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Category Archives: Artificial Intelligence

Three key themes on artificial intelligence – Research Information

Posted: February 20, 2024 at 6:56 pm

Verena Weigert reports from Jiscs Research and Innovation Sector Strategy Forum Workshop on AI and Research

Artificial intelligence is making waves in nearly every industry and sector, and research is no different; its impact on the design and management of the research system appears likely to become more pronounced in the coming years. The rapid advancement in the development of new AI tools presents opportunities for innovation and raises questions about how responsible use of these tools looks like in research.

It is a key time for research organisations to discuss ways AI might change, and enhance, the research and innovation sector.

Jisc recently organised a workshop to discuss AI in research, its management and leadership with our Research and Innovation Sector Strategy Forum of UK Deputy and Pro-Vice-Chancellors and Principles for Research and Innovation. The forum is a vibrant community, with representatives from a diverse range of UK institutions and reflect the views of senior managers and researchers in universities.

Fifteen pro-vice-chancellors and principals for research from all four UK nations met to discuss how AI might change the research and innovation sector, and how AI applications could be used in research and research management and the implications for researchers and research professionals.

Three key themes emerged from the conversation the effect of AI on research practice, AI as a tool for researchers, and the possible opportunities and challenges that AI in the research sector will bring.

Forum participants emphasised that to fully realise the benefits of AI in research, we need confidence that AI is being deployed appropriately and ethically. Integrity, transparency and accountability need to be designed into the use of the technology to preserve trust in research.

Dr Jennifer Chubb, a sociologist at the University of York with a research focus on the role of responsible storytelling and ethical development of AI, highlighted that we must increase awareness of the effect of AI on research practice: There is need for a greater understanding of the effect of AI on researchers and their creativity. Studies of the role of AI in research need to askfundamental questions about how the technology might provide new tools thatenable scholars to question thevalues and principlesdriving institutions andresearch processes.

Professor Nick Plant, Deputy Vice-Chancellor: Research and Innovation at the University of Leeds, said he hoped that:AI could help to free up time for researchers to focus on the creative and collaborative aspects of their work and help to get back to the roots of what it means to work in academia.

Our workshop participants welcomed the potential AI has to be an enabler of new processes. They also reflected on its effect on research culture and whether it might create unsustainable metrics that disadvantage researchers. There is a need for the appropriate use of AI tools and for assurance and ethics at an individual as well as institutional level. They highlighted the fact that AI applications could help with tasks such as processing grant applications, help with research data management, support for evaluation, demonstrating impact and financial reporting and data centre capacity management to name a few.

Our workshop participants welcomed the potential AI has to be an enabler of new processes. They also reflected on its effect on research culture and whether it might create unsustainable metrics that disadvantage researchers. There is a need for the appropriate use of AI tools and for assurance and ethics at an individual as well as institutional level.

Professor Maria Delgado, Vice Principal (Research and Knowledge Exchange) at the Royal Central School of Speech and Drama, University of London was mindful about some of the language around AI, saying: We should focus on different ways to navigate knowledge rather than highlight how AI can speed up tasks. Faster is not necessarily better and might disadvantage groups at particular career stages or in different disciplines, with possible implications on integrity and inclusivity."

Clifford Lynch, Director of the Coalition of Networked Information (CNI) who offered a US perspective on the use of AI in research, added: "The development of a national network of cloud labs is an important trend that complements AI in research." He pointed out that Carnegie Mellon University for example, was the first university to build a cloud lab in an academic setting designed to automate lab experiments with robotics and AI at an institutional scale.

Universities have been taking steps to consider what the use of AI in the research process means for their institutions.

Bella Abrams, Director of Information Technology at the University of Sheffield, highlighted that it is important to openly acknowledge the sustainability issues related to AI. While it can help with climate protection, she said, the energy demand and carbon emissions of some AI models that are trained with huge amounts of data is vast. With a better understanding of how much energy AI systems consume, institutions could decide what trade-offs they would like to make. There could be questions about the societal benefits of research with a high climate impact in the future.

Professor Matt Bellgard, Pro Vice-Chancellor (Impact and Innovation) at the University of East London was interested in using AI to support institution-wide research data management and to potentially capture real time data on the research process along the research journey to identify the areas of support and training needed at each stage of the research lifecycle.

