blueprint for an “AI Bill of Rights,” motivated by concerns about potential harms from automated decision-making. Arising from an initiative the White House Office of Science and Technology Policy (OSTP) launched in 2021, the AI Bill of Rights lays out five principles to foster policies and practices—and automated systems—that protect civil rights and promote democratic values.

For now, at least, adherence to these principles (and the steps recommended for observing them) remains voluntary—the blueprint is a guidance document with no enforcement authority attached to it. Notably, at inception, OSTP was unsure how the AI Bill of Rights might be enforced:

Possibilities include the federal government refusing to buy software or technology products that fail to respect these rights, requiring federal contractors to use technologies that adhere to this “bill of rights” or adopting new laws and regulations to fill gaps. States might choose to adopt similar practices.

The Biden administration decided to publish a nonbinding white paper, potentially recognizing the difficulty of shepherding legislation through any potential 118th Congress. Indeed, the document’s first page proclaims that it “is non-binding and does not constitute U.S. government policy.” Nor does it “constitute binding guidance for the public or federal agencies and therefore does not require compliance with the principles described herein.” Notwithstanding this disclaimer, the blueprint provides a clear indication of the Biden administration’s AI regulatory policy goals.

The Executive Branch and also independent agencies are likely to follow this lead in their respective domains.

Issues of Definition

In the debate over the European Union’s pending Artificial Intelligence Act, the definition of “artificial intelligence” has attracted much discussion. OSTP sidesteps this issue in the blueprint by addressing “automated systems,” which are defined as “any system, software or process that uses computation as whole or part of a system to determine outcomes, make or aid decisions, inform policy implementation, collect data or observations, or otherwise interact with individuals and/or communities.” OSTP adds, “Automated systems include, but are not limited to, systems derived from machine learning, statistics or other data processing or AI techniques, and exclude passive computing infrastructure,” which OSTP also defines.

The blueprint’s coverage of “automated systems” instead of “artificial intelligence” offers business a mixed bag. On the one hand, the broader scope aligns with the regulation of automated decision-making under California, Colorado,10 Connecticut, and Virginia12 privacy laws and New York City’s law on automated employment decision tools, all taking effect this year, as well as Article 2214 of the EU/UK General Data Protection Regulation.

On the other hand, it potentially threatens international harmonization of regulations based on the seemingly narrower scopes of the UNESCO Recommendation on the Ethics of Artificial Intelligence and the OECD AI Principles (also shared by the G20). Much of the blueprint concerns protection of “rights, opportunities or access.” OSTP explains this phrase as “the set of: civil rights, civil liberties and privacy, including”:

• “freedom of speech, voting, and protections from discrimination, excessive punishment, unlawful surveillance, and violations of privacy and other freedoms in both public and private sector contexts”;

• “equal opportunities, including equitable access to education, housing, credit, employment, and other programs”; or

• “access to critical resources or services, such as healthcare, financial services, safety, social services, non-deceptive information about goods and services, and government benefits.”

This explanation’s expansiveness underscores the Biden administration’s stated intent that the blueprint apply to automated systems affecting any facet of society or the economy.

Guiding Principles

The blueprint outlines five principles for all automated systems with the potential to “meaningfully impact individuals’ or communities’ exercise of rights, opportunities or access”:
• Safe and Effective Systems. Automated systems should be safe and effective. They should be evaluated independently and monitored regularly to identify and mitigate risks to safety and effectiveness. Results of evaluations, including how potential harms are being mitigated, should be “made public whenever possible.”
• Algorithmic Discrimination Protections. Automated systems should not “contribute to unjustified different treatment” or impacts that disfavor members of protected classes. Designers, developers, and deployers should include proactive equity assessments in their design processes, use representative data sets, watch for proxies for protected characteristics, ensure accessibility for people with disabilities, and test for and mitigate disparities throughout the system’s life cycle.
• Data Privacy. Individuals should be protected from abusive data practices and have control over their data. Privacy engineering should be used to ensure automated systems include privacy by default. Automated systems’ design, development, and use should respect individuals’ expectations about their data and the principle of data minimization, collecting only data strictly necessary for the specific context. OSTP stresses that consent should be used only where it can be appropriately and meaningfully provided, limited to specific use contexts and unconstrained by dark patterns; moreover, notice and requests for consent should be brief and understandable in plain language. Certain sensitive data (including data related to work, home, education, health, and finance) should be subject to additional privacy protection, including ethical review and use prohibitions.
• Notice and Explanation. Operators of automated systems should inform people affected by their outputs when, how, and why the system affected them. This principle applies even “when the automated system is not the sole input determining the outcome.” Notices and explanations should be clear and timely and use plain language.
• Human Alternatives, Consideration, and Fallback. People should be able to opt out of decision-making by automated systems in favor of a human alternative, where appropriate. Automated decisions should be appealable to humans.

The blueprint also includes a “Technical Companion” that details “concrete steps” for building these five principles into “policy, practice or the technological design process.” Organizations developing, procuring, and deploying AI and other automated systems will find these concrete steps to be generally consistent with other guidance on best practices.

What Next from the U.S. Government?

