Litigation


AI wordsmith too dangerous to be released… has been released

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A text-generating artificial intelligence (AI) algorithm whose creators initially deemed too dangerous to release – given its ability to churn out fake news, spam and misinformation after feasting on a mere headline – has been unleashed. So far, so good, says the research lab, OpenAI. In a blog post last week, the lab said that the researchers have seen "no strong evidence of misuse" of the machine-learning language model, which is called GPT-2… at least, not yet. While we've seen some discussion around GPT-2's potential to augment high-volume/low-yield operations like spam and phishing, we haven't seen evidence of writing code, documentation, or instances of misuse […] We acknowledge that we cannot be aware of all threats, and that motivated actors can replicate language models without model release. Exactly how convincing is the output?


Microsoft and Amazon are at the center of an ACLU lawsuit on facial recognition

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The American Civil Liberties Union (ACLU) is pressing forward with a lawsuit involving the facial recognition software offered by Amazon and Microsoft to government clients. In a complaint filed in a Massachusetts federal court, the ACLU asked for a variety of different records from the government, including inquiries to companies, meetings about the piloting or testing of facial recognition, voice recognition, and gait recognition technology, requests for proposals, and licensing agreements. At the heart of the lawsuit are Amazon's Rekognition and Microsoft's Face API, both facial recognition products that are available for customers of the companies' cloud platforms. The ACLU has also asked for more details on the US government's use of voice recognition and gait recognition, which is the automated process of comparing images of the way a person walks in order to identify them. Police in Shanghai and Beijing are already using gait-analysis tools to identify people.


New Rugged Supercomputing Servers Enable AI, HPC and Sensor Fusion Applications at the Edge

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Forward-Looking Safe Harbor Statement This press release contains certain forward-looking statements, as that term is defined in the Private Securities Litigation Reform Act of 1995, including those relating to the products and services described herein and to fiscal 2020 business performance and beyond and the Company's plans for growth and improvement in profitability and cash flow. You can identify these statements by the use of the words "may," "will," "could," "should," "would," "plans," "expects," "anticipates," "continue," "estimate," "project," "intend," "likely," "forecast," "probable," "potential," and similar expressions. These forward-looking statements involve risks and uncertainties that could cause actual results to differ materially from those projected or anticipated. Such risks and uncertainties include, but are not limited to, continued funding of defense programs, the timing and amounts of such funding, general economic and business conditions, including unforeseen weakness in the Company's markets, effects of any U.S. Federal government shutdown or extended continuing resolution, effects of continued geopolitical unrest and regional conflicts, competition, changes in technology and methods of marketing, delays in completing engineering and manufacturing programs, changes in customer order patterns, changes in product mix, continued success in technological advances and delivering technological innovations, changes in, or in the U.S. Government's interpretation of, federal export control or procurement rules and regulations, market acceptance of the Company's products, shortages in components, production delays or unanticipated expenses due to performance quality issues with outsourced components, inability to fully realize the expected benefits from acquisitions and restructurings, or delays in realizing such benefits, challenges in integrating acquired businesses and achieving anticipated synergies, increases in interest rates, changes to cyber-security regulations and requirements, changes in tax rates or tax regulations, changes to interest rate swaps or other cash flow hedging arrangements, changes to generally accepted accounting principles, difficulties in retaining key employees and customers, unanticipated costs under fixed-price service and system integration engagements, and various other factors beyond our control. These risks and uncertainties also include such additional risk factors as are discussed in the Company's filings with the U.S. Securities and Exchange Commission, including its Annual Report on Form 10-K for the fiscal year ended June 30, 2019.


Taking the Risk Out of Machine Learning and AI - Workflow

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Machine learning and artificial intelligence are integral components of any modern organization's IT stack but these data-harvesting tools can have a dark side if appropriate risk management and planning protocols aren't in place. There's no denying the power and possibilities created by AI and machine learning. With this astounding power to build models designed to improve the efficiency and performance of everything from marketing and supply chain to sales and human resources comes considerable responsibility. A recent McKinsey report sheds some light on how companies in every industry should be wary of assuming that these relatively new and remarkably complex tools will always deliver the desired outcome as they're integrated with other applications and processes. These tools are just like every other tool that's ever existed: they're only as good as the people designing and using them.


