Computers using artificial intelligence are discovering medicines, designing better golf clubs and creating video games. Patent offices around the world are grappling with the question of who -- if anyone -- owns innovations developed using AI. The answer may upend what's eligible for protection and who profits as AI transforms entire industries. "There are machines right now that are doing far more on their own than to help an engineer or a scientist or an inventor do their jobs," said Andrei Iancu, director of the U.S. Patent and Trademark Office. "We will get to a point where a court or legislature will say the human being is so disengaged, so many levels removed, that the actual human did not contribute to the inventive concept."

Cornerstone Research VANDY M. HOWELL, PhD Vandy Howell received her PhD in economics from MIT. She has expertise in industrial organization and labor economics. She is the head of Cornerstone Research's San Francisco office. Dr. Howell's practice area focus has been on antitrust, intellectual property, marketing, and breach of contract matters. She has experience across many industries, including cases involving technological and innovation markets, agriculture, and labor market issues.

A major California university has dropped plans to use facial recognition for the surveillance of the campus. The idea was to have the University of California Los Angeles use facial recognition as a way to gain access to buildings, to prove authenticity and deny entry to people with restricted access to the campus, matching their faces against a database. Advocacy group Fight for the Future says UCLA was the first major university exploring using facial recognition to monitor students. The group had tested facial recognition software and found that "dozens" of student-athletes and professors were incorrectly matched with photos from a mugshot database, "and the overwhelming majority of those misidentified were people of color." Why your face is the key: Do you really control how your face is being used?

The European Commission has said it intends to draw up new rules to protect citizens against misuses of artificial intelligence (AI) tech. It likened the current situation to "the Wild West" and said it would focus on "high-risk" cases. But some experts are disappointed that a white paper it published did not provide more details. A leaked draft had suggested a ban on facial recognition's use in public areas would be proposed. Industry Commissioner Thierry Breton suggested the new legislation would be comparable to the General Data Protection Regulation.

WASHINGTON/SEATTLE – Computers using artificial intelligence are discovering medicines, designing better golf clubs and creating video games. Patent offices around the world are grappling with the question of who -- if anyone -- owns innovations developed using AI. The answer may upend what's eligible for protection and who profits as AI transforms entire industries. "There are machines right now that are doing far more on their own than to help an engineer or a scientist or an inventor do their jobs," said Andrei Iancu, director of the U.S. Patent and Trademark Office. "We will get to a point where a court or legislature will say the human being is so disengaged, so many levels removed, that the actual human did not contribute to the inventive concept."

Based on our interactions and the results of this study, we expect to see organizations not only adopt AI--but scale it across their enterprises, by building/developing their own AI, or putting ready-made AI applications to work. For example, according to the survey, 40% of respondents currently deploying AI said they are developing proof-of-concepts for specific AI-based or AI-assisted projects, and 40% are using pre-built AI applications, such as chatbots and virtual agents. I see the excitement building with clients every day. Consider just a couple of recent examples. Legal software developer LegalMation has leveraged IBM Watson and our natural language processing technology to help attorneys automate some of the most mundane litigation tasks, speeding, for example, the written discovery process from multiple hours to a few minutes.

ORO VALLEY, AZ / ACCESSWIRE / February 18, 2020 / Tautachrome, Inc. (OTC PINK:TTCM) announces Google's TensorFlow artificial intelligence (AI) for image classification in ARknet release 1.3.4. ARknet will have the ability to classify incoming images utilizing TensorFlow, Google's artificial intelligence (AI) engine. The deployment of TensorFlow AI image recognition enables ARknet to crowdsource its userbase for machine learning purposes. Since ARknet can have segmented datasets, the ability to develop specialized machine learning models will also allow services to be provided to a wide range of business applications, connected devices, and enterprise services. TensorFlow is planned as the first of many AI frameworks that will be introduced into the ARknet platform in the future.

Artificial intelligence (AI) has the potential to help every sector of the economy. There is a challenge, though, in sectors that have fuzzier analysis and the potential to train with data that can continue human biases. A couple of years ago, I described the problem with bias in an article about machine learning (ML) applied to criminal recidivism. It's worth revisiting the sector as time have changed in how bias is addressed. One way is to look at sectors in the legal profession where bias is a much smaller factor.

In addition to their security properties, adversarial machine-learning attacks and defenses have political dimensions. They enable or foreclose certain options for both the subjects of the machine learning systems and for those who deploy them, creating risks for civil liberties and human rights. In this paper, we draw on insights from science and technology studies, anthropology, and human rights literature, to inform how defenses against adversarial attacks can be used to suppress dissent and limit attempts to investigate machine learning systems. To make this concrete, we use real-world examples of how attacks such as perturbation, model inversion, or membership inference can be used for socially desirable ends. Although the predictions of this analysis may seem dire, there is hope. Efforts to address human rights concerns in the commercial spyware industry provide guidance for similar measures to ensure ML systems serve democratic, not authoritarian ends.

Tesla and SpaceX CEO, Elon Musk, says that AI like the one his companies make should be better regulated. Musk's opinion on the dangers of letting AI proliferate unfettered was prompted by a report published in MIT Technology Review about changing company culture at OpenAI, a technology company that helps develop new AI. Elon Musk formerly helmed the company but left due to conflicts of interest. The report claims that OpenAI has shifted from its goal of equitably distributing AI technology to a more secretive, funding-driven company. 'OpenAI should be more open imo,' he tweeted.