Having drawn up the blueprint, the Biden administration is ready to build out its AI policies through guidance, rulemaking, and enforcement. This work is already under way.
Thus far, guidance—both for ethical best practices and compliance with existing laws—has been most common. For instance:
• Department of Energy AI Advancement Council. In May 2022, the Department of Energy established the AI Advancement Council20 to oversee coordination, advise on AI strategy, and address issues on the ethical use and development of AI systems.
• Algorithmic Discrimination in Hiring. In May 2022, the Equal Employment Opportunity Commission (EEOC) and the Department of Justice released a technical assistance document that explains how employers’ use of algorithmic decision-making may violate the Americans with Disabilities Act. EEOC’s guidance is a part of its larger initiative to ensure that AI and “other emerging tools used in hiring and other employment decisions comply with federal civilbrights laws that the agency enforces.”
• Consumer Protection. In May 2021, the Federal Trade Commission’s (FTC) published a blog post providing tips for responsible use of AI in compliance with Section 5 of the Federal Trade Commission Act, the Fair Credit Reporting Act, and the Equal Credit Opportunity Act.

Increasingly, however, the Executive Branch and independent agencies have been shifting to rulemaking and enforcement:
• Broad AI Regulation. In August 2022, FTC opened its “commercial surveillance” proceeding, which could lead to a wide range of rules on AI and other automated systems (as well as privacy and data security). FTC’s Advance Notice of Proposed Rulemaking asks a number of questions about algorithmic accuracy, validity, reliability, and error; algorithmic discrimination against traditionally protected classes and “other underserved groups”; and whether AI and other automated systems yield unfair methods of competition or unfair or deceptive acts or practices that violate Section 5 of the FTC Act.25
• Workplace Protections. The Department of Labor is ramping up enforcement of required surveillance reporting to protect worker organizing. The Department of Labor also released a blog post titled “What the Blueprint for an AI Bill of Rights Means for Workers.”
• Algorithmic Healthcare Discrimination. The Department of Health and Human Services (HHS) issued a proposed rule in August 2022 that, in relevant part, would prohibit algorithmic discrimination in clinical decision-making by covered health program and activities. HHS also planned to release an evidence-based examination of healthcare algorithms and racial and ethnic disparities by late e 2022.
• Algorithmic Housing Discrimination. In June 2022, Meta (formerly, Facebook) settled a Justice Department Fair Housing Act suit (following a Department of Housing and Urban Development investigation). The government alleged that Meta had used algorithms in determining which Facebook users received housing ads and that those algorithms relied, in part, on characteristics protected under the Fair Housing Act. As part of the settlement, Meta agreed to change its targeted advertising practices and to pay the maximum civil penalty of $115,054.
• Algorithmic Credit Discrimination. In March 2022, the Interagency Task Force on Property Appraisal and Valuation Equity released an Action Plan to Advance Property Appraisal and Valuation Equity that includes a commitment from regulators to include a nondiscrimination standard in proposed rules for automated valuation models. Also that month, the Consumer Financial Protection Bureau revised its Supervision and Examination Manual to focus on algorithmic discrimination as a prohibited unfair, deceptive or abusive acts or practice. Businesses should expect the blueprint to inform all such agency actions going forward. It is likely that these agencies will expand their AI initiatives while other agencies will become active addressing AI and other automated systems within their ambits.

The Chamber of Commerce’s Concerns Following the blueprint’s release, the U.S. Chamber of Commerce (the Chamber) wrote34 OSTP Director Dr. Arati Prabhakar,
highlighting a number of concerns:
• Lack of Stakeholder Engagement. OSTP received insufficient stakeholder input in formulating the blueprint, having sought comments only on biometric-identification systems.
• Poor Definitions. The blueprint supplies definitions of key terms, including “Automated System,” which lack precision and could undercut international harmonization of AI policies and standards.
• Independent Evaluations. The current lack of “concrete” auditing standards and metrics for AI systems makes it “pointless” to allow journalists, third-party auditors, and other independent evaluators “unfiltered access” to AI systems—as called for in the blueprint.
• Conflation of Data Privacy and Artificial Intelligence. Data privacy and AI raise “distinctly different” “nuances and complexities,” so the two issues should not be conflated.

The Chamber’s “unexpectedly forceful pushback” (to quote Politico’s Brendan Bordelon) to a supposedly nonbinding guidance document reflects the blueprint’s potential influence. In an interview, a representative said the Chamber expects dozens of federal agencies to incorporate the guidance into regulatory mandates and
fears “copycats at the state and local level.” A patchwork of differing requirements could impose a substantial burden on businesses.

Having released the Blueprint for an AI Bill of Rights with great fanfare, the Biden administration is unlikely to withdraw it in response to the Chamber’s critique. However, the critique probably does foreshadow coming battles in rulemaking dockets and legislative chambers around the country.

Conclusion

AI regulation is arriving swiftly. Businesses should monitor these changes and prepare their compliance programs. Companies with particular concerns may wish to raise them early in legislative and rulemaking processes while proposals remain fluid.

June 22, 2023
Big Tech’s Race to Develop Superior Artificial Intelligence Technology

Big Tech’s Race to Develop Superior Artificial Intelligence Technology

Will A.I. Compromise Free Enterprise, Disclosure and Security?

