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Opening the ‘black box’ of artificial intelligence

opening the ‘black box’ of artificial intelligence

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When decisions are made by artificial intelligence, it can be difficult for the end user to understand the reasoning behind them. Credit: phylevn/Flickr, licenced under CC BY 2.0

Artificial intelligence is growing ever more powerful and entering people’s daily lives, yet often we don’t know what goes on inside these systems. Their non-transparency could fuel practical problems, or even racism, which is why researchers increasingly want to open this ‘black box’ and make AI explainable.

In February of 2013, Eric Loomis was driving around in the small town of La Crosse in Wisconsin, US, when he was stopped by the police. The car he was driving turned out to have been involved in a shooting, and he was arrested. Eventually a court sentenced him to six years in prison.
This might have been an uneventful case, had it not been for a piece of technology that had aided the judge in making the decision. They used COMPAS, an algorithm that determines the risk of a defendant becoming a recidivist. The court inputs a range of data, like the defendant’s demographic information, into the system, which yields a score of how likely they are to again commit a crime.
How the algorithm …

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Bidgely Recognized by NARUC for Enhancing Gas Utility Customer Engagement and Energy Efficiency Through Artificial Intelligence

bidgely recognized by naruc for enhancing gas utility customer engagement and energy efficiency through artificial intelligence

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The National Association of Regulatory Utility Commissioners (NARUC) has distinguished Bidgely as an exemplary leader in artificial intelligence (AI)

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Artificial Intelligence Risk Is Topic Of Great Valley Research

artificial intelligence risk is topic of great valley research

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MALVERN, PA — Four Penn State Great Valley professors will be researching ways to test for risk and vulnerability in Artificial Intelligence at the development stage, so practical problems can be headed off. Self-driving cars and other Artificial Intelligence-assisted technologies awaiting mainstream use depend on large volumes of collected data. If data is in any way distorted, biased or tampered with, it’s suddenly not so awesome and could pose risks to people’s lives and to public safety. A research grant will fund their project, “Managing Risks in AI Systems: Mitigating Vulnerabilities and Threats Using Design Tactics and Patterns.” The Great Valley faculty team was one of eight across Penn State campuses to receive the one-year seed grants to fund research on cybersecurity for Artificial Intelligence. “Every AI project should manage risks in a broad sense.” said Youakim Badr, associate professor of data analytics at Penn State Great Valley. He explained, “The research project aims at applying risk management when we design an AI system and continuously monitor its behavior at runtime.” In the near future, many AI applications will be in physical contact with humans and will offer unimagined opportunities in many areas such as driverless trucks, fruit harvesting robots, autonomous …

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How the Combination of Artificial Intelligence and IoT makes the Smart Factory a Reality

how the combination of artificial intelligence and iot makes the smart factory a reality

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Augsburg / Munich, December 1, 2020 – Part 4 of the digital press conference series “Join us for a coffee…” took a look into the future of manufacturing and showed how industrial companies can increase efficiency, product quality and revenue by linking artificial intelligence and the Internet of Things – this time with the expertise of KUKA, Device Insight and Sentian.When it comes to combining artificial intelligence and IoT, industry has so far clearly focused on predictive maintenance. “A mistake,” says Dr. Christian Liedtke, Head of Strategic Alliances at KUKA, with conviction. As the expert made clear at the beginning of the virtual discussion round: “If companies focus exclusively on predictive maintenance, they can only achieve better availability of a single machine, which shouldn’t fail anyway.” What end users are really interested in is generating more revenue. “To achieve this, however, all those involved in the process must work better together and individual processes must interlock seamlessly.”Smart Production with Artificial Intelligence of ThingsOne approach enabling such a holistic optimization of production is the combination of artificial intelligence and the Internet of Things to form an “Artificial Intelligence of Things” (AIoT), as created by KUKA subsidiary Device Insight and AI specialist Sentian. Here, the …

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Healthcare Artificial Intelligence Requires Data Access, Standards

healthcare artificial intelligence requires data access, standards

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By Jessica Kent

December 01, 2020 – Data access and industry standards may help leaders eliminate potential bias in healthcare artificial intelligence tools, as well as improve implementation of the technology, according to a report from the US Government Accountability Office (GAO).
GAO noted that artificial intelligence has many possible uses in healthcare, in both the clinical and administrative areas of the industry.
“Developers have demonstrated AI tools in a number of clinical applications, such as supporting clinical decision-making. These tools are at varying stages of maturity and adoption, but with the exception of population health management tools, many have not achieved widespread use,” the report stated.
“Use of AI tools for administrative applications could also affect patient care, including by reducing provider burden, and are also at varying stages of maturity and adoption, ranging from emerging to widespread.”
While the potential of AI has been well-documented and demonstrated by researchers and developers alike, the technology could also bring significant challenges to care delivery. Concerns over data access, bias, transparency, and integration have hindered the use of AI in healthcare, and will continue to do so until these issues are addressed.
READ MORE: Top Challenges of Applying Artificial Intelligence to Medical ImagingGAO …

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Translation Is Trickier For Business, And Artificial Intelligence Can Help

translation is trickier for business, and artificial intelligence can help

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Artificial Intelligence

Sergey Tarasov – stock.adobe.com

Artificial intelligence (AI) for translation is something Google and other companies have provided for individuals. It can be accessed on your phone. However, translation is still a much larger and complex issue than many people realize. The business community has many complex and unique needs that add to the challenge of accurate and reliable translation, and AI is showing increasing capability.
One of the keys to business translation is the simple reality that each business sector has its own terms, phrases, and even idioms. A generic translation system in the cloud, trained widely by crowd sourcing or other public methods, won’t have the accuracy required for business translation. In addition, the cloud itself is still a problem. Much of a businesses’ goals involve protecting intellectual property (IP). To do that, they want their information to stay on-premises, behind their firewalls.
Now throw in the complexity of privacy requirements such as the European Union’s GDPR and California’s CCPA. Increasingly, governments are setting rules for where citizens’ data must be kept and what may be shared. The location and anonymization of information also adds to the challenge of a company understanding …

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A.I. start-up Scale now worth more than $3.5 billion and breaking even

a.i. start-up scale now worth more than $3.5 billion and breaking even

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Scale AI CEO Alex Wang, left.Scale AIArtificial intelligence start-up Scale announced Tuesday that it has raised $155 million, led by Tiger Global. It’s now worth more than $3.5 billion.AI has been around for decades, but building an AI model that does what it’s supposed to do isn’t always fast or easy. Part of the drudgery is augmenting raw data so that a model can learn to make accurate predictions. Scale AI, founded in 2016, specializes in performing that work for its clients. Customers include Airbnb, General Motors, Nvidia, OpenAI, Pinterest and DoorDash.The AI market isn’t as large and easy to understand as the market for, say, social media. It amounts to an enabling technology, like database software, in the sense that AI can be embedded into existing products. Still, it’s a real, and growing, market.In revealing its plan to go public last month, C3.ai, a company looking to trade under the ticker symbol “AI,” said IDC estimates the enterprise artificial intelligence software market will be worth $44 billion in 2024, up from $18 billion in 2020. And software makers have continued to pick up AI tools through acquisition. ServiceNow, for example, announced the acquisition of burgeoning industry-oriented start-up Element AI on Monday.” …

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Glia and LitLingo Announce Strategic Partnership to Enhance Compliance Monitoring with Artificial Intelligence for Financial Services

glia and litlingo announce strategic partnership to enhance compliance monitoring with artificial intelligence for financial services

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LitLingo Technologies, an AI company providing proactive compliance and risk-mitigation technology and Glia, a leading provider of Digital Customer Se

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