Archive for the ‘Artificial Intelligence’ Category

It is time to negotiate global treaties on artificial intelligence – Brookings Institution

The U.S. National Security Commission on Artificial Intelligence recently made the news when its members warned that America faces a national security crisis due to insufficient investment in artificial intelligence and emerging technologies. Commission Vice Chair Robert Work argued we dont feel this is the time for incremental budgets This will be expensive and requires significant change in the mindset at the national, and agency, and Cabinet levels. Commission Chair Eric Schmidt extended those worries by saying China is catching the US and competition with China will increase.

This is not the first time the country has worried about the economic and national security ramifications of new technologies. In the aftermath of World War II, the United States, Soviet Union, China, France, Germany, Japan, the United Kingdom, and others were concerned about the risk of war and the ethical aspects of nuclear weapons, chemical agents, and biological warfare. Despite vastly different worldviews, national interests, and systems of government, their leaders reached a number of agreements and treaties to constrain certain behaviors, and define the rules of war. There were treaties regarding nuclear arms control, conventional weapons, biological and chemical weapons, outer space, landmines, civilian protection, and the humane treatment of POWs.

The goal through these agreements was to provide greater stability and predictability in international affairs, introduce widely-held humanitarian and ethical norms into the conduct of war, and reduce the risks of misunderstandings that might spark unintended conflict or uncontrollable escalation. By talking with adversaries and negotiating agreements, the hope was that the world could avoid the tragedies of large-scale conflagrations, now with unimaginably destructive weapons, that might cost millions of lives and disrupt the entire globe.

With the rise of artificial intelligence, supercomputing, and data analytics, the world today is at a crucial turning point in the national security and the conduct of war. Sometimes known as the AI triad, these characteristics and other weapons systems, such as hypersonics, are accelerating both the speed with which warfare is waged, and the speed with which warfare can escalate. Called hyperwar by Amir Husain and one of us (John R. Allen), this new form of warfare will feature levels of autonomy, including the potential for lethal autonomous weapons without humans being in the loop on decision-making.

It will affect both the nature and character of war and usher in new risks for humanity. As noted in ourrecent AI book Turning Point,this emerging reality could feature swarms of drones that may overwhelm aircraft carriers, cyberattacks on critical infrastructure, AI-guided nuclear weapons, and hypersonic missiles that automatically launch when satellite sensors detect ominous actions by adversaries. It may seem to be a dystopian future, but some of these capabilities are with us now. And to be clear, both of us, and more broadly the worlds liberal democracies, are struggling with the moral and ethical implications of fully autonomous, lethal weapon systems.

In this high-risk era, it is now time to negotiate global agreements governing the conduct of war during the early adoption and adaptation of AI and emerging technologies to the waging of war and to specific systems and weapons. It will be much easier to do this before AI capabilities are fully fielded and embedded in military planning. Similar to earlier treaties on nuclear, biological, and chemical weapons in the post-war period, these agreements should focus on several key principles:

The good news is there are some international entities that already are working on these issues. For example, the Global Partnership on Artificial Intelligence is a group of more than a dozen democratic nations that have agreed to support the responsible and human-centric development and use of AI in a manner consistent with human rights, fundamental freedoms, and our shared democratic values. This community of democracies is run by the Organization for Economic Cooperation and Development and features high-level convenings, research, and technical assistance.

That said, there are increasingly calls for the technologically advanced democracies to come together to aggregate their capacities, as well as leveraging their accumulated moral strength, to create the norms and ethical behaviors essential to governing the applications of AI and other technologies. Creating a reservoir of humanitarian commitment among the democracies will be vital to negotiating from a position of moral strength with the Chinese, Russians, and other authoritarian states whose views on the future of AI vary dramatically from ours.

In addition, the North Atlantic Treaty Organization, European Union, and other regional security alliances are undertaking consultations designed to create agreed-to norms and policies on AI and other new technologies. This includes effort to design ethical principles for AI that govern algorithmic development and deployment and provide guardrails for economic and military actions. For these agreements to be fully implemented though, they will need to have the active participation and support of China and Russia as well as other relevant states. For just as it was during the Cold War, logic should dictate that potential adversaries be at the negotiating table in the fashioning of these agreements. Otherwise, democratic countries will end up in a situation where they are self-constrained but adversaries are not.

It is essential for national leaders to build on international efforts and make sure key principles are incorporated into contemporary agreements. We need to reach treaties with allies and adversaries that provide reliable guidance for the use of technology in warfare, create rules on what is humane and morally acceptable, outline military conduct that is unacceptable, ensure effective compliance, and take steps that protect humanity. We are rapidly reaching the point where failure to take the necessary steps will render our societies unacceptably vulnerable, and subject the world to the Cold War specter of constant risk and the potential for unthinkable destruction. As advocated by the members of the National Security Commission, it is time for serious action regarding the future of AI. The stakes are too high otherwise.