“Robots Typing” generated by ChatGPT

America’s Big Five tech companies – Amazon, Apple, Facebook, Google and Microsoft – are racing to develop technology they claim will change the world — again. The tech Goliaths have more than 33,000 researchers at their disposal to create artificial intelligence (A.I.) technology with an obvious and perpetual prize: revenue.

It’s the talk of the world. NBC Nightly News recently predicted the impacts that A.I. will have on society in the coming years. A.I. tech was also the center of attention at the 2023 Davos Economic Summit. Prominent tech leaders such as Elon Musk and the CEO of OpenAI, Sam Altman, heralded that A.I. will improve virtually everyone’s lives, but with some risks involved.

Andrew Perlman, dean of Suffolk University Law School, says there is nothing “future” about it. In The Implications of ChatGPT for Legal Services and Society, he wrote, “The disruptions from AI’s rapid development are no longer in the distant future. They have arrived …” And for the legal industry, he said, “ChatGPT may portend an even more momentous shift than the advent of the internet.”

Just one legal application out there today is the use of A.I. technology (GPT-3) by Docket Alarm, a popular court docket search service. Docket Alarm allows users to see A.I.-generated summaries of filings without even opening them. Michael Sander, VP of analytics with Docket Alarm owner Fastcase, told legal technology enthusiast Bob Ambrogi that the feature is experimental and should be relied upon with some healthy caution. [Disclosure: HB collaborates with Fastcase in creating litigation content, e.g., the Journal of Emerging Issues in Litigation and the Emerging Litigation Podcast.]

As non-attorney and comic book hero Spiderman famously said, “With great power comes great responsibility.” But will the tech companies (or their algorithms) take responsibility for the rush of legal issues certain to continue from an unregulated A.I. Wild West? Critics say this automated technology has already damaged democratic discourse. A.I.-generated content is easily observed on Twitter and other platforms — flooding the digital town square of public opinion.

An unregulated A.I. race creates myriad legal issues that our lawmakers and our Constitution seem ill-equipped to address — at least quickly. Legal issues to which A.I. will, critics fear, play a role include degradation of free speech and public discourse, increased monopolization, greater economic inequality, and the mass proliferation of copyright infringement.

Damage to Discourse and Democracy

FDR photo courtesy of the Library of Congress

Technology and democracy have historically gone hand in hand, from typesetters allowing printers to produce newspapers and magazines, to famous radio fireside chats with President Roosevelt. A healthy democracy relies on input from its citizens as well as unhindered First Amendment rights for the citizens who utilize technologies to disseminate messages, so long as they do not promote violence or undermine security.

Since 2015, A.I. has increasingly influenced the democratic process in both the United States and abroad. Chatbots — an A.I. technology designed to automate text via algorithms to respond to people’s messages. Bots have been used to repost, repopulate, and generate social media posts on Twitter and other social media sites. Misinformation abounds.

A popular bot is ChatGPT developed by OpenAI, which we used to augment this article. [Editor’s Note: See the photo at the top and writing examples in the sidebar. The rest was drafted by a human being. Or so he claims.]

In a November 2022 op-ed published in Scientific American by A.I. expert Gary Marcus, OpenAI’s ChatGPT was deemed to “sound authoritative, even when it’s wrong, which makes it a perfect tool for mass-producing misinformation.” A Stanford University analytical research paper co-sponsored by the school’s sociology and psychology departments explains that messages generated by ChatGPT are just as capable of persuading readers as human writers are.

A.I. has also been developed to write text for news stories. Blogger Jacob Bergdahl experimented in July 2021 with OpenAI’s GPT-3 bot to generate comical fake news stories about how President Biden’s favorite food was pizza with ice cream on top, how Sweden’s prime minister rode a pig, and the European Union’s investment in onion farms. (Again, those are made up!) Bergdahl said, “I don’t know about you, but I’m equal parts impressed and terrified at how convincingly the algorithm explained these ridiculous topics. To reiterate: I only entered the first sentence of each story, and I didn’t edit the AI’s output in the slightest.”

A.I. has recently been employed to manipulate images, generating a startlingly realistic image of Donald Trump being dramatically arrested in front of a Manhattan federal courthouse in March. Belgian-based journalist Eliot Higgins believes he has since been banned from the image generating platform, Midjourney. The image was on Bellingcat, Higgins’ investigative journalism site. He shared it on Twitter where it went viral; it was shared by millions social media users.

Critics say the challenges to democracy are exacerbated by the Big Five’s hold on the technology.

Monopolization and Free Enterprise Limitations

Text-based A.I. tools are already widely used by mid-sized companies to large corporations, particularly in the form of chatbots. Tech companies like Outreach.io promotes chatbot services to streamline customer service, reduce costs, and reduce labor needs. However many executives are, “proceeding with caution given the limitations of ChatGPT” according to a Wall Street Journal article published this January. Chatbots through ChatGPT and eventually through more advanced A.I. language systems may even convince most customers into believing they are interacting with human beings. The WSJ further reports that, “[w]hile many chatbots are trained to deliver a version of “I don’t know” to requests they cannot compute, ChatGPT, for example, is more likely to spout off a response with complete confidence—even if the information is wrong.”

