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Will robotic home health aides ever possess the compassion and technical expertise to care for the most vulnerable among us? Can artificial intelligence (AI) adequately recover the voiceless from the historical record? What can we do to make sure AI revolutionizes our world for the better?

For Ravi Bellamkonda, Emory University provost and executive vice president for academic affairs, questions like these are at the heart of AI.Humanity, a major university-wide initiative launched this academic year.

Emory seeks to realize the full potential of technology to shape the human endeavor, Bellamkonda says. We want to put AI into the service of humanity by using it to guide health, law, business, arts and humanities in thoughtful, ethical and wise ways.

Led by an advisory group of Emory faculty with diverse expertise in the field, the AI.Humanity initiative aims to recruit 60 to 75 new, leading faculty over three to five years. Hired through each of Emorys nine schools, this broad range of AI scholars will be poised for interdisciplinary work in four major focus areas: business and free enterprise, human health, law and social justice, and arts and humanities.

The initiative will be sustained by a focus on community-building to encourage scholarly collaboration, as well as educational opportunities for faculty, students and the Emory community.

AI has limitless opportunities as well as many grave challenges, says Emory President Gregory L. Fenves. Emory faculty and students have the multidisciplinaryexpertise neededto develop creative and thoughtful innovations so that AI can be a force for good improving our world and the human experience.

The most urgent research challenges in AI right now are complex and multifold, and they will require true interdisciplinary collaboration in order to be addressed not just within the sciences but with the humanities and social sciences as well, adds Lauren Klein, Winship Distinguished Research Professor of English and Quantitative Methods. Its thrilling to see the AI.Humanity initiative take shape at Emory, an institution that has long valued precisely this kind of transformative research.

Enhancing a cross-campus network

New hire Anant Madabhushi performs the kind of work Klein describes. A bioengineer by training, Madabhushi will join Emorys School of Medicine in July. Madabhushi uses artificial intelligence and machine learning techniques to improve outcomes for individuals with cancer and other diseases, as well as to help tackle racial health disparities and global health.

With ethics at the core of the AI.Humanity initiative, the inaugural James W. Wagner Chair in Ethics will be another early hire primed for interdisciplinary work.

While the AI.Humanity initiative is new, these and other faculty recruits will join an established network of AI scholars and ready collaborators across campus.

The intellectual and physical geography of the Emory campus are highly conducive to collaboration, notes Lance Waller, a professor in the Rollins School of Public Health and leader of the Woodruff Health Science Centers strategic initiative in data science. Im a biostatistician, trained as an engineer, but when I want to add a new dimension to my research, I dont have to go far to find art historians, epidemiologists, environmental lawyers and others with interesting ideas.

AI.Humanity is building on that in exciting new ways by recruiting a significant cohort of new colleagues who not only bring expertise in AI, but intentional focus in fields where Emory is already strong, Waller adds. The scope and the potential of the community were creating is truly powerful.

Earlier this semester, Emory researchers met to learn about each others work in data science and artificial intelligence through the Constructive Collisions program, run through the Office of the Senior Vice President for Research. The office is also providing seed grant funding to connect Emory and Georgia Tech faculty to spur new research collaborations and expand existing partnerships to leverage the artificial intelligence to improve society and our daily lives.

Building on these beginnings, the AI.Humanity community subgroup Waller leads is actively working to create new opportunities for collaboration. These include offering pilot funding and incubators in which projects and workgroups can grow, as well as lecture series and workshops.

A second AI.Humanity subgroup is focused on expanding educational opportunities across campus.

We believe in Al for all, says leader Vaidy Sunderam, chair of the Department of Computer Science. As the digital age advances, its becoming more and more important to have an understanding of what AI means, what it can and cant do, how to interface with it and when to be wary of it.

Infusing AI into both curricular and co-curricular spaces, the group is tasked with everything from promoting basic AI/ML (machine learning) literacy that allows students to answer questions like What does it mean to be a citizen in a digital world? to creating new interdisciplinary major, minor or certificate programs for those who want to focus more deeply.

Connecting AI to everyday life

The ongoing AI.Humanity Ethics Lecture Series is already bringing both educational and community-building opportunities to Emory. Held in April and May, it features world-renowned scholars approaching AI ethics from their own respective fields computer science, philosophy and law and highlights how critical ethical inquiry is to shaping the future of these fast-advancing technologies.

Ethics isintrinsicto AI, says Paul Root Wolpe, director of Emorys Center for Ethics and Raymond F. Schinazi Distinguished Research Chair in Jewish Bioethics. By that I mean that the purpose of AI is to make decisions, and decisions themselves are always based on some set of values, and the consequences of those decisions have ethical implications.

You cannot create AI without AI ethics, Wolpe continues. Emorys ethics scholarship throughout its schools, its singular Center for Ethics and the promise of ethical engagement in its vision statement situates Emory as the premier university to take AI ethics into the future.

Its precisely this kind of broad perspective that will distinguish Emorys approach to artificial intelligence research and education in a highly technical age, according to Bellamkonda.

