Artificial Intelligence/Robots – Page 7

"Introducing the LC Labs Artificial Intelligence Planning Framework"

To account for these [AI] challenges and realities, LC Labs has been developing a planning framework to support the responsible exploration and potential adoption of AI at the Library. At a high level, the framework includes three planning phases: 1) Understand 2) Experiment and 3) Implement, each supports the evaluation of three elements of ML: 1) Data; 2) Models; and 3) People. We’ve developed a set of worksheets, questionnaires, and workshops to engage stakeholders and staff and identify priorities for future AI enhancements and services. The mechanisms, tools, collaborations, and artifacts together form the AI Planning Framework. Our hope in sharing the framework and associated tools in this initial version is to encourage others to try it out and to solicit additional feedback. We will continue updating and refining the framework as we learn more about the elements and phases of ML planning.

https://tinyurl.com/4wuakvjy

"Approaching Artificial Intelligence and Open Research in Sync: Opportunities and Challenges"

AI can generate more complete and disambiguated metadata to enhance discovery and move search from the traditional keyword-based model to semantic and conversation-based searches.

AI can also help publishers improve accessibility, to make content available to a broader audience.

AI as a reader and consumer will become as important a consideration as the human reader and consumer. Publications should consider machines as consumer and provide machine readable and consumable formats.

AI can create personalized recommendations and news feeds, simultaneously helping researchers find the answers they need and allowing publishers to target specific audiences for specific publications.

Even better, AI can perform reverse engineering to measure the contribution of each source to the final answers. And publishers can charge based on the contribution. This could be new business model in the future. Many AI researchers are currently working on enabling explainable and transparent AI, but this research will take time.

https://tinyurl.com/uu4dhs9y

"Judge Will Toss Part of Authors’ AI Copyright Lawsuit "

According to Reuters, judge Vince Chhabria said the authors’ allegations that text generated by Llama infringes their copyrights simply doesn’t stand up to scrutiny. "When I make a query of Llama, I’m not asking for a copy of Sarah Silverman’s book—I’m not even asking for an excerpt," Chhabria observed, noting that, under the authors’ theory, a side-by-side comparison of text generated by the AI application and Silverman’s book would have to show they are similar.

However, the judge said he will not dismiss the case with prejudice, meaning the authors will be allowed to amend and refile their claims.

https://tinyurl.com/sd4wbba4

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"Google SGE [Search Generative Experience]: A New Way to Search, Teach, and Resist"

Google SGE removes many of the barriers that make us doubt our search abilities. We already know that users rarely look past the first page of results or scroll past the fold of a webpage, but with SGE you get exactly what you think is "good enough." However, the more I searched the more disappointed I was that Google continued to serve up the same kinds of sources you usually find at the top of the algorithm, such as Wikipedia pages, blog posts, news, and popular media. The only disclaimer that SGE gives is "Info quality may vary."

https://tinyurl.com/4tntbsbh

"How Well Does ChatGPT Handle Reference Inquiries? An Analysis Based on Question Types and Question Complexities"

To explore whether artificial intelligence can be used to enhance library services, this study used ChatGPT to answer reference questions. . . Overall ChatGPT’s performance was fair, but it did poorly in information accuracy. It scored the highest when handling facilities and equipment-related questions but the lowest when dealing with e-resources access problems. ChatGPT was weak in answering advanced research questions, complex inquiries, and known item searches relating to a specific local environment, but it could be adopted to enhance library communication with users.

https://tinyurl.com/3dabv5f8

Paywall: Generative AI and Librarians — "The Prompt Engineering Librarian"

In terms of training the public in prompt engineering skills, no single discipline or profession currently takes the lead, presenting an opportunity for professions like librarianship to step into this role. Librarians are already well-equipped to educate the public in a wide range of literacy skills and tasks, so prompt engineering may be a natural progression. The purpose of this paper is to examine the potential role of prompt engineering for library professionals.

https://doi.org/10.1108/LHTN-10-2023-0189

Also see: "Prompt Engineers or Librarians? An Exploration."

"Developing Responsible AI practices at the Smithsonian Institution"

Applications of artificial intelligence (AI) and machine learning (ML) have become pervasive in our everyday lives. These applications range from the mundane (asking ChatGPT to write a thank you note) to high-end science (predicting future weather patterns in the face of climate change), but, because they rely on human-generated or mediated data, they also have the potential to perpetuate systemic oppression and racism. For museums and other cultural heritage institutions, there is great interest in automating the kinds of applications at which AI and ML can excel, for example, tasks in computer vision including image segmentation, object recognition (labelling or identifying objects in an image) and natural language processing (e.g. named-entity recognition, topic modelling, generation of word and sentence embeddings) in order to make digital collections and archives discoverable, searchable and appropriately tagged.

