Climate change has emerged as the biggest threat to humanity, with devastating consequences such as extreme weather events, climate migration, and a sharp decline in biodiversity. While the brunt of climate action is shouldered by green parties and public activists like the young Greta Thunberg, in recent years many industries have stepped up innovation to try and do their bit. The informatics industry in particular has been flexing its R&D muscle to propose bleeding-edge solutions. A recent paper published by a group of high-profile AI experts and IT professionals explores the potential that can be found "at the nexus of climate change and machine learning". Headed by David Rolnick, a Postdoctoral Research Fellow at the University of Pennsylvania, the paper puts a spotlight on "high-impact opportunities for real-world change" present in such ML fields as artificial intelligence, computer vision, unsupervised learning, and more.

Climate change has emerged as the biggest threat to humanity, with devastating consequences such as extreme weather events, climate migration, and a sharp decline in biodiversity. While the brunt of climate action is shouldered by green parties and public activists like the young Greta Thunberg, in recent years many industries have stepped up innovation to try and do their bit. The informatics industry in particular has been flexing its R&D muscle to propose bleeding-edge solutions. A recent paper published by a group of high-profile AI experts and IT professionals explores the potential that can be found "at the nexus of climate change and machine learning". Headed by David Rolnick, a Postdoctoral Research Fellow at the University of Pennsylvania, the paper puts a spotlight on "high-impact opportunities for real-world change" present in such ML fields as artificial intelligence, computer vision, unsupervised learning, and more.

In any normal year, Cambridge Analytica would have been the biggest story. Facebook alone had a royal flush of scandals, including a huge data breach in September, becoming the subject of multiple class action lawsuits for discrimination, accusations of inciting ethnic cleansing in Myanmar, potential violations of the Fair Housing Act, and hosting masses of fake Russian accounts. Throughout the year, Facebook executives were frequently summoned to testify, with Mark Zuckerberg himself facing the US Senate in April and the European Parliament in May. News broke in March that Google was building AI systems for the Department of Defense's drone surveillance program, Project Maven. The news kicked off an unprecedented wave of tech worker organizing and dissent.

When researchers at University of Washington pulled together a clip of a faked speech by President Obama using video segments of the President's earlier speeches run through artificial intelligence, we watched with a queasy feeling. The combination wasn't perfect – we could still see some seams and stitches showing – but it was good enough to paint a vision of the future. Soon we would not be able to trust our own eyes and ears. Now the researchers at University of Washington (who clearly seem intent on ruining our society) have developed the next level of AI visual wizardry – fake people good enough to fool real people. As reported recently in Wired Magazine, the professors embarked on a Turing beauty contest, generating thousands of virtual faces that look like they are alive today, but aren't.

The issues of ethical development and deployment of applications using artificial intelligence (AI) technologies is rife with nuance and complexity. Because humans are diverse -- different genders, races, values and cultural norms -- AI algorithms and automated processes won't work with equal acceptance or effectiveness for everyone worldwide. What most people agree upon is that these technologies should be used to improve the human condition. There are many AI success stories with positive outcomes in fields from healthcare to education to transportation. But there have also been unexpected problems with several AI applications including facial recognition and unintended bias in numerous others.

WEST LAFAYETTE, Ind. – Increased adoption of cloud applications, such as Dropbox and Google Drive, by private users has increased concern about use of cloud information for cybercrimes such as child exploitation, illegal drug trafficking and illegal firearm transactions. Researchers at Purdue University have developed a cloud forensic model using machine learning to collect digital evidence related to illegal activities on cloud storage applications. "It is crucial to detect illegal cloud activities in motion," said Fahad Salamh, a PhD student in the Purdue Polytechnic Institute, who helped create the system. "Our technology identifies and analyzes in real time incidents related to these cybercrimes through transactions uploaded to cloud storage applications." Salamh worked on the technology with Marcus Rogers and Umit Karabiyik, professors in Polytechnic who specialize in computer and information technology.

Gartner released its 2020 technology trends last month with great – and appropriate – fanfare. Before I comment, we should all note just how volatile the technology world has become. So let me say at the outset that I appreciate Gartner's galvanizing a ton of trends into coherence. The robotic process automation (RPA) revolution is already in full swing. It's hard to find a company not looking at processes it can automate, and it's harder to find a company not keenly aware of technological leverage in the RPA mission.

A Supreme Court justice has added his voice to calls for the regulation of computer algorithms handling crucial decisions about people's lives. An'expert commission' could help ensure that automated decision making processes have'a capacity for mercy', Lord Sales (Philip Sales QC), said last night. Presenting the British and Irish Legal Information Institute's Sir Henry Brooke Lecture, Lord Sales said the growing role of algorithms and artificial intelligence poses significant legal problems, in particular around the fundamental concept of agency. Existing prejudices could be embedded in hidden rules that are impossible to challenge, he said. 'AI may get to the stage where it will understand the rules of equity and how to recognise hard cases, but we are not there yet.'

The Chancellor of the High Court has urged commercial lawyers to prepare for the disruptive impact of technology on the law, the legal system and legal profession before others "steal a march" on them. Sir Geoffrey Vos said the profession needed "to turn its incredible intellectual fire-power towards the development of the English common law, so that it can effectively tackle the problems thrown up by the use of big data, cryptoassets, on-chain smart contracts, and artificial intelligence". Expressing confidence that the English common law could adapt to these challenges, he added: "My plea is that you do not leave it too late, because there are many other brilliant lawyers in other jurisdictions who are motivated to steal a march on their common law colleagues in the UK." Giving the Commercial Bar Association's annual lecture this week, Sir Geoffrey warned commercial lawyers that it was too late to hope to retire before any of this became a reality. "It is already reality," he said. Rather, he encouraged lawyers "to think imaginatively about the world in which the commercial legal services of the future will be required".

Internet censorship by authoritarian governments prohibits free and open access to information for millions of people around the world. Attempts to evade such censorship have turned into a continually escalating race to keep up with ever-changing, increasingly sophisticated internet censorship. Censoring regimes have had the advantage in that race, because researchers must manually search for ways to circumvent censorship, a process that takes considerable time. New work led by University of Maryland computer scientists could shift the balance of the censorship race. The researchers developed a tool called Geneva (short for Genetic Evasion), which automatically learns how to circumvent censorship.