“[G]enerative A.I. risks turbocharging fraud. It may not be ready to replace professional writers, but it can already do a vastly better job of crafting a seemingly authentic message than your average con artist — equipping scammers to generate content quickly and cheaply. — FTC Chair Lina Khan, May 3, 2023, New York Times

Data security company Cyberhaven recently performed an audit of its employees using OpenAI’s ChatGPT to determine if sensitive company data was being passed on to the chatbot service. Their audit revealed as much as 11% of the content pasted into ChatGPT contained sensitive company data. Cyberhaven, which offers data security software to a variety of companies, observed that a growing number of their clients had employees utilizing ChatGPT. “Despite some companies blocking ChatGPT, its use in the workplace is growing rapidly,” wrote Cyberhaven’s Cameron Coles.

A.I. developers have also implemented their own chatbots or partnered with A.I. companies to optimize online search engines with the technologies. Google uses an A.I. tool called Bard. Microsoft, through its search engine Bing, recently implemented ChatGPT. A report by Public Citizen explains that an “A.I.-generated answer means the search engine becomes less a tool for finding unique and original sources of information and more a tool for synthesizing those original sources into a secondary source.” Microsoft started incorporating ads into its Bing search chatbot which means it will likely drive more online traffic away from an original information source and channel the traffic more to the answer provided by the A.I. service.

Publishers have also sounded the alarm about chatbots and A.I.-generated search engines. Publishers rely on users finding their content through search engines and worry that A.I. tools will drive traffic away from their sites. A.I. search engine results also further threaten small to mid-sized businesses and their economic prospects. OpenAI states on its website that it is developing plug-ins that will allow its latest model of ChatGPT to perform automated actions online for customers such as booking flights, ordering groceries, and shopping.

As the report by Public Citizen notes, “A.I. tools as intermediaries is another way tech corporations can insert themselves into supply chains and charge commissions that raise prices for consumers, while siphoning money away from small and local businesses.”

A.I. potentially sets up large businesses for claims of monopolization and unfair business practices, some forecast.

“While the technology is moving swiftly, we already can see several risks. The expanding adoption of A.I. risks further locking in the market dominance of large incumbent technology firms. A handful of powerful businesses control the necessary raw materials that start-ups and other companies rely on to develop and deploy A.I. tools. This includes cloud services and computing power, as well as vast stores of data.” — FTC Chair Lina Khan, May 3, 2023, New York Times

What is more, this technology has been widely predicted to cause greater economic inequality than exists today.

Economic Inequality

The Big Five and their whopping 33,000 doctoral A.I. researchers clearly indicate their intentions – to generate more corporate wealth. According to a March 27, 2023 article written by the Washington Post, nearly 70% of A.I. Ph.Ds. opt to work for the corporate sector whereas, 20 years ago, that number was roughly 20%. This metric indicates that the vast majority of A.I. tools and technology being developed are not for academia or truly life-improving purposes, but for corporations to render them more machine-like and more easily generate and manipulate money.

OpenAI CEO Sam Altman wrote a manifesto in 2021 predicting that the widespread deployment of A.I. would lead to most people being worse off than they are today. Altman painted an ominous picture of the world to come, decrying how “in the next five years, computer programs that can think will read legal documents and give medical advice. In the next decade, they will do assembly-line work and maybe even become companions. And in the decades after that, they will do practically everything, including making new scientific discoveries that will expand our concept of everything.”

Altman also argued that A.I. will “create phenomenal wealth,” and “if we get this right…can improve the standard of living for people more than we ever have before.” OpenAI conducted their own research into this topic in 2023 and published a paper indicating that approximately 80% of the U.S. workforce could have least 10% of their tasks affected by the introduction of GPTs (generative pre-trained transformers), while roughly 19% of the workforce could have as much as 50% of their tasks automated. The extent of unregulated image, text, and even voice manipulation by GPTs has the potential to create many copyright issues, especially for professional artists, musicians, and actors.

Copyright Infringement

Public Citizen reported that artists and writers have had the content they produced and published online used without their consent to train A.I. tools to produce derivative art. Cartoonist Sarah Anderson’s artwork was turned into neo-Nazi memes by far-right political activists. Voice actors have similarly been impacted by non-consensual use of their voices with the use of A.I. tech.

Vice News reported on Feb. 7, 2023, that voice actors were increasingly subjected to contracts containing language that gives away their rights to use of their A.I.-generated voices. (Demonstrating the high-wire act that online media is, Vice itself is reportedly headed to bankruptcy.)

Tim Friedlander, President and founder of the National Association of Voice Actors said clauses “are very prevalent right now” that sign rights to an actor’s voice over to publishers. “[M]any voice actors may have signed a contract without realizing language like this had been added. We are also finding clauses in contracts for non-synthetic voice jobs that give away the rights to use an actor’s voice for synthetic voice training or creation without any additional compensation or approval. Some actors are being told they cannot be hired without agreeing to these clauses.” Actor Emma Watson’s voice was recently used without her consent for a reading of Mein Kamph, according to Vice News.

U.K.-based Getty Images has launched a lawsuit in federal court in Delaware against Stability A.I., alleging that the company copied 12 million images without permission to train its A.I. tools. Stability A.I. has responded to the complaint, arguing that their use of the images falls under the Fair Use Act 17 U.S.C. § 107 and does not constitute copyright infringement. Legal analysts believe that Getty Images has a stronger case than an individual artist would have given the blatant use of millions of its images.