A coalition of staff, Fellows and interns working in digital spaces at the Smithsonian Institution, who are either engaged with research using AI or ML tools or working closely with digital data in other ways, came together to discuss the promise and potential perils of applying AI and ML at scale and this work results from those conversations. Here, we present the process that has led to the development of an AI Values Statement and an implementation plan, including the release of datasets with accompanying documentation to enable these data to be used with improved context and reproducibility (dataset cards). We plan to continue releasing dataset cards and for AI and ML applications, model cards, in order to enable informed usage of Smithsonian data and research products.

https://doi.org/10.3897/rio.9.e113334

"NEH Announces New Research Initiative: Humanities Perspectives on Artificial Intelligence"

NEH’s Humanities Perspectives on Artificial Intelligence initiative will support numerous AI-related humanities projects through the following funding opportunities:

Universities or independent research organizations considering establishing a research center that focuses on humanistic AI research should consider NEH’s newest grant program, Humanities Research Centers on Artificial Intelligence. This funding opportunity offers up to $750,000 to support the creation of humanities research centers focusing on the ethical, legal, or societal implications of artificial intelligence.

Individual scholars or scholarly teams based at an institution (e.g., colleges and universities) may consider Dangers and Opportunities of Technology: Perspectives from the Humanities. Independent scholars or those affiliated with an institution may apply to Fellowships, Awards for Faculty at HBCUs, HSIs, and TCUs, Summer Stipends, or Public Scholars.

Collaborative teams interested in planning for an international AI research project or hosting a scholarly convening about AI should consider Collaborative Research.

Institutions interested in hosting professional development programs on the latest research related to humanistic AI should consider Institutes for Advanced Topics in the Digital Humanities.

https://tinyurl.com/c5sb7x26

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"UC Berkeley Library to Copyright Office: Protect Fair Uses in AI Training for Research and Education"

If the Copyright Office were to enable rightsholders to opt-out of training AI for research and teaching fair uses, then academic institutions and scholars would face even greater hurdles in licensing content for research purposes. It would be operationally difficult for academic publishers and content aggregators to amass and license the "leftover" body of copyrighted works that remain eligible for AI training. Costs associated with publishers’ efforts in compiling "AI-training-eligible" content would be passed along as additional fees charged to academic libraries, who are already financially constrained to preserve TDM and other fair uses for scholars. In addition, rightsholders might opt out of allowing their work to be used for AI training fair uses, and then turn around and charge AI usage fees to scholars (or libraries)—essentially licensing back fair uses for research. These scenarios would impede scholarship by or for research teams who lack grant or institutional funds to cover these additional expenses; penalize research in or about underfunded disciplines or geographical regions; and result in bias as to the topics and regions studied.

https://tinyurl.com/5cd2vc85

"Springer Nature and Authors Successfully Use Generative AI to Publish Academic Book"

As part of an innovative experiment, Springer Nature has become the first publisher to create a whole new academic book by empowering authors to use GPT as part of the integrated workflow. Developed during a —Hack Day— in the Spring which brought together authors, editors and experts from across Springer Nature, the German-language book Einsatzmöglichkeiten von GPT in Finance, Compliance und Audit (Applications of GPT in finance, compliance and audit) has now been published. It took less than five months from inception to publication — about half the time normally taken. . . .

The process was as follows:

Working simultaneously on six screens, the team defined commands which GPT then executed chapter by chapter to create the first version of the manuscript

At each stage of the process, the content generated by the Large Language Model (LLM) was reviewed by the authors, who then asked the machine to adapt the text

This "prompt ping pong" ensured that the knowledge expertise of the authors renowned in their field was combined with the language expertise of the LLM

After the Hack Day, the authors and Springer Nature’s editorial team further checked, corrected and supplemented the text

The team then linked the relevant data sources to ensure proper attribution

https://tinyurl.com/4x7nvvks

"Springer Nature Introduces Curie, Its AI-powered Scientific Writing Assistant"

Springer Nature today announced a new AI-powered in-house writing assistant to support researchers, particularly those whose first language is not English, in their scientific writing. . . .

It has been specifically trained on academic literature, spanning 447+ areas of study, more than 2,000 field-specific topics and on over 1 million edits on papers published including those in leading Nature journals. It combines the power of large language models (LLMs) with specialised AI digital editing developed in-house and designed specifically for scientific writing. Unlike generalist AI writing apps, Curie focuses on the unique pain points of researchers in their professional writing, including translation to English and English language editing to address grammatical errors and improve phrasing and word choice.

https://tinyurl.com/msvc28ra

Paywall: "Implementing a Rules-Based Chatbot for Reference Service at a Large University Library"

While some chatbots or virtual assistants generate automatic and custom responses to user input, this paper explores the implementation of a rules-based chatbot, where all responses have been input and configured by library staff. Details are provided to describe the process before, during, and after the initial implementation with data and observations from the pilot in mid-2023.

