It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Sunday, June 02, 2024
Marine Protected Areas don’t line up with core habitats of rare migratory fish, finds new research
62% of Marine Protected Areas (MPAs) designated to protect rare migratory fish species are outside of their core habitats, according to a new modelling study. The findings are published in the British Ecological Society’s Journal of Applied Ecology.
A team of researchers in France from the “Pole MIAME” that gathers diadromous fish experts from multiple research institutions (OFB, INRAE, Institut Agro and UPPA) have developed a new modelling approach that accurately predicts core and unsuitable habitats of rare and data-poor diadromous fish (fish which migrate between marine and freshwater), such as threatened shads and the IUCN red-listed ‘critically endangered’ European eel.
The researchers found that 62% of MPAs which are specifically meant to protect diadromous fish species, don’t overlap with the core habitats of the fish modelled in the study.
In fact, only 55% of the modelled core habitats of diadromous fish fell within any MPAs, and of these protected areas, only had half had specific measures to protect the species.
When looking at individual species, the researchers found that less than 30% of the endangered Mediterranean twaite shad (Alosa agone) core habitat was within MPAs.
Although other species such as European eel and European smelt had around 70% of their core habitats within MPAs, only 9% of these MPAs have specific measures to protect the European eel, and none had specific measures to protect European smelt.
Dr Sophie Elliott at the Game and Wildlife Conservation Trust (previously at Institute Agro in France) and lead author of the study, said “Given the sharp decline in diadromous fish which was noted just last week by The Living Planet Index (LPI) for migratory freshwater fishes 2024 update, it is a surprise more isn't being done to protect these species.
“We found that existing Marine Protected Areas with and without measures to protect listed diadromous fish across France, England, Belgium, and the Netherlands are not adequately protecting them despite a number of these fish being protected.”
Dr Anthony Acou, at the French Biodiversity Agency and Patrinat, in charge of diadromous fish evaluation for the EU MSFD (Marine Strategy Framework Directive), and a co-author of the study, added that “Due to a lack of data on rare species, spatial protective measures are often implemented with little understanding of the species distribution and habitat (‘the rare species paradox’).”
Dr Laurent Beaulaton, also at the French Biodiversity Agency, and a co-author said “We hope that our ‘Combined Model for Accurate Prediction’ methodological framework can help improve accurate rare species distribution modelling for reliable biodiversity assessments, meaning conservation measures can be targeted in specific areas that protect rare and poorly detected species while also minimising conservation impacts on human activity.”
The researchers tested their newly developed modelling approach on diadromous fish because very little is known about their at-sea life history stage and there is no existing model of their distribution.
These types of fish are also sensitive to anthropogenic pressures. Dr Sophie Elliott explained that “Diadromous fish species are particularly threatened because they are subject to terrestrial, freshwater, and marine pressures such as agricultural and pollutant runoffs, habitat destruction, barriers to migration, fishing, bycatch, and climate change. These barriers cumulate through their life cycle as they travel between their freshwater and marine habitats.”
To test the accuracy of their new modelling approach, the researchers collated an unprecedented amount of data on fisheries-dependent and independent data within eastern Atlantic and Mediterranean waters, focussing on 11 rare and data-poor diadromous fish including the European eel, European flounder, smelt and three species of shad and the thinlip mullet. They then compared the predicted core and unsuitable habitats for the fish against 89 OSPAR and habitat Directive MPAs found in these waters.
The researchers would now like to see their modelling approach expanded to larger areas across the Northeast Atlantic and look closer at habitat types. “The next step is to better characterise at-sea functional habitats (migratory corridor, nursery area, refuge area) of the different species. But for that additional data are needed…” added Dr Etienne Rivot, a population modelling expert at DECOD (Ecosystem Dynamics and Sustainability), L’Institut Agro, INRAE, Ifremer, and a co-author of the study.
The researchers also highlight that the modelling approach could be used for other protected, threatened and usually rare species, particularly for species where protected areas have been put in place for their conservation.