Proposed Public Solutions

Media attention surrounding A.I. tools and technology is accelerating. The Biden Administration acknowledged that policymaking was woefully lagging in mitigating potential harms stemming from the widespread deployment of A.I. In response, the Biden Administration published a “Blueprint for an A.I. Bill of Rights” in October 2022.

This blueprint is intended to serve as a broad guide for the federal government’s deployment of A.I. and model of best practices for society at-large.

There are five principles outlined in the guidance document:

1) Americans should be protected from unsafe or ineffective systems.

2) Americans should not face discrimination by algorithms.

3) Americans should be protected from abusive data practices and have agency over how data about them is used.

4) Americans should know when, how and why automated systems are being used to make decisions that affect them.

5) Americans should have the choice to opt out of automated customer service and have access to a person who can help troubleshoot problems.

Critics of the blueprint argue that while the White House did seek input from the Big Five’s lobbyists, the guide “is essentially a white paper with no enforcement authority against Big Tech.” Some in the corporate world have already contested that, saying ,“even [the] unenforceable guidelines could stifle innovation.”

U.S. Representative Ted Lieu (D-Calif.), who has a background in computer science, is advocating for the creation of a federal agency dedicated to regulating A.I. technologies. Lieu argues that Congress needs to implement the creation of this new agency to “ensure that the development and deployment of A.I. is done in a way that is safe, ethical, and respects the rights and privacy of all Americans, and that the benefits of A.I. are widely distributed and the risks are minimized.”

As the Big Five and other contributing A.I. companies continue their race to develop the newest and best A.I. technologies, people worldwide remain at risk for potential nonconsensual data collection, unwarranted marketing solicitation, and nonconsensual use of personal information, pictures, published text, and videos. This report highlights but a portion of the foreseeable legal issues arising in the unregulated Wild West of A.I. technology.

[Editor’s Note: Would it be petty to point out that in the photo of Robots Typing some appear not to have heads? But, then, maybe their brains and eyeballs are located elsewhere. 😊 ]

Tom Hagy edited and contributed to this article.

By Hunter SchmitzGuest Writer

Hunter Schmitz is a freelance legal writer and paralegal with Focus on Property Law and Civil Litigation.

How A.I. Can Benefit Society

By ChatGPT

Artificial intelligence has the potential to benefit society in a multitude of ways. One of the most significant areas of impact is in automation, where AI can perform repetitive and tedious tasks more efficiently and accurately than humans. This can lead to cost savings and increased productivity, freeing up people’s time to focus on more creative and strategic endeavors. Additionally, AI can help in areas such as healthcare by improving diagnostics and developing personalized treatment plans. It can also be used in education to provide personalized learning experiences and in environmental conservation to monitor and protect wildlife and natural resources. AI can also assist in disaster response and relief efforts by analyzing data and predicting outcomes. Overall, artificial intelligence has the potential to improve many aspects of society, from healthcare to education to the environment, and beyond.

Can ChatGPT Really Pass the Bar?

By ChatGPT

As an AI language model, I do not have the ability to pass a bar exam or attend law school in the traditional sense. While I have been trained on a vast amount of legal information, including case law, statutes, and legal principles, I am not a licensed attorney and cannot provide legal advice or representation. However, I can assist in answering legal questions and providing information about legal topics. It is important to note that relying solely on information provided by an AI language model is not a substitute for seeking the advice of a licensed attorney.

What is This Article About?

By ChatGPT

The article discusses the race among America’s Big Five tech companies – Amazon, Apple, Facebook, Google, and Microsoft – to develop artificial intelligence (AI) technology that they claim will change the world. The author raises concerns about the legal issues that may arise from an unregulated AI race, including degradation of free speech and public discourse, increased monopolization, greater economic inequality, and copyright infringement. The article also discusses how AI has already influenced the democratic process by being used to spread misinformation and generate fake news stories. The article further argues that the almost exclusive development of AI technology by the Big Five could lead to monopolization and limitations on free enterprise.

May 11, 2023
AI Image Generators and Copyright: Eligibility in the U.S., UK, EU, and More; Fair Use, Derivative Works, Liability
AI Image Generators and Copyright:

Eligibility in the U.S., UK, EU, and More; Fair Use, Derivative Works, Liability

Photo by Hitesh Choudhary on Unsplash

AI programs are now readily available for all. Stability AI, Lensa, and other AI image creation tools create original works of art, raising the question of IP protection for such art. The United States requires human authorship in order to obtain copyright protection, and so far, the U.S. Copyright Office has declined to grant copyright registrations for AI-created works of art based on a lack of human authorship (one of these decisions is being challenged in Thaler v. Perlmutter (D.D.C. filed June 2, 2022)). While some countries take a similar approach to the US, others treat the issue of copyright eligibility for AI-generated art quite differently and provide at least some protection of computer generated works.

Questions have also been raised as to whether AI-generated images constitute derivative works and whether such images and the AI generation tools used to create them infringe third-party copyrights, or whether the fair use doctrine or other defenses may apply. The first lawsuits involving image generators have now been filed raising copyright claims in addition to other claims.

