Shawn Hudson filed the negligence lawsuit in state court in Orlando, Florida, on Tuesday, claiming Tesla made false statements about the autopilot safety on his vehicle. He says his Model S failed to detect a stalled car on a highway, leading to a collision that left him with permanent injuries.

Google says the competition will look at ways in dealing with some of the most grappling social issues such as sex trafficking, environmental issues etc. Google has said it is earmarking a sum of $25 million for the development of new AI applications that would seek to address the ills of the present society and help improve people's lives in the process. Named the AI Global Impact Challenge, the contest is already open and will accept applications till Jan. 22, 2019. After that, the winners will be declared in the spring of 2019. Google said the contest will target NGOs, social research organizations and social enterprises who might already have a track record of working on the social sector.

Google has pledged $25 million to launch projects that apply Artificial Intelligence (AI) technology to find solutions for various societal problems. Google said the grant will be used to fund the "AI Impact Challenge" contest, which is part of its "AI for Social Good" programme dedicated to "addressing some of society's biggest unsolved challenges". "We'll help selected organisations bring their proposals to life with coaching from Google's AI experts, Google.org Grantees will also join a specialised "Launchpad Accelerator" programme. The California-based tech giant is making a "global call for non-profits, academics, and social enterprises from around the world to submit proposals on how they could use AI to help address some of the world's greatest social, humanitarian and environmental problems."

Researchers at the State University of New York in Korea have recently explored new ways to detect both machine and human-created fake images of faces. In their paper, published in ACM Digital Library, the researchers used ensemble methods to detect images created by generative adversarial networks (GANs) and employed pre-processing techniques to improve the detection of images created by humans using Photoshop. Over the past few years, significant advancements in image processing and machine learning have enabled the generation of fake, yet highly realistic, images. However, these images could also be used to create fake identities, make fake news more convincing, bypass image detection algorithms, or fool image recognition tools. "Fake face images have been a topic of research for quite some time now, but studies have mainly focused on photos made by humans, using Photoshop tools," Shahroz Tariq, one of the researchers who carried out the study told Tech Xplore.

You know when you try to go online at a Starbucks or on an airplane, first you get a little popup that asks you to accept some terms before you can get to the internet? That popup window exists in a sort of netherworld between actual internet connection and being offline–you pick it up via Wi-Fi, but until you click a box, you're not actually online. A team of five developers realized in that gray area was potentially a huge opportunity to save lives. It's an intractable problem during natural disasters: telecommunications networks and power grids are often damaged or overwhelmed; without them, first responders struggle to help survivors, coordinate evacuations, and even count the dead. Project Owl proposes an elegant solution: an AI-powered disaster coordination platform paired with a robust communication network that can reach people even when other connections are down.

Combating bias and creating more inclusive AI is unlikely to succeed unless developers include those people who have been historically excluded or ignored. Advances in automation, machine learning and artificial intelligence (AI) mean we're on the threshold of discoveries that could change human society irreversibly – for better or worse. From AI that sorts CVs and shortlists job applicants, to facial recognition algorithms, these technologies are bringing new efficiencies and reducing errors in both public and private sector decision making. But, increasingly, many of us are becoming aware of the dangers of bias and discrimination inherent in these technologies. A recent MIT study measuring how the technology works on people of different races and gender found that facial recognition AI was less accurate when classifying the faces of people with darker skin.

A natural reaction today may be to chalk up the sale of a smudgy-looking portrait as the latest sign that AI, no longer satisfied with taking jobs, is now moving on to creating artwork and general AI is here and don't forget Skynet, etc. But leave it to Artnet, an art market website, to provide a clear description of Generative Adversarial Networks, an AI system of algorithms and two neural networks used to generate photorealistic images. It also put artificial intelligence's potential in context for artists and business practitioners alike. "We would do better to stop asking where the boundary line lies between human artists' agency and that of AI toolsets, and instead start asking whether human artists are using AI to plumb greater conceptual and aesthetic depths than researchers or coders," Artnet writes. In art and in business, everyone would be better served if AI was treated as a tool, with benefits and risks noted.

Human intelligence precedes civilization; artificial and superhuman intelligences, however, will redefine it. Current research in artificial general intelligence (AGI) and intelligence enhancement (IE) seek to remove human error from their most ambitious technological quests. On the one hand, using evolutionary algorithms, AGI aims to develop a fully automated, increasingly independent, gradually cognitive, and eventually conscious artificial being. On the other hand, using neurotechnology, IE intends to create a super-intelligent and inherently different human being capable to counteract the inexorable ascension of machines in the next few years. But what is the limit of such scientific enterprises?

On giant screens in the European parliament building in Brussels last week, the face of Mark Zuckerberg looked down on the world's data protection and privacy commissioners assembled there for their annual conference. What he said was cautious and rather bland, but the imagery was potent: a young Big Brother issuing a tailored message to those who administer the laws of many lands. Zuckerberg did not take questions – a Facebook executive in the chamber did, after Zuckerberg faded from the screens into the green and sunny background of his distant locale. An actual dialogue with the controller of Facebook might have been illuminating. For example, does Facebook anticipate, as others speculate, that the internet will split into two, or three – the US internet, the China internet and the EU internet?

In my first post in this series, I wrote that one definition of artificial intelligence (AI) is a machine that thinks. Several people with technical backgrounds in the AI field reached out to me after reading that post. One comment I received that I found striking is that AI is neither A nor I. Instead, it is just computer code. Nothing is thinking; a computer is just following directions. And AI is just inputs to outputs for a goal.