Accurately predicting rare and poorly detectable species habitat for spatial protection
ARTICLE PUBLICATION DATE
29-May-2024
Study finds environmental conditions influenced how early humans migrated across northern Eurasia and the Americas beyond Africa
FLINDERS UNIVERSITY
IMAGE:
THE INFOGRAPHIC SHOWS THE ROUTES MOST LIKELY FAVOURED BY THE FIRST HUMAN MIGRANTS ACROSS EURASIA AND THE AMERICAS. THESE ROUTES ARE ESTIMATED USING A STATISTICAL COMBINATION OF ARCHAEOLOGICAL AND GENETIC DATA. COLOURED AREAS INDICATE THE TYPE OF ECOSYSTEMS ENCOUNTERED, BASED ON CLIMATE AND VEGETATION MODELS. THE INSET IMAGE ILLUSTRATES THE IDEAL MIGRATION CONDITIONS: WARM AND HUMID AREAS CONTAINING A MIX OF FOREST AND GRASSLANDS NEAR RIVERS.
Study finds environmental conditions influenced how early humans migrated across northern Eurasia and the Americasbeyond Africa
Researchers have gleaned new insights into the great human migration, revealing how environmental conditions in northern Eurasia and the Americas shaped the journey of ancestors who left Africa tens of thousands of years ago.
The Out of Africa theory suggests that more than 70,000 years ago, some groups left Africa to spread across Europe, Asia, Australia, and the Americas. However, it remains unclear how much the environment they encountered beyond Africa facilitated or hindered their journey.
Researchers combined climate models, genetic data, and archaeological evidence to examine how regional environmental conditions influenced migration and to re-establish our long-lasting connection to nature.
The multidisciplinary analysis, led by Flinders University ecologist Dr Frédérik Saltré and recently published in Nature Communications, demonstrates that while the relative importance of environmental factors varies across regions, our ancestors travelled primarily through warm and humid areas containing a mix of forest and grasslands near rivers.
“The first human migrants favoured routes that provided essential resources and facilitated travel, as well as regions with a mix of forests and open areas for shelter and food, while allowing them to expand into new territories,” Dr Saltré, whose study was supported by the Australian Research Council Centre of Excellence for Australian Biodiversity and Heritage (CABAH), said.
In Europe, humans likely first spread from the Fertile Crescent through the Caucasus Mountains into Scandinavia approximately 48,300 years ago and Western Europe around 44,100 years ago, following warmer and wetter conditions.
In northern Asia, migration routes followed major rivers to cope with harsher climates before reaching Beringia, a currently submerged land bridge between Siberia and Alaska, approximately 34,700 years ago.
In North America, humans initially migrated along the Pacific coast around 16,000 years ago, and then approximately 3000 years later, moved inland through the ice-free corridor by the Mackenzie River.
In South America, migration followed wetter grasslands bordering the Amazon, leveraging connectivity provided by major rivers by 14,800 years ago.
Professor Tom Higham of the University of Vienna said the power of these new modelling approaches in understanding the deep human past is exciting for archaeological science.
“For too long we have been working rather separately in our different approaches. Incorporating new modelling methods with the latest climatic, archaeological, and environmental data allows really exciting insights into understanding how ancient humans moved and adapted across vast continents tens of thousands of years ago.”
Professor Corey Bradshaw, also from Flinders University and a Chief Investigator at CABAH, said modelling provides a powerful framework for exploring and understanding the complexities of deep history, offering insights into how past events and conditions have shaped the present.
“Knowing where people first trekked beyond the cradle of human evolution gives us a flavour of how adaptable our early ancestors were, what environmental challenges they faced, and how they overcame them and survived. We can also infer the technological innovations that were at play during those times—such as watercraft, clothing, and other tools—that allowed people to exploit the most hostile environments.”
Associate Professor Bastien Llamas from The University of Adelaide and a Deputy Director in CABAH said merging genetic data with historical climate information and archaeological discoveries is a powerful method for inferring past human migration patterns.
“Studying genetic differences between groups of people helps us understand ancient migration patterns. Typically, this results in a basic map showing general movements from one area to another without detailed routes. However, by combining genetic data with information about past climates, environments, and archaeological findings, we can create much more detailed and accurate maps of how people moved over time and across different regions.”
Dr Saltré said the study’s results help us appreciate the importance of biodiversity in how our ancestors adapted to and overcame environmental challenges.