Listen as our authoritative panel of IP attorneys examines AI image generators and the associated copyright issues. The panel will discuss eligibility in the U.S. and the recent actions by the Copyright Office and contrast this with the approaches used in other countries. The panel will also address the recent cases that have been filed and the potential liability for copyright infringement in the U.S. and other countries.

Speakers

Michael R. Graif
Member
Mintz Levin Cohn Ferris Glovsky and Popeo

Lisa T. Oratz
Senior Counsel
Perkins Coie

Scott J. Sholder
Partner
Cowan DeBaets Abrahams & Sheppard

CLE On-Demand Webinar

This Strafford production has been specially selected for HB audiences.

Topics
- What hurdles confront counsel when demonstrating authorship of AI-generated works?
- How does copyright apply to AI-generated works? How does it differ across jurisdictions?
- What steps can counsel take to increase the likelihood of success when seeking copyright protection for AI-generated works?
Outline
1. AI-generated works of art and copyrightability
  1. Eligibility in the U.S.
  2. Eligibility in other countries
2. AI image generators and copyright infringement
  1. Derivative works
  2. Fair use and other defenses
  3. Liability in other jurisdictions
  4. Best practices
April 6, 2023
Discovery Strategies in Wage and Hour Class and Collective Actions Before and After Certification of Putative Class
Discovery Strategies in Wage and Hour Class and Collective Actions Before and After Certification of Putative Class

Strategically Limiting Discovery, Resolving Discovery Disputes

Wage and hour class and collective actions are complex and discovery intensive. Discovery requests are often burdensome, seeking information concerning a broad swath of workers. This causes the discovery process to sometimes linger for years and creates a significant expense for employers.In recent years, courts have emphasized that parties must rein in extensive and expensive discovery requests. Employment litigators are increasingly raising proportionality arguments as a basis for objecting to opposing counsel’s discovery requests.

Drafters are responding by tailoring requests to anticipate such challenges. Drafting discovery requests that are likely to withstand burden and proportionality challenges and objections to broad discovery requests is critical for litigators representing employers in wage and hour class and collective actions. Employment litigators must develop and implement effective discovery strategies both before and, as applicable, after certification of the putative class. These strategies often must anticipate the possibility of a future summary judgment motion, further certification practice, and trial on the merits.

Listen as our authoritative panel of employment law attorneys explains effective strategies for pursuing or objecting to discovery requests in wage and hour collective and class actions and resolving discovery disputes that arise during litigation.

Questions Addressed:
- What are the most common discovery challenges counsel face when litigating wage and hour collective and class actions–from initiation through resolution of the case?
- What strategies have been effective in wage and hour collective and class actions for obtaining essential information with the least expense?
- What is the scope of discoverable evidence before and after certification of the putative class, and how can you limit or best manage discovery?
- When drafting discovery requests in wage and hour class and collective actions, what should employment counsel consider to ensure that the requests align with the proportionality standard?
Interested in More CLE OnDemand? Click Here.

Interested in this program? Click here to send us a note.

On Demand CLE Webinar

Interested in this program? Click here to send us a note.

Speakers

Gerald Maatman Jr.
Partner
Duane Morris
GMaatman@duanemorris.com

Noel P. Tripp
Principal
Jackson Lewis
Noel.Tripp@jacksonlewis.com

Outline
1. Pursuing or objecting to discovery requests in wage and hour collective and class actions
  1. Before conditional collective or class certification
  2. After conditional certification of a collective action
  3. After class certification
2. Discovery considerations for summary judgment
3. Discovery considerations for trial
4. Resolving discovery disputes
Explore more from Duane Morris LLP!

Journal (JEIL) Artificial Intelligence Litigation Risks in the Employment Discrimination Context. By Gerald Maatman Jr., Alex Karasik, and George Schaller

CLE OnDemand Webinar: AI Nuts & Bolts Survival Guide: Artificial Intelligence – Discrimination in Employment Context. Gerald Maatman Jr., Alex Karasik, and George Schaller

CLE OnDemand Webinar: Discovery Strategies in Wage and Hour Class and Collective Actions Before and After Certification of Putative Class. Gerald Maatman Jr., Noel P. Tripp

CLE OnDemand Webinar: Rule 23(c)(4) Issue Certification: Reconciling the Conflict With the Predominance Requirement. Gerald Maatman Jr., Timothy Congrove, Jennifer Mesko and James Muehlberger
February 15, 2023
Data-Driven Legal Guidance with Ed Walters

Today we’re going to talk about the weather. But only for a minute. Mostly we’re going to talk about the use of big data in the practice of law.

There is a reason IBM acquired the digital assets of The Weather Channel, and it’s not because they are climate nerds. They bought it to put weather data to work to “operationalize [the] understanding of the impact of weather on business outcomes.” Think about the economic impact of snowstorms, hurricanes, and even less dramatic weather conditions, or the impact on the durability of manufacturing or building materials as temperatures rise or fall outside the norm.

While we all crave meteorological precision, we also crave precision when making legal and business decisions.