https://doi.org/10.1080/19322909.2023.2268832

"How ChatGPT and Other AI tools Could Disrupt Scientific Publishing"

In the age of LLMs, [Michael] Eisen pictures a future in which findings are published in an interactive, "paper on demand" format rather than as a static, one-size-fits-all product. In this model, users could use a generative AI tool to ask queries about the experiments, data and analyses, which would allow them to drill into the aspects of a study that are most relevant to them. It would also allow users to access a description of the results that is tailored to their needs. "I think it’s only a matter of time before we stop using single narratives as the interface between people and the results of scientific studies," says Eisen.

https://doi.org/10.1038/d41586-023-03144-w

"How ChatGPT and Other AI Tools Could Disrupt Scientific Publishing"

More broadly, generative AI tools have the potential to change how research is published and disseminated, says Patrick Mineault, a senior machine-learning scientist at Mila — Quebec AI Institute in Montreal, Canada. That could mean that research will be published in a way that can be easily read by machines rather than humans. "There will be all these new forms of publication," says Mineault.

https://doi.org/10.1038/d41586-023-03144-w

"A Comprehensive Survey of ChatGPT: Advancements, Applications, Prospects, and Challenges"

This survey offers an overview of ChatGPT, delving into its inception, evolution, and key technology. We summarize the fundamental principles that underpin ChatGPT, encompassing its introduction in conjunction with GPT and LLMs. We also highlight the specific characteristics of GPT models with details of their impressive language understanding and generation capabilities. We then summarize applications of ChatGPT in a few representative domains. In parallel to the many advantages that ChatGPT can provide, we discuss the limitations and challenges along with potential mitigation strategies. Despite various controversial arguments and ethical concerns, ChatGPT has drawn significant attention from research industries and academia in a very short period. The survey concludes with an envision of promising avenues for future research in the field of ChatGPT.

https://doi.org/10.1016/j.metrad.2023.100022

60 Minutes: "’Godfather of Artificial Intelligence’ Geoffrey Hinton on the Promise, Risks of Advanced AI"

Scott Pelley: You think these AI systems are better at learning than the human mind.

Geoffrey Hinton: I think they may be, yes. And at present, they’re quite a lot smaller. So even the biggest chatbots only have about a trillion connections in them. The human brain has about 100 trillion. And yet, in the trillion connections in a chatbot, it knows far more than you do in your hundred trillion connections, which suggests it’s got a much better way of getting knowledge into those connections.

https://tinyurl.com/4a7bmn5p

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"Toward Non-human-Centered Design: Designing an Academic Article with ChatGPT"

Non-human-centered design tools, such as ChatGPT, have shown potential as effective aids in academic article design. This study conducts a comparative evaluation of ChatGPT-3.5 and ChatGPT-4, examining their capabilities and limitations in supporting the academic article design process. The study aims to demonstrate the utility of ChatGPT as a writing tool and investigate its applicability and efficacy in the context of academic paper design. The author interacted with both versions of ChatGPT, providing prompts and analyzing the generated responses. In addition, a different expert academic was consulted to assess the appropriateness of the ChatGPT responses. The findings suggest that ChatGPT, despite its limitations, could serve as a useful tool for academic writing, particularly in the design of academic articles. Despite the limitations of both GPT-3.5 and GPT-4, GPT-3.5 offers a broader perspective, whereas GPT-4 provides a more in-depth and detailed approach to the design of articles. ChatGPT exhibits capabilities in aiding the design process, generating ideas aligned with the overall purpose and focus of the paper, producing consistent and contextually relevant responses to various natural language inputs, partially assisting in literature reviews, supporting paper design in terms of both content and format, and providing reasonable editing and proofreading for articles. However, limitations were identified, including reduced critical thinking, potential for plagiarism, risk of misinformation, lack of originality and innovation, and limited access to literature.

https://doi.org/10.3145/epi.2023.sep.12

"Introducing the Journal of the Medical Library Association’s Policy on the Use of Generative Artificial Intelligence in Submissions"

With the arrival of ChatGPT, the academic community has expressed concerns about how generative artificial intelligence will be used by students and researchers alike. After consulting policies from other journals and discussing among the editorial team, we have created a policy on the use of AI on submissions to JMLA. This editorial provides a brief background on these concerns and introduces our policy.

https://doi.org/10.5195/jmla.2023.1826

"Introducing Open Data Editor (beta): Towards a No-Code Data App for Everyone "

Intuitive Data Editing: Open Data Editor (beta) provides a user-friendly, spreadsheet-like interface that allows you to view, edit, and validate your data effortlessly.

Data Transformation: Easily transform your data from one format to another with a wide range of supported data formats, including CSV, Excel, JSON, and more.

Data Validation: Ensure data quality and consistency with built-in validation checks that generate a visual validation report, making it super easy for you to clean your data.