“It underscores how climate and ecology shaped human prehistory, highlighting biodiversity's role in human survival and mobility, demonstrating that rich ecosystems enabled humans to thrive in new environments for thousands of years. The biodiversity crisis that we are experiencing now compromises our ability to thrive. Despite the advanced technology we have today, I genuinely wonder if we will last long without maintaining the bulk of current biodiversity.”
Environmental conditions associated with initial northern expansion of anatomically modern humans
WAIT, WHAT?!
The Jackson Laboratory creates mice that better reflect human genetic variation
The Jackson Laboratory and colleagues create new wild-derived mice that could make it easier to draw conclusions about the effectiveness of new treatments or pharmaceuticals on humans
JACKSON LABORATORY
IMAGE:
BETH DUMONT, AN EVOLUTIONARY BIOLOGIST AT THE JACKSON LABORATORY, RESEARCHES THE MECHANISMS THAT GENERATE GENETIC DIVERSITY THROUGH THE LENS OF EVOLUTION.
The great majority of how we understand human disease, and attempt to cure it, derives from mice genetically fashioned to be prolific breeders, docile and easy to handle – all qualities that have made it the favorite tool of large-scale biomedical research. However, this human-imposed selection of these behavioral and reproductive traits has come at a hefty cost: By weeding out undesirable traits in the highly standardized laboratory mouse, researchers have also placed unseen constraints on what is possible to know and learn from them.
Beth Dumont, an evolutionary biologist at The Jackson Laboratory, and colleagues are looking to remedy this situation. By collecting mice in their natural habitats, in fields, barns and forests, and in divergent ecological niches (polar, tropical, and arid climates) across North and South America, Dumont and colleagues have developed 10 new laboratory-grade research mouse strains with genomes packed with information that had been stamped out of classical mice.
These new mouse strains, detailed recently in PLoS Genetics, will provide an important new resource for researchers worldwide: Their genomes introduce millions of novel genetic variants compared to classical in-bred strains, including predicted versions of a gene that, on average, decreases the fitness of the organism carrying it, and gene-spanning structural variants, including loss of DNA, duplicated DNA, and detached chromosomes that reattach in the opposite direction – all genetic profiles that better reflect human genetic variation.
“Since the early 1900s, we’ve actively removed a lot of genetic information from laboratory mice that is incredibly relevant to human health,” said Dumont. “We’ve bred out traits that relate to anxiety, aggressiveness, and infertility, for instance, and that means we’re missing out on a wealth of potentially transformative biomedical research, making it much harder to determine how effectively new treatments or pharmaceuticals will work in humans.”
Dumont and her colleague, Professor Michael W. Nachman at the University of California, Berkeley and teams of graduate students went to work. They collected – with some difficulty – wild mice across five locations in Canada, the United States, and Brazil. These wild mice, which all belonged to a single mouse subspecies (M. musculus domesticus; important because they can all interbred, which is not necessarily the case with all genetically diverse mice) looked very different from laboratory mice, having experienced adaptive pressures to survive and thrive in their respective environments. For example, mice from Canada were bigger and had high metabolic activity to stay warm in a colder climate; mice from Brazil were smaller and their metabolism was radically different, indicating that mice collected in Brazil were uniquely adapted to a hot climate.
Dumont, Nachman and colleagues meticulously inbred these mice for 20 generations to eliminate deleterious genes while imposing very minimal selection for docile behavior and/or reproductive output. Dumont then re-derived these mice via IVF to prevent the introduction of wild pathogens, making them now suitable for laboratory use.
If you can catch them. That is, the new strains are also noticeably feistier.
“They’re fast, and they don’t want you to hold them,” said Dumont. “I haven’t been bitten, but working with them does require quick reflexes.”
The wild-derived laboratory strains showed variation in phenotypic traits beyond size and speed. The introduction of millions of genetic variants captured broad variations across many biological domains. Their biochemical, neurobehavioral, physiological, morphological, and metabolic traits differed much more broadly than those in inbred laboratory mice, more accurately modeling the complex genetic basis of human disease-related phenotypes.
“Tapping into wild strains has the potential to establish a powerful suite of resources for the modeling of human traits and diseases, enabling important discoveries across pretty much every disease area,” said Dumont. “As researchers start to recognize that, we’ll see increasing interest in wild-derived lab mice.”