Over the years, strict ethical guidelines have been developed among others for research collecting data from human participants and researchers now need to make decisions on the appropriate use of AI tools to meet those and other standards. The forum raised a need for guiderails for higher education institutions to ensure the responsible, ethical and efficient use of AI technologies in the research process.

The University of Strathclyde, for example, has recently launched a project to help researchers and their institutions make informed decision on how they use generative AI with participant data to project the privacy of the essential people who participate in research.

Many forum members were also in favour of considering the opportunities AI brings as a mechanism to think differently and to innovate aspects of the research system as a whole: for example, to explore how it could help to create new as yet undefined innovative scholarly publishing models which ensure research security and trust to enable a leap forward in thinking about scholarly publishing.

Jiscs Research and Innovation Sector Strategy Forum will continue to meet regularly to discuss the future benefits and challenges facing the research sector and to help shape our next steps for AI in research.

Verena Weigert is Product and Portfolio Manager (Research and Innovation Sector Strategy) at Jisc.

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Three key themes on artificial intelligence - Research Information

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How Artificial Intelligence is transforming consumerism – WFLA

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How Artificial Intelligence is transforming consumerism  WFLA

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SAP names Philipp Herzig as chief artificial intelligence officer – CIO

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SAP is reorganizing its AI activities. Philipp Herzig, formerly head of cross-product engineering and experience, now leads a new end-to-end growth area focused on AI as the companys chief artificial intelligence officer (CAIO).

Herzig now reports directly to CEO Christian Klein, and will oversee the entire value chain for SAP business AI from research and product development through to implementation at the customer.

With this new structure, SAP aims to accelerate the pace of its AI development, according to a statement from the software manufacturer. The newly established organization also underlines the central importance of business AI as a strategic driver for SAPs further growth. Herzigs team will work closely with other innovators within SAP. The aim is to integrate artificial intelligence into every part of the portfolio. Based on this, customers should be able to use SAP business AI consistently across the entire SAP portfolio.

SAPs increased focus on business AI marks the start of a completely new generation of enterprise innovation, and Im honored to have the chance to help customers make the most of this unprecedented opportunity, said Herzig, describing his role. I look forward to working with our team, as well as our ecosystem of customers and partners, to drive the development and delivery of relevant, reliable, responsible business AI that fundamentally changes the way business runs.

Walter Sun, who moved from Microsoft to SAP in September 2023, will coordinate the development of SAPs next generation of enterprise software worldwide as Global Head of AI and lead AI product developer in Herzigs team. Herzig was already Suns boss before his latest move.

This is not the only change in SAPs reporting structure. At the beginning of 2024, the company established a new Executive Board department, Customer Services & Delivery. Its head, Thomas Saueressig, is tasked with driving the still hesitant cloud transformation among customers. Product Development, which Saueressig had previously headed, has been taken over by Muhammad Alam, who has also been promoted to the SAP Executive Board. Like Sun, Alam had moved from Microsoft to SAP, albeit at the end of January 2022.

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SAP names Philipp Herzig as chief artificial intelligence officer - CIO

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Unleashing the Power of Artificial Intelligence: Transforming Web-Based Applications for Enhanced Efficiency and User … – Financialbuzz.com

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Unleashing the Power of Artificial Intelligence: Transforming Web-Based Applications for Enhanced Efficiency and User ...  Financialbuzz.com

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Koch Industries continues to accelerate its artificial intelligence initiative – The Business Journals

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Koch Industries continues to accelerate its artificial intelligence initiative  The Business Journals

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Forget Nvidia: These 3 Artificial Intelligence (AI) Stocks Can Be the Next Stock-Split Stocks – The Motley Fool

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Forget Nvidia: These 3 Artificial Intelligence (AI) Stocks Can Be the Next Stock-Split Stocks  The Motley Fool

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Artificial Intelligence for small business focus of upcoming JWCC Lunch and Learn on Feb. 28 Muddy River News – Muddy River News

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Artificial Intelligence for small business focus of upcoming JWCC Lunch and Learn on Feb. 28 Muddy River News  Muddy River News

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Opponents Highlight the Environmental Impact of Artificial Intelligence – News-Press Now

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Generative AI’s environmental costs are soaring and mostly secret – Nature.com

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Last month, OpenAI chief executive Sam Altman finally admitted what researchers have been saying for years that the artificial intelligence (AI) industry is heading for an energy crisis. Its an unusual admission. At the World Economic Forums annual meeting in Davos, Switzerland, Altman warned that the next wave of generative AI systems will consume vastly more power than expected, and that energy systems will struggle to cope. Theres no way to get there without a breakthrough, he said.

