I find questions like this quite amusing.
Can an AI chatbot be convicted of an illegal wiretap? A case against Gap’s Old Navy may answer that
NBC reports:
Can an AI be convicted of illegal wiretapping?
That’s a question currently playing out in court for Gap’s Old Navy brand, which is facing a lawsuit alleging that its chatbot participates in illegal wiretapping by logging, recording and storing conversations. The suit, filed in the Central District of California, alleges that the chatbot “convincingly impersonates an actual human that encourages consumers to share their personal information.”
In the filing, the plaintiff says he communicated with what he believed to be a human Old Navy customer service representative and was unaware that the chatbot was recording and storing the “entire conversation,” including keystrokes, mouse clicks and other data about how users navigate the site. The suit also alleges that Old Navy unlawfully shares consumer data with third parties without informing consumers or seeking consent.
Old Navy, through its parent company Gap, declined to comment.
A model for retire-but-still-work-full-time?
https://apnews.com/article/kiss-digital-avatars-end-of-road-finale-37a8ae9905099343c7b41654b2344d0c
Kiss say farewell to live touring, become first US band to go virtual and become digital avatars
On Saturday night, Kiss closed out the final performance of their “The End of the Road” farewell tour at New York City’s famed Madison Square Garden.
But as dedicated fans surely know — they were never going to call it quits. Not really.
During their encore, the band’s current lineup — founders Paul Stanley and Gene Simmons as well as guitarist Tommy Thayer and drummer Eric Singer — left the stage to reveal digital avatars of themselves. After the transformation, the virtual Kiss launched into a performance of “God Gave Rock and Roll to You.”
They ain’t human but they is intellectual?
https://engagedscholarship.csuohio.edu/clevstlrev/vol72/iss1/12/
That Thing Ain't Human: The Artificiality of "Human Authorship" and the Intelligence in Expanding Copyright Authorship to Fully-Autonomous AI
The U.S. Copyright Review Board (the "Board") decided that works entirely created by fully-autonomous artificial intelligence ("AI") are not entitled to copyright protections. The Board based its decision on a copyrightability requirement referred to as “human authorship.” However, the Copyright Act of 1976 (the "Act") never mentions a “human” requirement to copyright authorship, nor do most of the Board’s cited authorities. Denying authorship to intellectually-impressive and economically-valuable works under a poorly-established legal subelement is antithetical to copyright law’s history and to Congress’s constitutional mandate to “promote . . . [the] useful [a]rts . . . .” It leaves creators who use AI to create works with no protections for their creations. But this Note argues that, when properly interpreting various copyright-law authorities that allegedly establish a “human authorship” requirement, copyright law does not require “human authorship,” but “intellectual labor.” Under this standard, AI-produced works are entitled to copyright protections.
Perspective.
https://www.frontiersin.org/articles/10.3389/frbhe.2023.1338608/full
The Ethics and Behavioral Economics of Human-AI Interactions: Navigating the New Normal
Although some patterns already documented for interactions with previous generations of technologies are likely to extend to the current wave of AI, some of its features warrant specific examination. In particular, the ability of AI systems to continuously learn from new data and experiences means that they can evolve over time and even in real time, offering contextually relevant interactions and providing information that are tailored to the individual user's needs. On the one hand, this changes the performance expectations of the user, but on the other hand, it makes the outcomes less predictable, and the process more opaque, than in the interaction with older generations of automated agents. In essence, the special quality of AI lies in its mimicry of human learning processes and its adaptability to the user. This feature opens a space for strategic interactions on the both sides: Human users may adjust their behavior to generate desirable outcomes, for example, to affect individualized pricing; AI agents might adjust their behavior to increase engagement, for instance, by offering the information that the user is more likely to like, thus potentially fostering and amplifying biases, creating echo chambers, and spreading disinformation. These peculiarities raised questions and concerns not for a distant future; they are immediate and pressing as AI technologies become more capable and widespread. How, for example, is cooperation achieved when humans interact with "artificial agents"? What is different or similar as compared to human-human interactions? Do people display similar or different behavioral tendencies and biases (other regarding preferences, time preferences, risk attitudes, (over)confidence, etc.) when interacting with artificial agents as compared to humans? What are people's attitudes toward the use of intelligent machines for certain tasks or functions? What moral concerns does this raise? What are the reasons for any potential opposition to the reliance on AI-operated machines for certain tasks? Behavioral economics offers a lens to understand the nuanced ways in which interacting with AI affects human behavior. The papers in this special issue highlight the breadth of questions to be addressed: from the role of human personality traits for the hybrid interactions, to reliance on technology, intergroup dynamics and immoral behavior. The findings from these studies as well as from many ongoing research efforts remind us that this interaction is not a simple case of mechanical replacement but a fundamental transformation of the decision landscape. AI's influence on human behavior is intricate and often counterintuitive. The presence of AI alters the context in which decisions are made, the information that is available, and the strategies that are employed. Various foundational methods in behavioral economics, such as laboratory and field experiments, have been employed to provide causal evidence on the topic. These methods effectively abstract from and control for potential confounding factors that might be challenging or unfeasible to isolate using observational data. In addition, new tools -such as field-in-the-lab experiments with a learning factory -allows investigating real-world interactions in a controlled environment. Taking stock of existing evidence and theoretical contributions, moreover, conceptual analyses can offer unique insights from a number of the regularities documented in previous studies. The interaction with AI is dynamic and evolving due to the rapid pace of technological change. Although the exact sizes of the estimated effects might be context-specific and may change from one generation of a technology to another, we can and should study underlying behavioral regularities that are persistent and shape the general framework of the interaction with technology. The overarching narrative is clear: the rise of AI is not just a technological or economic phenomenon, but a behavioral one. The research presented here is united by a common goal: to navigate the ethical and economic implications of our deepening relationship with AI. The insights gleaned from these and many other studies to come can help pave the way for a future where AI and human behavior co-evolve in a manner that is beneficial and, above all, humancentric.
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