Clients ask questions like these all the time: What is our case worth? What size award will we get? Where should I file? Will the judge grant summary judgment? Should I even bring this suit? Lawyers will draw on experience to offer their best advice, providing ranges followed by caveats and usually preceded by the most lawyerly of lawyer answers: “It depends.” As my guest points out, lawyers also get business-related questions. Business-related answers may begin with “it depends,” but must end with a number. When a CEO asks how much revenue your project will generate, “more” is not the answer they’re looking for. I know. I’ve tried.

Lawyers who seek greater precision in their predictions can take comfort in the increasing sophistication of analytical tools that can evaluate massive troves of data and account for myriad variables. Not only are we seeing advances in machine learning, artificial intelligence, and language processing, but there is greater access to important litigation-related data – BIG DATA – than ever before. Using new technologies to comb through millions of records – combined with an attorney’s insights – cannot only sharpen their predictive capabilities, but it can help them build, defend, and resolve cases.

For insights on the past, present and future of legal guidance and analysis, listen to my interview with Ed Walters, co-founder and CEO of our partners on this podcast, Fastcase, the legal research and software company whose divisions include Fastcase Full Court Press (publishing), Law Street Media (legal news), Docket Alarm (docket tools), and NextChapter (software). An entrepreneur, writer and professor, Ed brings his experience advising global Fortune 500 tech and pharma companies and sports leagues, serving in the White House on media affairs and speechwriting, and contributing to several major newspapers and journals. Ed is an adjunct law professor at Georgetown and Cornell universities. He is also a self-described “weather nerd,” which explains my tortured introduction.

This podcast is the audio companion to the Journal on Emerging Issues in Litigation. The Journal is a collaborative project between HB Litigation Conferences and the Fastcase legal research family, which includes Full Court Press, Law Street Media, and Docket Alarm. The podcast itself is a joint effort between HB and our friends at Law Street Media. If you have comments or wish to participate in one our projects please drop me a note at Editor@LitigationConferences.com.

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Tom Hagy
Litigation Enthusiast and
Host of the Emerging Litigation Podcast
Home Page
LinkedIn

Data-Driven Legal Guidance

Ed WaltersFastcase

Ed Walters is the CEO and co-founder of Fastcase, an online legal research software company based in Washington, D.C. Under Professor Walters’s leadership, Fastcase has grown to one of the world’s largest legal publishers, serving more than 1.1 million subscribers from around the world.

Before founding Fastcase, Professor Walters worked at Covington & Burling, in Washington D.C. and Brussels, where he advised Microsoft, Merck, SmithKline, the Business Software Alliance, the National Football League, and the National Hockey League. His practice focused on corporate advisory work for software companies and sports leagues, and intellectual property litigation.

November 26, 2022
Robojudges: If Machines Could Make Judicial Decisions, Should They?
The Author

Joshua P. DavisProfessor & Practicing Attorney

A leading academic and practitioner, Joshua P. Davis (davisj@usfca.edu) is a nationally recognized expert on legal ethics and class actions, as well as on artificial intelligence in the law, antitrust, civil procedure, free speech, and jurisprudence. He has published more than 30 scholarly articles and book chapters on these subjects and is currently writing a book on AI titled Unnatural Law, which will be published by Cambridge University Press. He is Research Professor of Law at the University of California Hastings College of Law, and a Shareholder of the Berger Montague PC law firm and Manager of its new San Francisco Bay Area Office. Before taking these posts, for more than 20 years Davis was a tenured Professor of Law at University of San Francisco Law School, where he also served as the Director of the Center for Law and Ethics.

Davis is also a member of the Editorial Board of Advisors for the Journal on Emerging Issues in Litigation, published by Fastcase Full Court Press. Tom Hagy, Editor in Chief.

You can also listen to Josh on the Emerging Litigation Podcast!

Robojudges: If Machines Could Make Judicial Decisions, Should They?

By Joshua P. Davis

Abstract: As artificial intelligence makes its way into every aspect of our daily lives—including the practice of law—humans have some decisions to make. Do we wish for AI to replace human judges? What are the risks and how might they be mitigated? What breakthroughs need to occur? How might robotic judges, or “robojudges,” perform better than human jurists? What surprises might be in store? Read on for the author’s perspectives on these important questions. After all, as he points out, AI is already being used by the judiciary, albeit to a limited extent.

Some of the most exciting, vexing, and terrifying issues at the intersection of artificial intelligence (AI) and law involve robojudges. Can we build a robojudiciary that replaces human judiciaries? Should we? These are no small questions given such a shift would massively disrupt how our legal systems operate and transform democratic self-government.

Part of the challenge in thinking about robojudges is technical. There are all sorts of practical technological advances that would be necessary to build an effective robojudge. We are not there yet and we likely won’t be for a while. Some of the steps would likely require increasing the power of computers, designing programs for natural language, and possibly mastering quantum computing.

More general and accessible, however, are a series of conceptual issues. We might frame them as questions.
1. What breakthroughs are necessary for AI to think the way we do?
2. Will AI be able to simulate human instrumental reasoning; that is, reasoning about how best to achieve prescribed objectives?
3. Will AI be able to simulate human purposive reasoning; that is, reasoning about which objectives to pursue?
4. What role does consciousness play in answering these questions?
5. Could we program AI to have conscious experiences similar enough to ours for it to make reliable instrumental and purposive judgments?
6. Do human judges engage in instrumental or purposive reasoning?
Answering these questions can serve a few major purposes.