Into the Wild: A novel wild-derived inbred strain resource expands the genomic and phenotypic diversity of laboratory mouse models
A.I.
Hiding in plain sight
Generative AI used to replace confidential information in images with similar visuals to protect image privacy
UNIVERSITY OF TOKYO
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THE SECTIONS OF THESE IMAGES OUTLINED WITH A RED BOX WERE ANNOTATED AS PRIVACY THREATENING WITH THE USE OF AN OPEN SOURCE DATASET CALLED DIPA. GCR THEN USED THE ANNOTATED TEXT PROMPTS TO REPLACE THE SECTIONS WITH VISUALLY SIMILAR OR WELL-INTEGRATED SUBSTITUTES.
CREDIT: 2024 A. XU, S. FANG, H. YANG ET AL./ ASSOCIATION FOR COMPUTING MACHINERY
Image privacy could be protected with the use of generative artificial intelligence. Researchers from Japan, China and Finland created a system which replaces parts of images that might threaten confidentiality with visually similar but AI-generated alternatives. Named “generative content replacement,” in tests, 60% of viewers couldn’t tell which images had been altered. The researchers intend for this system to provide a more visually cohesive option for image censoring, which helps to preserve the narrative of the image while protecting privacy. This research was presented at the Association for Computing Machinery’s CHI Conference on Human Factors in Computing Systems, held in Honolulu, Hawaii, in the U.S., in May 2024.
With just a few text prompts, generative AI can offer a quick fix for a tricky school essay, a new business strategy or endless meme fodder. The advent of generative AI into daily life has been swift, and the potential scale of its role and influence are still being grappled with. Fears over its impact on future job security, online safety and creative originality have led to strikes from Hollywood writers, court cases over faked photos and heated discussions about authenticity.
However, a team of researchers has proposed using a sometimes controversial feature of generative AI – its ability to manipulate images – as a way to solve privacy issues.
“We found that the existing image privacy protection techniques are not necessarily able to hide information while maintaining image aesthetics. Resulting images can sometimes appear unnatural or jarring. We considered this a demotivating factor for people who might otherwise consider applying privacy protection,” explained Associate Professor Koji Yatani from the Graduate School of Engineering at the University of Tokyo. “So, we decided to explore how we can achieve both — that is, robust privacy protection and image useability — at the same time by incorporating the latest generative AI technology.”
The researchers created a computer system which they named generative content replacement (GCR). This tool identifies what might constitute a privacy threat and automatically replaces it with a realistic but artificially created substitute. For example, personal information on a ticket stub could be replaced with illegible letters, or a private building exchanged for a fake building or other landscape features.
“There are a number of commonly used image protection methods, such as blurring, color filling or just removing the affected part of the image. Compared to these, our results show that generative content replacement can better maintain the story of the original images and higher visual harmony,” said Yatani. “We found that participants couldn’t detect GCR in 60% of images.”
For now, the GCR system requires a lot of computation resources, so it won’t be available on any personal devices just yet. The tested system was fully automatic, but the team has since developed a new interface to allow users to customize images, giving more control over the final outcome.
Although some may be concerned about the risks of this type of realistic image alteration, where the lines between original and altered imagery become more ambiguous, the team is positive about its advantages. “For public users, we believe that the greatest benefit of this research is providing a new option for image privacy protection,” said Yatani. “GCR offers a novel method for protecting against privacy threats, while maintaining visual coherence for storytelling purposes and enabling people to more safely share their content.”
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Paper Title
Anran Xu, Shitao Fang, Huan Yang, Simo Hosio, and Koji Yatani. 2024. Examining Human Perception of Generative Content Replacement in Image Privacy Protection. In CHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, 22 pages. 14 May 2024. https://dl.acm.org/doi/10.1145/3613904.3642103
This research is part of the results of Microsoft Research Asia CORE-D program as well as Value Exchange Engineering, a joint research project between R4D, Mercari Inc., and the RIISE.
Examples of popular methods for image content replacement and protection (outlined here by red boxes), and how they compare to GCR in the far-right column.
Can’t hand-le it.
