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Artificial intelligence examines best ways to keep parolees from recommitting crimes - ScienceBlog.com

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Starting a new life is difficult for criminals transitioning from prison back to regular society. To help those individuals, Purdue University Polytechnic Institute researchers are using artificial intelligence to uncover risky behaviors which could then help identify when early intervention opportunities could be beneficial. Results of a U.S. Department of Justice study indicated more than 80 percent of people in state prisons were arrested at least once in the nine years following their release. Almost half of those arrests came in the first year following release. Marcus Rogers and Umit Karabiyik of Purdue Polytechnic's Department of Computer and Information Technology, are leading an ongoing project focused on using AI-enabled tools and technology to reduce the recidivism rates for convicted criminals who have been released.


New machine learning tool predicts devastating intestinal disease in premature infants

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Necrotizing enterocolitis (NEC) is a life-threatening intestinal disease of prematurity. Characterized by sudden and progressive intestinal inflammation and tissue death, it affects up to 11,000 premature infants in the United States annually, and 15-30% of affected babies die from NEC. Survivors often face long-term intestinal and neurodevelopmental complications. Researchers from Columbia Engineering and the University of Pittsburgh have developed a sensitive and specific early warning system for predicting NEC in premature infants before the disease occurs. The prototype predicts NEC accurately and early, using stool microbiome features combined with clinical and demographic information. The pilot study was presented virtually on July 23 at ACM CHIL 2020.


Artificial Intelligence and Archives • CLIR

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—Rebecca Bayeck and Azure Stewart “Artificial Intelligence and Archives” was the inaugural webinar of the series on Emerging Technologies, Big Data & Archives, organized by CLIR postdocs Rebecca Y. Bayeck of the Schomburg Center for Research in Black Culture and Azure Stewart of New York University. With the emergence of new technologies and big data, the processing and preservation of data has changed and will continue to change. As in other domains (e.g., health, video games), artificial intelligence (AI) is increasingly reshaping the way we process, interact with, and think about archives. Consequently, in the age of big data, archives are not just “a collection of historical records relating to a place, organization, or family” (Cambridge Dictionary Online). Today, archives also include all types of digital data—including social media data—and algorithms. Archivists are therefore called on to preserve and process data as they are being created, which requires understanding AI languages, processes, and practices for the creation and protection of data/records now for the future. In this webinar, our speaker Dr. Anthea Seles, from the International Council on Archives (ICA), discussed AI in archival spaces: its uses, application, and the role archivists should play to become critical voices in AI discussions. Two hours were not enough to address all the questions raised by the 280 attendees. As a follow up to the webinar, we have thematically organized and addressed the unanswered questions and present them here. Artificial Intelligence in Archives How much has AI penetrated archives in the developing world? I would say [this has been] limited, if at all. I think the main issue is that these technologies are being applied in the assessment of development initiatives like Sustainable Development Goals (SDGs). Increasingly there are many projects focusing on artificial intelligence and human rights, for example the University of Essex Human Rights, Big Data and Technology Project, and it is becoming a concern for organisations like Amnesty International. Who already has the best AI for archives today, according to ICA regulation, that we can adopt? There is no commercial provider that works specifically on archival questions. I think you can use off-the-shelf eDiscovery software, but you need to have a basic understanding of what the technology is doing in order to measure your precision and recall.  Artificial Intelligence Tools Will governments and big corporations use artificial intelligence as a tool to centralize information in future? Potentially. I think there is some thinking about this coming out of the records management community, but I still believe it is about balancing the strengths of the tool with the continuing need for human intervention. The question is, when will the human be needed? And what can the tool be trusted to do with minimum supervision? How do we ensure a continuous feedback loop to identify records of long-term value as information creation changes?  What tools were you using for the file analysis and visualization in this presentation? The screen shots are only example photos, they are not from any of the tools we used. We looked at several eDiscovery tools with different algorithms (e.g., Latent Semantic Indexing, Latent Dirichlet Allocation). These are bog standard machine learning applications that have been around for a while, and we chose to go down that road to see what we could get in off-the-shelf commercial software packages. So, is there a way to write a script to avoid metadata corruption and alteration? There are tools now you can use that will preserve the integrity of the metadata when you move material from one system or file to another. I think for historical metadata alteration/corruption it is a question of how we explain this to users and how this might affect different access methods like visualisation.  Will the International Council on Archives provide training on artificial intelligence and machine learning? Not yet, but I’m open to suggestions. [We are] currently speaking with different stakeholders and maybe we can hold a hackathon at the Abu Dhabi Congress.  Access to Archives Will the course Managing Digital Archives be accessible online? The managing digital archives course is organized by the ICA and will be accessible online in fall 2020. Please check the ICA website or social media channels (Twitter and Facebook) for more information. What are some of the practices in the UK National Archives and government on managing structured data as records? How does the UK identify, capture, manage, and apply retention and disposition to data (both transactional applications and analytical ones)? There are no published policies on identification of datasets that I can see and would suggest you contact either the record copying or the UK government web archive records unit to see if anything more substantive has been developed. What is your suggestion for keeping physical records for posterity and authentication? Records should always be maintained in the format in which they are created. The belief in scanning paper records and destroying them in order to save space and save on storage costs is a false economy. The level at which you should be scanning that material and the amount of metadata that should be captured to maintain it over time is very high. Also, you need to take into account computer storage costs, and whether you can afford the costs of digital preservation software, which all begins to add up. One must also take into account the active management of these authentic digital surrogates by digital preservation specialists. Furthermore, if you have a paper management problem and you don’t take that into account when you move into the digital environment you are then transferring an analog integrity issue into a digital integrity/authenticity issue. Digital will not solve integrity issues; in my opinion it will magnify them. Artificial Intelligence and Society In Brazil, we are concerned with the problem of the spread and political use of misinformation (fake news). How can archivists with algorithm training provide reliable research insights to fight against this historical problem? At this point, I couldn’t honestly provide you with an answer but Read More