We want technology to help us realize the full potential of human beings, expressing themselves as a community informed by values, in a manner that we actively choose and shape, he says. This is the space that Emory seeks to pursue. It is the space where we excel as a university, and where we seek to contribute to the world.

Visit Emorys AI.Humanity website to learn more about the initiative, including news and events.

Emory University Provost Ravi Bellamkonda explains that Emorys AI.Humanity initiative will bring together a community of scholars who understand the interface of AI machine learning and their impact on human health, law and social justice, business and free enterprise, and arts and humanities.

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Emorys AI.Humanity Initiative Aims to Shape the Future of Artificial Intelligence to Serve Society - SaportaReport

Machine learning systems have gotten extremely good at generating stock imagery from just a few bits of text. AI tools like Open AIs DALL-E have quickly become a favorite among artists, allowing them to generate extremely specific and surreal images by typing things like cats playing chess in space or shrimp sitting on a park bench contemplating life.

Artist David OReilly took this even further, using the generative systems to create an entire animated childrens cartoon called Bartak. The result is a storybook-esque nightmare world that feels like the machine learning equivalent of being lobotomized. Characters faces melt into digital oblivion while a chipper AI-generated voice narrates the story in an extremely unsettling non-language that sounds like a Disney Channel host speaking in tongues.

OReilly, a 3D artist who is well-known for creating these kinds of disturbing animations, describes the short as a sneak peak of a series that uses the awesome power of AI to create the perfect kids entertainment. In an Instagram post, OReilly claims that a full season order of 75,000 episodes is now being generatedwhich may or may not be true, given his track record of unsettling one-off provocations. (OReilly could not be reached for comment)

DALL-E and other natural language processing systems are known for their ability to generate uncannily accurate results. Previous systems like GPT-3, which is frequently used by chatbots, have been used to create AI dungeon text adventures and even occult rituals that feel disturbing realisticso much so that its often difficult to distinguish the systems output from a real human.

Researchers have found that these systems are also prone to generating results that reproduce racist and sexist stereotypes. In an analysis of DALL-E, Open AIs researchers found that typing things like CEO would exclusively generate images of white men, while typing nurse would produce images of Southeast Asian women.

As a weird art project, OReillys use of the tool seems relatively benign, however. And his fans seem to be in on the joke.

Its really inspiring to see how well Bartak has helped my kids understand the world around them, and taught me how to be a better parent! writes one Instagram commenter of the extremely cursed cartoon. My kids are so much smarter as a result. You want to see the excitement in their eyes, especially at the hands of a show like this.

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AI Created This Extremely Cursed Children's Cartoon - VICE

Advanced technologies such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) have become a cornerstone of successful modern clinical trials, integrated into many of the technologies enabling the transformation of clinical development.

The health and life sciences industrys dramatic leap forward into the digital age in recent years has been a game-changer with innovations and scientific breakthroughs that are improving patient outcomes and population health. Consequently, embracing digital transformation is no longer an option but an industry standard. Lets explore what that truly means for clinical development.

An accelerated path to better results

Over the years, technology has equipped clinical leaders to successfully reduce costs while accelerating stages of research and development. These technologies have aided in the structurization of complex data environmentsa need created by the exponential growth in data sources containing valuable information for clinical research.

Today, the volume, variety and velocity of structured and unstructured data generated by clinical trials are outpacing traditional data management processes. The reality is that there is simply too much data coming from too many sources to be manageable by human teams alone. As a response to this, AI/ML technologies have proven in recent years to hold the remarkable potential to automate data standardization while ensuring quality control, in turn easing the burden on researchers with minimal manual intervention.

Once the collection and streamlining of data is compiled within a single automated ecosystem, clinical trial leaders begin to benefit from faster and smarter insights driven by the application of machine analysis. These include the creation of predictive and prescriptive insights that can aid researchers and sites to uncover best practices for future processes. Altogether, these capabilities can improve research outcomes, patients experience and safety.

A look into compliance and privacy

When we think about the use of patient data, privacy and compliance adherence must be a consideration. The bar is set high for any technology being implemented into clinical trial execution.

Efforts must adhere to Good Clinical Practice (GcP) and validation requirements that ensure an outcome is valid by it being predictable and repeatable. Additionally, there must be transparency and explainability around how any AI algorithm makes decisions to prove correctness and avoidance of any potential bias. This is becoming more essential than ever from a compliance perspective as regulators look at algorithms as part of what they base their approvals on.

Keeping the h(uman) in healthcare

The goal of implementing AI/ML in clinical research is not to replace humans with digital tools but to increase their productivity through high-efficiency human augmentation and the automation of mundane tasks. Before the application of advanced technologies to clinical trials, there was an unmet need for an agile methodology where researchers and organizers could solely focus on critical requirements and the delivery of results.

The intelligent application of technology allows for human interaction with AI models to bring better outcomes to research, and even in its most advanced stage, data science technology never replaces the human data scientist. It does, however, provide a mutually beneficial circumstance wherein the augmentation of workflows allows data scientists to ease data burden while AI models flourish through human feedback. This continuous learning by an AI model is known as Continuous Integration/Continuous Delivery (CI/CD).