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It is time to negotiate global treaties on artificial intelligence - Brookings Institution

Artificial intelligence in helping with COVID-19 | JIR – Dove Medical Press

Hui Xie,1,2 Qing Li,2,3 Ping-Feng Hu,4 Sen-Hua Zhu,5 Jian-Fang Zhang,6 Hong-Da Zhou,1 Hai-Bo Zhou4

1Department of Radiation Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Peoples Republic of China; 2Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province, Chenzhou, 423000, Peoples Republic of China; 3Department of Interventional Vascular Surgery, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Peoples Republic of China; 4Department of Radiology, The Second Peoples Hospital of Chenzhou City, Chenzhou, 423000, Peoples Republic of China; 5Beijing Linking Medical Technology Co., Ltd, Beijing, 100085, Peoples Republic of China; 6Department of Physical Examination, Disease Control and Prevention of Chenzhou, Chenzhou, 423000, Peoples Republic of China

Correspondence: Qing LiDepartment of Interventional Vascular Surgery, Affiliated Hospital (Clinical College) of Xiangnan University, 25 Renmin Street, Chenzhou, 423000, Peoples Republic of ChinaTel +86 19918761912Email xnxyliqing@163.com

Objective: The aim of this study was to explore the role of the AI system which was designed and developed based on the characteristics of COVID-19 CT images in the screening and evaluation of COVID-19.Methods: The research team adopted an improved U-shaped neural network to segment lungs and pneumonia lesions in CT images through multilayer convolution iterations. Then the appropriate 159 cases were selected to establish and train the model, and Dice loss function and Adam optimizer were used for network training with the initial learning rate of 0.001. Finally, 39 cases (29 positive and 10 negative) were selected for the comparative test. Experimental group: an attending physician a and an associate chief physician a read the CT images to diagnose COVID-19 with the help of the AI system. Control group: an attending physician b and an associate chief physician b did the diagnosis only by their experience, without the help of the AI system. The time spent by each doctor in the diagnosis and their diagnostic results were recorded. Paired t-test, univariate ANOVA, chi-squared test, receiver operating characteristic curves, and logistic regression analysis were used for the statistical analysis.Results: There was statistical significance in the time spent in the diagnosis of different groups (P< 0.05). For the group with the optimal diagnostic results, univariate and multivariate analyses both suggested no significant correlation for all variables, and thus it might be the assistance of the AI system, the epidemiological history and other factors that played an important role.Conclusion: The AI system developed by us, which was created due to COVID-19, had certain clinical practicability and was worth popularizing.

Keywords: CT, COVID-19, intelligent analysis, AI, helping role

This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License.By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

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Artificial intelligence in helping with COVID-19 | JIR - Dove Medical Press

Trueblue Designs the Future of Artificial Intelligence and Analytics for Healthcare With Aidea Integrated With Microsoft Dynamics 365 – Business Wire

VERONA, Italy--(BUSINESS WIRE)--Trueblue, after having announced the integration of its Artificial Intelligence Relationship Management with Microsoft Dynamics 365 and Power Platform, officially launches on the market:

AiDEA

Smart Customer Engagement

AiDEA is the new AI driven Omnichannel Customer Engagement suite. The foundation of the solution, represented by Artificial Intelligence , integrates and powers the operational and analytical functionalities based on Microsoft Dynamics 365 and Power Platform, for a holistic and integrated experience, with the goal of revolutionizing the working model of Pharma & Life Science markets, simplifying omni-channel engagement through intuitive and conversational interaction.

Two fundamental components guide the change, whose union had not yet materialized in the reference market: the concrete integration of Big Data in the perspective of Multichannel Management and the use of Artificial Intelligence functionalities and algorithms. The latter is an element that can no longer be postponed from an IT point of view, as it is necessary to drive Customer Engagement processes to satisfy company objectives from both a strategic and an operational point of view.

These elements require a structural change in the approach of organizations and tools, as a generic Customer Relationship Management system is no longer sufficient. It is in fact necessary to adopt specific Smart Omnichannel Customer Engagement solutions, fully enabled in terms of Artificial Intelligence, to have, in a quick, simple and intuitive way, precise indications about one's own customers.

As part of this transition in fact, Pharma companies such as Angelini Pharma, Alfasigma and others are taking this direction with strength and determination with the aim of innovating and achieving their business results faster.

"Artificial Intelligence represents a tremendous opportunity to increase our effectiveness and we want to provide this competitive advantage to our employees thanks to AiDEA" said Pierluigi Antonelli, CEO of Angelini Pharma "After a long and thorough analysis, we identified Trueblue and Microsoft as the best partners to advance our Customer Engagement capabilities by delivering an innovative digital CRM solution that transforms strategy into action.

