Artificial Intelligence/Robots – Page 14

Ethics of Artificial Intelligence: Case Studies and Options for Addressing Ethical Challenges

This open access collection of AI ethics case studies is the first book to present real-life case studies combined with commentaries and strategies for overcoming ethical challenges. Case studies are one of the best ways to learn about ethical dilemmas and to achieve insights into various complexities and stakeholder perspectives.

https://cutt.ly/z1zj5Oy

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"When AI Can Make Art—What Does It Mean for Creativity?"

While internet users have embraced this supercharged creative potential—armed with the correctly refined prompt, even novices can now create arresting digital canvases—some artists have balked at the new technology’s capacity for mimicry. Among the prompts entered into image generators Stable Diffusion and Midjourney, many tag an artist’s name in order to ensure a more aesthetically pleasing style for the resulting image. Something as mundane as a bowl of oranges can become eye-catching if rendered in the style of, say, Picasso. Because the AI has been trained on billions of images, some of which are copyrighted works by living artists, it can generally create a pretty faithful approximation.

https://cutt.ly/iMv27Pn

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Microsoft, GitHub, and OpenAI Sued: "The Lawsuit That Could Rewrite the Rules of AI Copyright"

Microsoft, its subsidiary GitHub, and its business partner OpenAI have been targeted in a proposed class action lawsuit alleging that the companies’ creation of AI-powered coding assistant GitHub Copilot relies on "software piracy on an unprecedented scale". . . .Copilot, which was unveiled by Microsoft-owned GitHub in June 2021, is trained on public repositories of code scraped from the web, many of which are published with licenses that require anyone reusing the code to credit its creators. Copilot has been found to regurgitate long sections of licensed code without providing credit—prompting this lawsuit that accuses the companies of violating copyright law on a massive scale.

https://cutt.ly/FMwC4mR

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"An AI Toolkit for Libraries"

Now that artificial intelligence (AI) tools are being widely used across academic publishing, how can we make informed assessments of these utilities? There is a need for a set of skills for evaluating new tools and measuring existing ones, which should enable anyone commissioning or managing AI utilities to understand what questions to ask, what parameters to measure and possible pitfalls to avoid when introducing a new utility. The skills required are not technical. Potential problems include bias in the corpus, a poor training set or poor use of metrics for evaluation. This article gives a quick overview of some of areas where AI tools are being used and how they work. It then provides a checklist for assessment. The goal is not to discredit AI, but to make effective use of it.

http://doi.org/10.1629/uksg.592

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Paywall: "‘So How Do We Balance All of These Needs?’: How the Concept of AI Technology Impacts Digital Archival Expertise"

Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.

https://doi.org/10.1108/JD-08-2022-0170

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Google —Text Prompts Create Videos (with Live Examples): "Imagen Video: High Definition Video Generation Wwth Diffusion Models"

We present Imagen Video, a text-conditional video generation system based on a cascade of video diffusion models. Given a text prompt, Imagen Video generates high definition videos using a base video generation model and a sequence of interleaved spatial and temporal video super-resolution models. . . . We find Imagen Video not only capable of generating videos of high fidelity, but also having a high degree of controllability and world knowledge, including the ability to generate diverse videos and text animations in various artistic styles and with 3D object understanding.

https://cutt.ly/aBzo4R2

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Openly Licensed Photos and AI Facial Recognition White Paper: AI_Commons

"This white paper presents the case of using openly licensed photographs for AI facial recognition training datasets. . . . The case creates an opportunity to ask fundamental questions about the challenges that open licensing faces today, related to privacy, exploitation of the commons at massive scales of use, or dealing with unexpected and unintended uses of works that are openly licensed"

https://cutt.ly/pBuHEmH

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