Schema Management: Define and manage data schemas to ensure data consistency and compliance with standards.

Data Publishing: Seamlessly publish your data to the web or data portals. It is easy to publish the processed data to CKAN, Github and Zenodo with a single button click, making it accessible to a wider audience and increasing its impact.

Generative AI: Optionally add a generative AI provider to unlock many features based on chat-based language models. The feature is currently limited to OpenAI, but more providers will be added soon.

https://tinyurl.com/2xwcp87x

"Where Does ChatGPT Fit into the Framework for Information Literacy? The Possibilities and Problems of AI in Library Instruction"

We have found that the idea of ChatGPT (and generative AI more broadly) can be connected to many of the knowledge practices and dispositions from the six frames of the ACRL Framework. In some places, the Framework enables us to embrace ChatGPT as an exciting new tool that adds value to information literacy instruction. In other places, the Framework’s discussions of evaluating authority and examining bias shines light on the inherent flaws of ChatGPT.

https://tinyurl.com/2shjyukb

"Western Appoints Mark Daley as First-Ever Chief AI Officer"

Mark Daley has been appointed Western University’s first-ever chief Artificial Intelligence (AI) officer, as Western becomes the first university in Canada to house such a role within its senior executive. Daley’s five-year term begins Oct. 15. . . .

Daley’s experience includes tenure as vice-president of research at the Canadian Institute for Advanced Research, a world-renowned institute supporting AI research and Canada’s AI strategy. The multidisciplinary scholar has held cross-appointments in several departments at Western, including computer science, mathematics, statistics and actuarial sciences, biology, electrical and computer engineering, and epidemiology and biostatistics.

He most recently served as Western’s first-ever chief digital officer leading Western Technology Services, and is excited to take on his new role, buoyed by Western’s "forward-thinking approach to AI."

https://bit.ly/3RIWziF

"Can ChatGPT Be an Author? A Study of Artificial Intelligence Authorship Policies in Top Academic Journals"

Academic publishers have quickly responded to the impact of artificial intelligence (AI) tools on authorship and academic integrity. However, there remains a lack of understanding about AI authorship policies and the attitude of academic journals towards these tools. This study aims to address this gap by examining the AI authorship policies of 300 top academic journals during the period of late-spring 2023. Over half of the journals examined have an AI authorship policy and guidelines for acknowledging AI usage in manuscript preparation. These acknowledgments are typically made in the methods or acknowledgement sections, although some journals have introduced a new, special section on AI usage. The study also found that AI authorship policies may differ depending on the publisher and discipline of the journal. Many publishers have adopted uniform AI authorship policies that are implemented across all journals that they publish.

https://doi.org/10.1002/leap.1582

"A Critical Examination of the Ethics of AI-Mediated Peer Review"

Recent advancements in artificial intelligence (AI) systems, including large language models like ChatGPT, offer promise and peril for scholarly peer review. On the one hand, AI can enhance efficiency by addressing issues like long publication delays. On the other hand, it brings ethical and social concerns that could compromise the integrity of the peer review process and outcomes. However, human peer review systems are also fraught with related problems, such as biases, abuses, and a lack of transparency, which already diminish credibility. While there is increasing attention to the use of AI in peer review, discussions revolve mainly around plagiarism and authorship in academic journal publishing, ignoring the broader epistemic, social, cultural, and societal epistemic in which peer review is positioned. . . . The discussion here emphasizes the need to critically assess the legitimacy of AI-driven peer review, addressing the benefits and downsides relative to the broader epistemic, social, ethical, and regulatory factors that sculpt its implementation and impact.

https://arxiv.org/abs/2309.12356

"ChatGPT Users Can Now Browse Internet, OpenAI Says"

ChatGPT users will now be able to surf the web, Microsoft-backed (MSFT.O) OpenAI said on Wednesday, expanding the data the viral chatbot can access beyond its earlier September 2021 cutoff.

The artificial intelligence startup said its latest browsing feature would allow websites to control how ChatGPT can interact with them. . . .

The startup also announced a major update earlier this week that would enable ChatGPT to have voice conversations with users and interact with them using images, moving it closer to popular AI assistants like Apple’s (AAPL.O) Siri.

https://tinyurl.com/yckddzzm

Looking Towards a Brighter Future: The Potentiality of AI and Digital Transformations to Library Spaces

At the University of Leeds, we have developed an ambitious, bold vision for our libraries called Knowledge for all. Knowledge for all sets out the libraries’ direction for 2030, and digital transformation is critical in making our vision a reality. The Artificial Intelligence (AI) in Libraries Project forms the basis of this report and it is one of the steps the library is taking to achieve its bold vision. This vision is fully embraced by the University of Leeds as part of the university’s development strategy.

https://tinyurl.com/44v2c5w8