First, it can help us deal with the present and immediate future. Reliance on AI in judging may soon be commonplace. To some extent, it already occurs. AI has become a judicial tool in setting bail and deciding which children should be removed from their families to protect their well-being.

Second, the answers can help us prepare for far greater disruptions in the future. We should think carefully now about the outer limits of AI, lest we are caught off guard and allow changes that we regret and cannot undo. In times of great and rapid change, foresight is necessary to steer societies toward improvements and away from pitfalls.

Third, AI offers a grand experiment that may tell us a great deal about ourselves. It may shed light on how our brains and minds work, how the two relate, how the law works, and what role consciousness plays in it all. With these purposes in mind, below is an analysis that offers some preliminary and admittedly speculative answers to the above questions.

See what else the author has to say about robojudges and get the complete article.

Get the article now!
March 3, 2022
The Rise of Robojudges with Josh Davis

The Rise of Robojudges with Joshua Davis

The good news for all of us, not the least of which are the robe and wig industries, is that we still have time. Artificial intelligence is advancing rapidly, but it’s still not able to think like a learned jurist. We can say it will have flaws, but so do our human deciders. So it will be a tradeoff, right? What are the risks? What are the upsides? Will robojudges be able to absorb infinitely more information quickly? Will they hand down decisions free from the influence of bias? Wouldn’t it be great to eliminate conflicts of interest?

Joining me to discuss this not-so-out-there concept is Joshua P. Davis, a nationally recognized expert on legal ethics, class actions, and artificial intelligence in the law. He is Research Professor of Law at the University of California Hastings College of Law, and Shareholder and Manager of Berger & Montague, P.C.’s new San Francisco Bay Area Office. For more than 20 years Josh was a tenured Professor of Law at the University of San Francisco Law School, where he also served as the Director of the Center for Law and Ethics. Josh is authoring two books, one titled Unnatural Law, dealing with AI and the law, and a second on the important issue of class action ethics.

Finally, remind me never to assume anything when I ask Josh a question. I said something like, “Surely we’re not talking about sci-fi robots here,” to which he basically said, “Not so fast.” This happened more than once. When will I learn?

This podcast is the audio companion to the Journal on Emerging Issues in Litigation, a collaborative project between HB Litigation Conferences and the Fastcase legal research family, which includes Full Court Press, Law Street Media, Docket Alarm and, most recently, Judicata. If you have comments or wish to participate in one our projects, or want to tell me how insightful and forward-thinking Josh is, please drop me a note at Editor@LitigationConferences.com.

Tom Hagy
Host of the Emerging Litigation Podcast

According to an article written by our guest, “Some of the most exciting, vexing, and terrifying issues at the intersection of AI and law involve robojudges.”

Can we build a robojudiciary that replaces human judiciaries? Should we? Doing so would massively disrupt how our legal systems operate. It also might transform democratic self-government.” I have to ask: Would any of that be so bad? It’s not like humans are doing such a bang-up job. The risk, of course, is what if we get it all wrong?

via GIPHY

December 15, 2021
Putting an AI App to Work to Protect IP with Jan-Diederik Lindemans and Judith Bussé

Putting an AI App to Work to Protect IP with Jan-Diederik Lindemans and Judith Bussé

They are Crowell & Moring partner Jan-Diederik Lindemans and Judith Bussé, both part of the firm’s Technology & Intellectual Property Department in Brussels. And, working with Neotalogic, they developed an interactive app that takes you through a set of attorney-crafted questions that, depending on your answers, take you to other questions. The app applies a layer of artificial intelligence to enhance the information gathering process. Listen to what these innovators had to say about the Crowell & Moring IP Check-Up application, and take it for a test drive yourself. Or, here is a quick video of someone using the app.

This podcast is the audio companion to the Journal on Emerging Issues in Litigation*, a collaborative project between HB Litigation Conferences and the legal news folks at Law Street Media, and the Fastcase legal research family, which includes Docket Alarm and Judicata. If you have comments or wish to participate in one our projects, or want to tell me how insightful our guests are, please drop me a note at Editor@LitigationConferences.com.

Tom Hagy
Host of the Emerging Litigation Podcast

* Highly regarded insurance and reinsurance industry attorney Laura Foggan of Crowell & Moring’s Washington, DC, office is on the Editorial Advisory Board. Thanks to Laura for connecting me with J.D. and Judith.

An organization’s intellectual property is often its most valuable asset.

Whether it’s a patent or a trademark, a graphic design or proprietary market information, or just the unique way they do what they do, organizations must protect their innovations or risk significant damage to their future prospects.

Assessing the vulnerabilities of such valuable inventory is as important as it is time-consuming. But a portfolio protection and process review involves answering the same long set of questions posed to any organization, no matter what type.

There is the problem. You have a critical invention. You don’t know if it’s at risk. What do you do? You contact a lawyer, of course. You go through the process, one they have managed many times before. What if you could do this yourself first, before contacting a firm? What if it took just 20 minutes and could be done from the comfort of your desk? If you’re the attorney, what if you already had many of your questions answered before your first meeting with a new client?

An innovative pair of attorneys in Brussels asked these questions and came up with a solution. And I had the pleasure of interviewing them.

November 1, 2021