CAPTION
As has been comically noted in many other AI-generated images shared online, for now GCR can also struggle to recreate realistic hands and facial features.
CREDIT
2024 A. Xu, S. Fang, H. Yang et al. / Association for Computing Machinery
About the University of Tokyo
The University of Tokyo is Japan’s leading university and one of the world’s top research universities. The vast research output of some 6,000 researchers is published in the world’s top journals across the arts and sciences. Our vibrant student body of around 15,000 undergraduate and 15,000 graduate students includes over 4,000 international students. Find out more at www.u-tokyo.ac.jp/en/ or follow us on X at @UTokyo_News_en.
Systemic issues can put women’s security at risk when artificial intelligence (AI) is adopted, and gender biases across widely used AI-systems pose a significant obstacle to the positive use of AI in the context of peace and security in South-East Asia.
Moreover, women human rights defenders (WHRDs) and women’s Civil Society Organisations (WCSOs) in the region are at high risk of experiencing cyber threats and, while largely aware of these risks, are not necessarily able to prepare for, or actively recover from, cyber-attacks.
These are among the key findings of groundbreaking research released today by UN Women and the United Nations University Institute in Macau (UNU Macau) examining the connections between AI, digital security and the women, peace and security (WPS) agenda in South-East Asia.
The research was made possible with support from the Government of Australia, under the Cyber and Critical Tech Cooperation Program (CCTCP) of the Department for Foreign Affairs and Trade (DFAT), and the Government of the Republic of Korea through the UN Women initiative, Women, Peace and Cybersecurity: Promoting Women, Peace and Security in the Digital World.
With AI projected to add USD 1 trillion to the gross domestic product of South-East Asian countries by 2030, understanding the impact of these technologies on the WPS agenda is critical to supporting these countries to regulate the technologies and mitigate their risks.
The report Artificial Intelligence and the Women, Peace and Security Agenda in South-East Asia, examines the opportunities and risks of AI from this unique perspective by focusing on four types of gender biases in AI – discrimination, stereotyping, exclusion, and insecurity – which need to be addressed before the region can fully benefit from new technological developments.
This research examines the relationship between AI and WPS according to three types of AI and its applications: AI for peace, neutral AI, and AI for conflict.
This report notes that across these categories, there are favourable and unfavourable effects of AI for gender-responsive peace and women’s agency in peace efforts.
While using AI for peace purposes can have multiple benefits, such as improving inclusivity and the effectiveness of conflict prevention and tracking evidence of human rights breaches, it is used unequally between genders, and pervasive gender biases render women less likely to benefit from the application of these technologies.
The report also highlights risks related to the use of these technologies for military purposes.
This research identifies two dimensions to improving the dynamics of AI and the WPS agenda in the region: mitigating the risks of AI systems to advancing the WPS agenda, especially on social media, but also on other tools, such as chatbots and mobile applications; and fostering the development of AI tools built explicitly to support gender-responsive peace in line with WPS commitments.
The second report, Cybersecurity Threats, Vulnerabilities and Resilience among Women Human Rights Defenders and Civil Society in South-East Asia, explores cybersecurity risks and vulnerabilities in this context with the goal of promoting cyber-resilience and the human and digital rights of women in all their diversity.
While there is increasing awareness of the risks women and girls face in cyberspace, there is little understanding of the impacts of gender on cybersecurity, or of the processes and practices used to protect digital systems and networks from cyber risks and their harms.
This work differs from previous research into cybersecurity as it focuses on human-centric as compared to techno-centric cybersecurity and emphasises human factors rather than technical skills as well as the centralisation of gender as critical to cybersecurity.
Furthermore, cyber threats are understood to be gendered in nature, whereby WCSOs and WHRDs are specifically targeted due to the focus of their work and are likely to be attacked with misogynistic and sexualised harassment.
The results highlight that digital technologies are central to the work of WCSOs and WHRDs, while simultaneously noting that WCSOs had higher threat perceptions and threat experiences compared to CSOs that do not work on gender and women’s rights, carrying disproportionate risks of disrupting their work, damaging their reputation, and even creating harm or injury, all of which contribute to marginalising women’s voices.
The largest differences of experienced threats between the groups were for online harassment, trolling (deliberately provoking others online to incite reactions) and doxxing (when private or identifying information is distributed about someone online without their permission).