Trueblue, which has always been at the center of technological and digital innovation for the pharmaceutical industry, thanks to the integration with Microsoft introduces with AiDEA a new paradigm in which Artificial Intelligence is the backbone and key factor of the evolutionary process.

"Through this integration, Trueblue will help companies in the industry accelerate their growth and find new ways to drive Digital Innovation through a wide range of solutions that will enable them to simplify the use of AI in their daily activities," said Marco Bonesini CEO of Trueblue

In todays reality of accelerated digital transformation processes, pharma & life science companies rely on proactive solutions such as AIDEA, integrated with Dynamics 365 and Power Platform, to enable effective omnichannel strategies said Elena Bonfiglioli, Managing Director, HealthCare and Life Sciences, EMEA Regional Lead.

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Trueblue Designs the Future of Artificial Intelligence and Analytics for Healthcare With Aidea Integrated With Microsoft Dynamics 365 - Business Wire

Detecting colon cancer early with artificial intelligence – wtkr.com – wtkr.com

NORFOLK, Va. - News 3 is taking action for your health!

March is National Colorectal Cancer Awareness Month. Be aware - the Hampton Roads area was identified as a "hot spot" for colon cancer deaths, according to the American Cancer Society.

In Norfolk, a trial is currently underway, adding the tool of artificial intelligence in the quest for prevention.

As the video indicates, AI technology is like an extra set of eyes; it highlights areas of interest when a patient undergoes a colonoscopy.

Early detection means better outcomes, and the addition of artificial intelligence in the screening appears to be an asset for both doctor and patient.

Dr. David Johnson calls it a game changer.

Weve used it for a year. We find it incredibly helpful in our practice and now in the trial, we see an increment in even among experts detecting polyps. We can do better. There were 3,000 cases in 2020 of colon cancer, 53,000 deaths. Barbara, we have to do better, and we can," Dr. Johnson said.

Related: Local woman shares story of colon cancer, warns others to get screened

The American Cancer Society recommends that you start screening at the age of 45 if you are at normal risk.

If you are at a higher risk, talk to your primary care provider.

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Detecting colon cancer early with artificial intelligence - wtkr.com - wtkr.com

Everything in Moderation: Artificial Intelligence and Social Media Content Review – JD Supra

Interactive online platforms have become an integral part of our daily lives. While user-generated content, free from traditional editorial constraints, has spurred vibrant online communications, improved business processes and expanded access to information, it has also raised complex questions regarding how to moderate harmful online content. As the volume of user-generated content continues to grow, it has become increasingly difficult for internet and social media companies to keep pace with the moderation needs of the information posted on their platforms. Content moderation measures supported by artificial intelligence (AI) have emerged as important tools to address this challenge.

Whether you are managing a social media platform or an e-commerce site, minimizing harmful content is critical to the user experience. Such harmful content can include everything from posts promoting violence to child abuse. In fact, the range and scope of potential harmful content has proven too broad for human moderators to comprehensively review. AI systems, designed to mirror the way humans think and process information, may be able to improve the speed and accuracy of this process. AI technology can take large data sets and teach machines to identify patterns or make predictions about certain inputs. Ultimately, this capability allows computers to recognize and filter certain words or images with more efficiency than humans can process this information. As an added benefit, this reduces or could potentially eliminate the need for human moderators to be directly exposed to harmful content.

While AI systems are promising, they are not without their own set of challenges. By some estimates, there are 2.5 quintillion bytes of data created each day. As such, while AI offers a way to more efficiently process large amounts of data, the volume of content at issue is now so vast that it has become critical that AI models perform with both speed and accuracy. And achieving optimal accuracy requires an AI model to not only be based on accurate data and imagery but also be able to appreciate nuances in the content reviewed to distinguish satire from disinformation. Further, questions have been raised regarding whether these models remove the inevitable biases of human content moderators, or if the AI models themselves actually introduce, entrench or amplify biases against certain types of users. One study, for example, found that AI models trained to process hate speech online were 1.5 times more likely to identify tweets as offensive or hateful when written by African-American users.

This tension demonstrates the difficult balance between designing models to address human inefficiencies and root out human error in content moderation while ensuring new systematic issues are not introduced into the models themselves. In fact, U.S. policymakers have conducted numerous hearings and floated legislative proposals to address concerns regarding bias within AI systems and the unintentional discrimination that could result from using such systems.

AI systems undeniably offer online platforms enhanced capabilities to effectively moderate user-generated content, but they present their own set of challenges that must be considered as these systems are designed and deployed as moderation tools.

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Everything in Moderation: Artificial Intelligence and Social Media Content Review - JD Supra