Addressing legal issues with the latest technological developments and social media trends.
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GettyImages-901599596-e1660252913509-300x269Though we recently touched on the U.S. Court of Appeals for the Federal Circuit ruling that only natural beings, which do not include artificial intelligence, can be an inventor under the U.S. Patents Act, the decision merits additional discussion.

Defining artificial intelligence (AI) can be a challenging task due to the expansiveness of its reach and evolving nature if its application. At its core, AI is the use of computer systems to perform tasks which historically have required human intelligence. Thus, AI can interpret and learn from data, creating alone, using what it has learned from this data, without additional human input. Such machine learning is further refined into deep learning, in which artificial neural networks—algorithms which copy how the human brain works—learn in a manner that mimics how humans do but by processing vast amounts of data. This neural networks approach of having computers “learn” as the human brain does differs from the more traditional rules-based computer programming, in which a computer is programmed with the explicit rules it will follow. Even as AI-powered computers begin to mimic human thinking, going beyond following predetermined tasks and routines, it’s not surprising that while AI is good at rules-based thinking, it cannot mimic certain functions of the human brain yet.

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AI technology dominates the news cycle with news of DeepMind’s groundbreaking discovery of almost all structures of known proteins, an ethical dilemma prompted by a chess-playing robot that broke its young opponent’s finger, the artistic possibilities that DALL-E’s text-to-picture art tool may deliver, and more.

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GettyImages-1129133524-300x291Even as artificial intelligence (AI) has become more commonplace and relied upon by businesses in different industries, it still faces criticism on whether it can be implemented in a safe and ethical manner and, related, how the bias often inherent in the underlying algorithms can be detected and reduced.

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Black box isolated on white backgroundArtificial intelligence has long since evolved from a technology with exciting potential to a near ubiquitous and integral component in the day-to-day conduct of many businesses. Take the automotive and aerospace industries—each is undergoing massive changes and movements toward more competitive, efficient and innovative uses of technology and AI in order to meet consumer demands, create more efficient factories, optimize supply chains, and achieve better performance in operations and production. Using modern software and AI has become essential across many companies.

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GettyImages-1185884207-300x213It’s no secret that every move you make on the internet can be tracked. Even when you are not actively searching, scrolling through a social media feed, or using your phone to navigate to a new local restaurant, your digital behavior can be tracked, analyzed, stored, marketed, and sold. But is that simply the price we now pay for convenience and connectedness? Maybe, but companies should at least tell you what they are doing with your valuable data.

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GettyImages-155602728-300x200Earlier this year, Ethereum co-founder Vitalik Buterin, in cooperation with economist Glen Meyl and researcher Puja Ohlhaver, published a research paper on soulbound tokens (SBTs). SBTs are publicly visible, non-transferrable (but possibly revocable by the issuer) digital assets representing “commitments, credentials, and affiliations.” Buterin et al. have said that such tokens would be like an “extended résumé” while others have said SBTs will enable protocols such as Ethereum to “encode social relationships of trust.” The ultimate use of SBTs would be to allow Ethereum to create a Decentralized Society (DeSoc), a concept that the authors define in their paper through the exploration of use cases and how those would enable a digital social ecosystem. At highest level, the DeSoc described in this paper is a bottom-up coordination between participants to build, participate and govern plural network goods. (An example of a plural network good is access to property that would otherwise be private.)

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GettyImages-1370659682-300x300The non-fungible token (NFT) market has grown dramatically over the past 24 months. NFTs first garnered widespread attention when the artist Beeple sold digital artwork at Christie’s in March 2021 for $69 million. According to the DappRadar Industry Report, spending on NFTs exceeded $25 billion in 2021, but the market has been significantly lower this year and according to the The Wall Street Journal, “flatlined” last month.

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CFPB-logo-e1655398162416-300x274As previously discussed, financial services regulators are increasingly focused on how businesses use artificial intelligence (AI) and machine learning (ML) in underwriting and pricing consumer finance products. Although algorithms provide opportunities for financial services companies to offer innovative products that expand access to credit, some regulators have expressed concern that the complexity of AI/ML technology, particularly so-called “black box” algorithms, may perpetuate disparate outcomes. Companies that use AI/ML in underwriting and pricing loans must therefore have a robust fair lending compliance program and be prepared to explain how their models work.

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