This report’s recommendations include fostering inclusive and collaborative approaches in cybersecurity policy development and engagement, and building the knowledge of civil society, government, private-sector actors and other decision makers to develop appropriate means of prevention and response to cyberattacks and their disproportionate impacts on WCSOs and WHRDs.
Specific attention should be given to at-risk individuals and organizations, such as women’s groups operating in politically volatile and conflict and crisis-affected contexts and situations where civic space is shrinking.
UNU Macau and UN Women aim for this research, conducted over 12 months, to contribute to the global discourse on ethics and norms surrounding AI and digital governance at large.
Next, training materials based on the research findings and consultations with women’s rights advocates in the region will be rolled out, initially in Thailand and Vietnam, with e-learning modules and training handbooks to be publicly available in English, Thai and Vietnamese for interested stakeholders from mid-2024.
Download full reports and research summaries
- Artificial Intelligence and the Women, Peace and Security Agenda in South-East Asia [Full Report] [Research Summary]
- Cybersecurity Threats, Vulnerabilities and Resilience among Women Human Rights Defenders and Civil Society in South-East Asia [Full Report] [Research Summary]
USTC reveals how to effectively utilize large language models
UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA
Nowadays, Large Language Models (LLMs) are extensively applied in various situations from writing to solving complex problems. However, how to effectively interact with Artificial Intelligence and explore its potential remains to receive little attention.
Recently, Researcher LIN Zhicheng from Department of Psychology, University of Science and Technology of China (USTC) proposed practical strategies and guidelines to help us better understand and utilize LLMs. He emphasized that well-crafted prompts can enhance the accuracy and relevance of responses, preventing poor performance due to low-quality instructions. This commentary was published in Nature Human Behavior on 4th March.
Trained with deep learning, LLMs simulate neural network, with a distinctive feature of self-attention. LLMs are able to understand human language, thus being more user-friendly. Effective engagement with LLMs adds to the accuracy and relevance of the outputs, while reversely, poorly structured prompts can lead to inadequate answers. Though interacting with LLMs is seemingly simple, LIN pointed out that, designing effective prompts for LLMs is challenging.
The commentary highlighted the importance of "prompt engineering", a technique to optimize LLMs outputs through accurate input control. LIN proposed a series of strategies, including giving explicit instructions, adding relevant context, asking for multiple options and so on. These methods can help lead to ideal answers and reduce the compounding effect of errors.
This commentary serves as a practical guide for interactions with LLMs, helping users achieve ideal outcomes from LLMs and adding to our understanding on their potential. The strategies and opinions can provide valuable reference for the users who are expecting an enhanced efficiency in the interaction with LLMs.
How to write effective prompts for large language models
Korea and NYU establish global AI frontier lab
Brooklyn-based joint research will be led by prize-winning AI researchers Yann LeCun and Kyunghyun Cho
NEW YORK UNIVERSITY
Republic of Korea Minister of Science and ICT Lee Jong-ho and New York University President Linda G. Mills today announced the establishment of the Global AI Frontier Lab. The Lab—which will be based in NYU facilities in Brooklyn and draw top AI researchers from the U.S., Korea, and around the world—is the latest advance of thejoint research effort launched in 2023. The Institute of Information and Communication Technology Planning and Evaluation (IITP) President Hong Jin-bae and NYU signed a Memorandum of Agreement to establish the Global AI Frontier Lab and to outline its structure and operating guidelines.
The Global AI Frontier Lab will be led by two AI scholars from NYU’s esteemed Courant Institute of Mathematical Sciences and Center for Data Science: Yann LeCun, a Turing Prize-winning professor at NYU and Meta’s chief AI scientist, and Kyunghyun Cho, winner of the Samsung Ho-Am Award for Engineering, senior director of Frontier Research at Genentech, and a graduate of KAIST.
An open call for Korean researchers who wish to participate in the Global AI Frontier Lab and conduct world-class joint research with NYU was issued earlier this week by IITP in Korea (more details may be found on the IITP website). The Memorandum of Agreement will provide support for Korean researchers to participate in the joint research, as well as detail the structure of the research project and delineate priority-setting for specific joint research undertakings. The new lab is expected to be established in almost 13,000 sq. ft. of space in 1 MetroTech Center, adjacent to NYU’s Tandon School of Engineering and NYU’s 370 Jay Street technology and multimedia center.