AI Helps Forecast Volcanic Eruptions

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Volcanoes are one of the most important geological forces on the planet. Their activity can halt air travel, impact air quality, force evacuations and damage communities. It isn't currently possible to predict when one might blow or for how long. But there are important indicators, including changes in seismic activity, temperature, gas emissions and the shape of the ground, that can alert researchers whether a volcano may be shifting from dormant into a more explosive mode, scientists say. Increasingly, volcanologists are turning to artificial intelligence to help them sift through these data streams, which come from sensors on the ground, in the sky and in space.


How Artificial Intelligence can help improve air quality

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When we think of air pollution, we often think of Delhi, perhaps Beijing, or even Shanghai. Hence, the World Health Organisation (WHO) reports that 9 out of 10 people around the world breathe polluted air. As humans, we contribute the most to air pollution by using energy to drive our vehicles, power our houses, run our data centers, and to travel. So much so that everything we use today was made at a factory that has contributed to air pollution. Today, technology has become an enabler to help address air pollution.


New Machine Learning Tool Predicts Devastating Intestinal Disease in Premature Infants

#artificialintelligence

Necrotizing enterocolitis (NEC) is a life-threatening intestinal disease of prematurity. Characterized by sudden and progressive intestinal inflammation and tissue death, it affects up to 11,000 premature infants in the United States annually, and 15-30 percent of affected babies die from NEC. Survivors often face long-term intestinal and neurodevelopmental complications. Researchers from Columbia Engineering and the University of Pittsburgh have developed a sensitive and specific early warning system for predicting NEC in premature infants before the disease occurs. The prototype predicts NEC accurately and early, using stool microbiome features combined with clinical and demographic information. The pilot study was presented virtually on July 23 at ACM CHIL 2020.


Beck teams up with NASA and AI for 'Hyperspace' visual album experience

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Grammy award-winning artist Beck took an ethereal journey to the stars for his 2019 record "Hyperspace." Now, he has taken this cosmic journey a giant leap forward in a collaboration with NASA's Jet Propulsion Laboratory and artificial intelligence creatives OSK. The result: A visual album experience titled "Hyperspace: A.I. Exploration." The new visual album, unveiled today (Aug. To launch "Hyperspace: A.I. Explorations," Beck premiered a bonus track from "Hyperspace" titled "I Am The Cosmos (42420)," on Aug. 12 on Youtube along with videos for the rest of the songs.


AI Computing Platform

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The cognitiveAI Platform is a cloud-based AI software platform for deriving new levels of Enterprise value from multiple data sources. The AI platform is designed to be cost-effective, easily deployed and used to simplify complexity while unlocking the power of Semantic Computing.


Apes Spotted Flying Drone and Smiling

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In a new short video that has surfaced on TikTok, apes have been spotted flying drones. The drone is an Autel Robotics Evo and the apes are located in a Myrtle Beach Safari in South Carolina. The video was taken by photographer Nick B. and shows two apes flying a drone. One is standing up using the drone's controller while the other sits beside him holding the drone's case. The video is particularly impressive as the ape seems very much in control of the drone.


What happens in Vegas… is captured on camera

MIT Technology Review

The use of facial recognition by police has come under a lot of scrutiny. In part three of our four-part series on FaceID, host Jennifer Strong takes you to Sin City, which actually has one of America's most buttoned-up policies on when cops can capture your likeness. She also finds out why celebrities like Woody Harrelson are playing a starring role in conversations about this technology. Credits: This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley and Emma Cillekens. We had help from Benji Rosen and Karen Hao.