Im glad he said it. Ive seen consistent downplaying and denial about the AI industrys environmental costs since I started publishing about them in 2018. Altmans admission has got researchers, regulators and industry titans talking about the environmental impact of generative AI.

So what energy breakthrough is Altman banking on? Not the design and deployment of more sustainable AI systems but nuclear fusion. He has skin in that game, too: in 2021, Altman started investing in fusion company Helion Energy in Everett, Washington.

Is AI leading to a reproducibility crisis in science?

Most experts agree that nuclear fusion wont contribute significantly to the crucial goal of decarbonizing by mid-century to combat the climate crisis. Helions most optimistic estimate is that by 2029 it will produce enough energy to power 40,000 average US households; one assessment suggests that ChatGPT, the chatbot created by OpenAI in San Francisco, California, is already consuming the energy of 33,000 homes. Its estimated that a search driven by generative AI uses four to five times the energy of a conventional web search. Within years, large AI systems are likely to need as much energy as entire nations.

And its not just energy. Generative AI systems need enormous amounts of fresh water to cool their processors and generate electricity. In West Des Moines, Iowa, a giant data-centre cluster serves OpenAIs most advanced model, GPT-4. A lawsuit by local residents revealed that in July 2022, the month before OpenAI finished training the model, the cluster used about 6% of the districts water. As Google and Microsoft prepared their Bard and Bing large language models, both had major spikes in water use increases of 20% and 34%, respectively, in one year, according to the companies environmental reports. One preprint1 suggests that, globally, the demand for water for AI could be half that of the United Kingdom by 2027. In another2, Facebook AI researchers called the environmental effects of the industrys pursuit of scale the elephant in the room.

Rather than pipe-dream technologies, we need pragmatic actions to limit AIs ecological impacts now.

Theres no reason this cant be done. The industry could prioritize using less energy, build more efficient models and rethink how it designs and uses data centres. As the BigScience project in France demonstrated with its BLOOM model3, it is possible to build a model of a similar size to OpenAIs GPT-3 with a much lower carbon footprint. But thats not whats happening in the industry at large.

It remains very hard to get accurate and complete data on environmental impacts. The full planetary costs of generative AI are closely guarded corporate secrets. Figures rely on lab-based studies by researchers such as Emma Strubell4 and Sasha Luccioni3; limited company reports; and data released by local governments. At present, theres little incentive for companies to change.

There are holes in Europes AI Act and researchers can help to fill them

But at last, legislators are taking notice. On 1 February, US Democrats led by Senator Ed Markey of Massachusetts introduced the Artificial Intelligence Environmental Impacts Act of 2024. The bill directs the National Institute for Standards and Technology to collaborate with academia, industry and civil society to establish standards for assessing AIs environmental impact, and to create a voluntary reporting framework for AI developers and operators. Whether the legislation will pass remains uncertain.

Voluntary measures rarely produce a lasting culture of accountability and consistent adoption, because they rely on goodwill. Given the urgency, more needs to be done.

To truly address the environmental impacts of AI requires a multifaceted approach including the AI industry, researchers and legislators. In industry, sustainable practices should be imperative, and should include measuring and publicly reporting energy and water use; prioritizing the development of energy-efficient hardware, algorithms, and data centres; and using only renewable energy. Regular environmental audits by independent bodies would support transparency and adherence to standards.

Researchers could optimize neural network architectures for sustainability and collaborate with social and environmental scientists to guide technical designs towards greater ecological sustainability.

Finally, legislators should offer both carrots and sticks. At the outset, they could set benchmarks for energy and water use, incentivize the adoption of renewable energy and mandate comprehensive environmental reporting and impact assessments. The Artificial Intelligence Environmental Impacts Act is a start, but much more will be needed and the clock is ticking.

K.C. is employed by both USC Annenberg, and Microsoft Research, which makes generative AI systems.

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Chapter Summary: Genesis of Artificial Intelligence and a Scientific Revolution: 1950-1979 – EIN News

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