The integration of human capacity and technology results in accelerated efficiency, improved compliance and superb patient personalization. Furthermore, regardless of how efficient algorithms become, the decision-making power will always belong to humans.

Envisioning a bold future

AI/ML strategies are redefining the clinical development cycle like never beforeand as the industry leaps into new frontiers, digital transformation is leading the way to incredible advancements that will revolutionize the space forever. Leaders today have the opportunity to apply advanced technologies to solve historically complicated problems in the field.

Already, weve seen better site selection, more effective risk-based quality management, improved patient monitoring and safety, enhanced patient recruitment and engagement, and improved overall study qualityand this is just the beginning.

Photo: Blue Planet Studio, Getty Images

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The role of AI and machine learning in revolutionizing clinical research - MedCity News

Creating a machine learning agent to ease interactions between participants in virtual and augmented reality environments such as the metaverse in order to help them achieve their goals and address conflict situations. This is the main objective ofGuestXR, the European project under the coordination of professor Mel Slater, from theFaculty of Phycologyand the Institute of Neurosciences of the University of Barcelona UB (UBNeuro).

As part of the GuestXR project (A Machine Learning Agent for Social Harmony in eXtended Reality), coordinated by the Eurecat technological centre, a machine learning system called guest will be designed, and it will work as an agent able to examine the individual and group behaviour of the participants by drawing on existing models from the neuroscience and social psychology standpoint. Moreover, Deep Reinforcement Learning will train the Guest to learn over time both in simulations and real meetings and it will be more efficient in social interaction, informs UB in a press release.

In these lines, the agent will take part in the conversation in different ways, performing a range of multisensory actions through music or changes in space, among others, notes the director of Eurecat Audiovisual Technologies, Adan Garriga.

Each meeting in virtual and augmented reality has a purpose, be it explicit (for instance, reaching an agreement on a topic) or implicit (such as enjoyment). The basic idea of the guest is to help the group of people to accomplish this purpose. This involves an exciting research with a strong interdisciplinary element, which opens new paths, and hopefully, contributes to the success of virtual and augmented reality, notes Professor Mel Slater.

In order to modulate this social interaction, the guest will carry out a series of multisensory actions, through, for instance, visual and auditory features to create specific states of mind and stimulate a relaxed environment when it identifies a conflict, highlights researcher Umut Saying, from Eurecat Audiovisual Technologies.

This project is designed to help offering solutions to the existing challenges in online environments of social interaction such as online harassment, for which there isnt a specific European legislation, says the coordinator of the Eurecat GuestXR project, Aurora Ses.

The intervention of the machine learning system will initially be tested in conflict resolution situations, interactions with participants with hearing difficulties and contexts that lead to polarized debates such as climate change.

Two open calls to include other innovative use cases to test the effectiveness of the system are expected. One case will be aimed at society in general including companies and associations, among others while the other will aimed at the field of arts.

The GuestXR technology will be carried out under the Ethics by design approach, which entails considering the potential ethical problems derived from the use of artificial intelligence (respect for human autonomy, prevention of harm, fairness, etc.).

The GuestXR consortium, coordinated by the UB and the Eurecat technology centre, is formed by eight organizations from six countries with multidisciplinary teams of the field of the expanded reality, machine learning, artificial intelligence, social psychology, neuroscience of emotions, multisensory integration, ethics of research and technology transfer. Among the collaborators are the University of Maastricht (the Netherlands), the University of Warsaw (Poland), the University of Reichman (Israel), the National Institute for Research in Digital Science and Technology (INRIA, France), and the companies Virtual Bodyworks and G.tec medical engineering GMBH.

Building the metaverse in Europe: open source collaboration platforms gain momentum

After Mark Zuckerbergs public announcement that Facebook is rebranding itself as Meta, the metaverse has once again become a buzzword.

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Machine learning tool improves conflict management in the metaverse - Innovation Origins

Research and innovation in machine learning in the mining industry operations and technologies sector has declined in the last quarter but remains higher than it was a year ago.

The most recent figures show that the number of related patent applications in the industry stood at 16 in the three months ending March up from 10 over the same period in 2021.

Figures for patent grants related to followed a different pattern to filings stagnating from one in the three months ending March 2021 to one in the same period in 2022.

The figures are compiled by GlobalData, which tracks patent filings and grants from official offices around the world. Using textual analysis, as well as official patent classifications, these patents are grouped into key thematic areas and linked to key companies across various industries.

Machine learning is one of the key areas tracked by GlobalData. It has been identified as being a key disruptive force facing companies in the coming years, and is one of the areas that companies investing resources in now are expected to reap rewards from. The figures also provide an insight into the largest innovators in the sector.

Honeywell International was the top innovator in the mining industry operations and technologies sector in the latest quarter. The company, which has its headquarters in the US, filed nine related patents in the three months ending March. That was up from three over the same period in 2021.

It was followed by the US-based Caterpillar with six patent applications, and Japan-based Komatsu (1 applications).

Innovative Industrial Technologies

Process Instrumentation Systems and Bulk Solids Sensors for the Mining Sector

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Machine learning innovation among mining industry companies dropped off in the last quarter - Mining Technology