Autonomous Legal Entities are Already Possible Under American Law

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If you ask a hundred lawyers whether a software system or a robot can buy a house or file a lawsuit, all of them would be likely to answer'no.' But because of the extreme flexibility of limited liability companies (LLCs) under US law, software and other artificial systems in fact can get basic legal personhood or at least a very close surrogate of it. That is, they can enter contracts, own property, sue, and be sued. The modern American LLC is an amazingly flexible structure. At its core, it is a legally recognized entity controlled however its organizers want it to be controlled.


Artificial Intelligence in the Courtroom: Are We Ready for This?

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Expensive, complicated, and bureaucratic legal processes constrain the judicial system. They make the wheels of justice grind excruciatingly slow. Case in point: Beijing, China, launched an online litigation service for "repetitive basic work". The high-tech facility features a female AI judge. The e-service offers a complete user experience with human facial expressions and bodily gestures and actions.


Is the Use of Artificial Intelligence in the Employee Application Process Worth the Risk? JD Supra

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As companies increasingly look to artificial intelligence ("AI") solutions to streamline their business practices, a new area has popped up: the use of artificial intelligence in analyzing videos of job interview applicants. For companies with tremendous volumes of job applicants, AI can be helpful in sorting through the applicant pool to narrow down the applicants who companies may want to bring in for in-person interviews or hire. As with most things technology, the laws are struggling to keep up with the rapid pace of innovation. However, Illinois continues to lead the nation in increasingly regulating the use of advancing technology. Though riddled with undefined terms and ambiguities, the Illinois Artificial Intelligence Video Interview Act (the "Act")--effective January 1, 2020--requires businesses who utilize AI to evaluate job applicants' video interviews to provide notice and obtain prior consent before doing so, and includes restrictions on video sharing and retention.


US Chamber of Commerce Mobilizes in Support of Facial Recognition Technology

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Clearly alarmed by shifting public perceptions about facial recognition technology and the potential for state and local governments to impose an outright ban on the use of such technology, tech vendors and other businesses offering facial recognition technology solutions are now mobilizing their forces. They are reaching out to U.S. congressional leadership, urging the House and Senate to re-think any initiatives to impose a "blanket moratorium" on the use of facial recognition technology. And, at the same time, they are rushing to the legal defense of big Silicon Valley tech firms such as Facebook, which is facing a major class action lawsuit in the state of Illinois over the wrongful use of biometric facial data. In one highly public move, the U.S. Chamber of Commerce wrote an open letter on facial recognition technology, which was addressed to the top political leaders in both the U.S. House of Representatives and U.S. Senate. The letter on facial recognition technology urges political leaders to consider all the positive uses of the technology.


AI-based Analytics: The key to business-led eDiscovery Casepoint

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Another common eDiscovery pitfall is the use of standard approaches for every case. Rather than dig in and discern data minimization and cost estimates for each case, many practitioners use generic formulas. Dubious tenets like "every stage of large cases goes to law firms" or "law firms always manage review for us" still rule the day. Teams automatically slap project planning formulas like 0 to 6 months for ECA, 6 to 12 months for full-blown eDiscovery and 12 to 24 months to finish eDiscovery, motions and trial preparations onto every eDiscovery project.


AI-based Analytics: The key to business-led eDiscovery Casepoint

#artificialintelligence

Another common eDiscovery pitfall is the use of standard approaches for every case. Rather than dig in and discern data minimization and cost estimates for each case, many practitioners use generic formulas. Dubious tenets like "every stage of large cases goes to law firms" or "law firms always manage review for us" still rule the day. Teams automatically slap project planning formulas like 0 to 6 months for ECA, 6 to 12 months for full-blown eDiscovery and 12 to 24 months to finish eDiscovery, motions and trial preparations onto every eDiscovery project.