Prof Ashutosh Sharma, secretary to the government (Ministry of Science and Technology) reportedly said that the government has initiated a project to digitally map the country with a resolution of 10 centimetres, using drones and technologies such as artificial intelligence and big data. The Survey of India, a part of the Department of Science and Technology, started on the project a few months ago and has chalked out a five-year plan to complete the project. The survey has started the exercise in Maharashtra, Karnataka and Haryana. "The project will be extended to other states but the respective government should show interest and also provide some financial support," Sharma said. The project, which is expected to cost INR 1000 Cr, is also mapping the entire Ganga basin from the beginning to the end, 25 km from either sides of the banks with an accuracy of 10 cm.

Truck drivers can put the brakes on their worst automation fears. Robots are not getting behind the wheel and stealing the jobs of long-haul drivers anytime soon, according to two government experts, offering a contrarian view to some of the biggest names in tech and a presidential candidate. In a study published in the Industrial and Labor Relations Review, Maury Gittleman, a research economist at the Bureau of Labor Statistics, and Kristen Monaco, an associate commissioner in the Office of Compensation and Working Conditions also at BLS, argue that there are three main reasons why the threat of automation, robots and AI to truck drivers is more fear-mongering than fearsome. "Looking at the data, we believe that, while the risk of job loss from automation is very real, the projections that often get touted are overstated," the two penned in Harvard Business Review Wednesday. The projections they're referring to are the elimination of some 2-3 million truck driving jobs, and one that recently got a boost by presidential candidate Andrew Yang, who retweeted Tuesday an article on trucking automation by Business Insider that perpetuated the projection in question.

The Guidelines put forward a set of 7 key requirements that AI systems should meet in order to be deemed trustworthy. The AI HLEG has also prepared a document which elaborates on a Definition of Artificial Intelligence used for the purpose of the Guidelines. The document also provides an assessment list that operationalises the key requirements and offers guidance to implement them in practice. Starting from the 26th of June, this assessment list undergoing a piloting process, to which all stakeholders are invited to test the assessment list and provide practical feedback on how it can be improved.

A viral app which classifies selfies using its in-built artificial intelligence has been spewing out vile and racist labels and enraging users. Many took to social media to condemn the racist and offensive software but makers of the app, at Princeton University, say causing offence was exactly the intention. It was intended to be deliberately provocative to draw attention to the in-built prejudice and discrimination in many forms of machine learning. However, many users, it seems, didn't fully get the idea of the art project and were outraged at what their images were labelled as. One MailOnline staffer who tried the app was grotesquely dubbed a'rape suspect' from an innocuous picture.

Laura Nolan is a modern hero. A former Google software engineer, Nolan resigned from her job last year after being asked to dramatically enhance the artificial intelligence used in US military drones. She is now calling for a ban on all forms of autonomous weapons on the basis that they might accidentally initiate a catastrophic global war. She said this as part of her role as a member of the Campaign to Stop Killer Robots. Now, listen, sometimes I'm able to kid myself about the goodness of people.

For some organizations, harnessing artificial intelligence's full potential begins tentatively with explorations of select enterprise opportunities and a few potential use cases. While testing the waters this way may deliver valuable insights, it likely won't be enough to make your company a market maker (rather than a fast follower). To become a true AI-fueled organization, a company may need to fundamentally rethink the way humans and machines interact within working environments. Executives should also consider deploying machine learning and other cognitive tools systematically across every core business process and enterprise operation to support data-driven decision-making. Likewise, AI could drive new offerings and business models. These are not minor steps, but as AI technologies standardize rapidly across industries, becoming an AI-fueled organization will likely be more than a strategy for success--it could be table stakes for survival. In his new book The AI Advantage, Deloitte Analytics senior adviser Thomas H. Davenport describes three stages in the journey that companies can take toward achieving full utilization of artificial intelligence.1 In the first stage, which Davenport calls assisted intelligence, companies harness large-scale data programs, the power of the cloud, and science-based approaches to make data-driven business decisions. Today, companies at the vanguard of the AI revolution are already working toward the next stage--augmented intelligence--in which machine learning (ML) capabilities layered on top of existing information management systems work to augment human analytical competencies. According to Davenport, in the coming years, more companies will progress toward autonomous intelligence, the third AI utilization stage, in which processes are digitized and automated to a degree whereby machines, bots, and systems can directly act upon intelligence derived from them. The journey from the assisted to augmented intelligence stages, and then on to fully autonomous intelligence, is part of a growing trend in which companies transform themselves into "AI-fueled organizations."

A new report from Data and Society raises doubts about automated solutions to deceptively altered videos, including machine learning-altered videos called deepfakes. Authors Britt Paris and Joan Donovan argue that deepfakes, while new, are part of a long history of media manipulation -- one that requires both a social and a technical fix. Relying on AI could actually make things worse by concentrating more data and power in the hands of private corporations. "The panic around deepfakes justifies quick technical solutions that don't address structural inequality," says Paris. "It's a massive project, but we need to find solutions that are social as well as political so people without power aren't left out of the equation."

Judge Napolitano's Chambers: Judge Andrew Napolitano breaks down why the Fourth Amendment is an intentional obstacle to government, an obstacle shown necessary by history to curtail tyrants. A trial in Great Britain has just concluded with potentially dangerous implications for personal freedom in the U.S. Great Britain is currently one of the most watched countries in the Western world – watched, that is, by its own police forces. In London alone, one study found that more than 420,000 surveillance cameras were present in public places in 2017. What do the cameras capture? Everything done and seen in public.

Tackling climate change is one of the greatest challenges facing humanity. Over the next decade, the technologies of the Fourth Industrial Revolution (4IR) – particularly 5G, the Internet of Things (IoT) and artificial intelligence (AI) – will provide essential tools for increasing efficiency in the economy and preparing for a post-fossil fuel society. Last year, the Intergovernmental Panel on Climate Change delivered its special report on the effects of global warming of 1.5 C and above. The report clearly lays out the difference between 1.5 C and 2 C warming and emphasizes the urgent need to avoid crossing tipping points in Earth's life support systems. To give us a chance to limit global warming to this level, global greenhouse gas emissions must peak by 2020 and then fall by half every decade, corresponding to 7% annual reductions as a global average.

Tackling climate change is one of the greatest challenges facing humanity. Over the next decade, the technologies of the Fourth Industrial Revolution (4IR) – particularly 5G, the Internet of Things (IoT) and artificial intelligence (AI) – will provide essential tools for increasing efficiency in the economy and preparing for a post-fossil fuel society. Last year, the Intergovernmental Panel on Climate Change delivered its special report on the effects of global warming of 1.5 C and above. The report clearly lays out the difference between 1.5 C and 2 C warming and emphasizes the urgent need to avoid crossing tipping points in Earth's life support systems. To give us a chance to limit global warming to this level, global greenhouse gas emissions must peak by 2020 and then fall by half every decade, corresponding to 7% annual reductions as a global average.