Minister Lee Jong-ho said, “The Global AI Frontier Lab is the first step in a new international joint research paradigm and will serve as a stepping stone for Korea’s AI G3 leap and global solidarity and expansion,” adding, “We will provide policy support so that researchers can come together and actively contribute to AI innovation and sustainable AI development.”
NYU President Mills said, “These are important steps forward in ensuring the success of this joint research effort—an agreement on the Global AI Frontier Lab’s structure, world-class AI scholars in place as leadership, and a location in Downtown Brooklyn. Altogether, an outstanding combination. This project builds on NYU’s assets as an unrivaled global institution and on a foremost area of scholarly strength in science and technology for NYU. We and our Korean partners are very pleased with the development of this project; I am confident that this global partnership, steeped in scholarly excellence, will make a transformative contribution to the field of artificial intelligence.”
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Will generative AI change the way universities communicate?
A new study in JCOM monitors changes in university communication within the German landscape
SISSA MEDIALAB
Since the launch of ChatGPT 3 in November 2022, we've been abuzz with talk of artificial intelligence: is it an unprecedented opportunity, or will it rob everyone of jobs and creativity? As we debate on social media (and perhaps use ChatGPT almost daily), generative AIs have also entered the arena of university communication. These tools—based on “Large Language Models” that were optimized for interactive communication—can indeed support, expand, and innovate university communication offerings. Henke analyzed the situation of German realities about six months after the launch of ChatGPT 3: "The research was conducted about a year ago when enthusiasm was high, but it was still early for people to understand the potential of the medium", he explains.
This initial early monitoring showed that usage was already widespread at that point. Henke distributed a questionnaire to all press/communication offices of the country's universities, receiving 101 responses, about a third of the total. Practically all those who responded declared that they make some use of generative AIs.
Translations, text corrections and text generation are the main uses recorded by Henke. The other functions suggested in the questionnaire—image creation, slide production, or document analysis—are instead marginal. "What we observe in this initial work is that as far as communication is concerned, artificial intelligence is adopted by universities mainly to increase process efficiency, for example, to speed them up, doing more things in less time," explains Henke.
What also emerges, especially in some open answers, is a certain caution and growing awareness towards ethical aspects. An example is data protection. "For instance, one wonders whether it is wise, or right, to feed these intelligences—owned by private companies—with university data. The issue of privacy is also important," comments the researcher. In this sense, "more and more universities in Germany are releasing their own instances of generative AI chatbots, on dedicated servers", precisely to try to maintain control over these delicate aspects.
"There is not only a technological shift underway but also a cultural one," adds Henke. "Usually the early adopters tend to be younger and fresher in the profession, more open to change." The problem highlighted, however, is that there is no policy that works for everyone. Many are also worried by the possibility that these technologies could replace jobs. "You need the social aspect of technology adoption to be taken seriously," Henke recommends.
Henke, who is now working on a new survey to assess the situation a year after the first, believes he will observe further evolution of the situation: "I know that the use of generative AI tools is bound to increase", he says. "Last year people were experimenting, but in the comments, they also explained that sometimes they were not satisfied with the results. It was probably a matter of competence. They didn't know, for example, how to make an effective prompt for their goals. Probably today this aspect will have improved. We have to now turn our head and focus on a more strategic and integrated AI approach", especially in light of the continuous updates and advancements of these tools (just a few days ago, Chat GPT 4o was launched, sparking new controversies regarding security, even among the staff of Open AI, the company that owns Chat GPT)."
Henke believes it is important that universities learn to use these new instruments without calling into question the work they have done so far and the future goals they have already planned. "Communication is about building relationships and trust. In particular, one of the main purposes of science communication (of which university communication is a particular case) serves to build trust and relationships between the public and scientific research. If you compromise these relationships using 'automated' press releases or mainly use bots to talk to the public, the latter will end up losing interest or worse, start having doubts about the institution itself. It's important that humans remain part of the process. Artificial intelligence should enhance communication, not replace it", concludes Henke.
