The findings were discussed at the annual meeting of the American Association for the Advancement of Science in Seattle on Friday. Sex robots integrate artificial intelligence and traditional as well as novel technologies that may result in widely unknown and unpredictable risks. Scientists are concerned these sex robots (or love dolls) are being designed to look like children or even programmed to protest and simulate a rape scenario. According to tech expert Chris Riddell, stricter regulation of sex robots is needed immediately, "otherwise it's going to be the wild west." "Until now, we've only had human-to-human relationships. We're heading into an era where humans are having relationships with technology systems, and that's disturbing us," Riddell told 10 daily.

Fuel poverty affects between 50 and 125 million households in Europe and is a significant issue for both developed and developing countries globally. This means that fuel poor residents are unable to adequately warm their home and run the necessary energy services needed for lighting, cooking, hot water, and electrical appliances. The problem is complex but is typically caused by three factors; low income, high energy costs, and energy inefficient homes. In the United Kingdom (UK), 4 million families are currently living in fuel poverty. Those in series financial difficulty are either forced to self-disconnect or have their services terminated by energy providers. Fuel poverty contributed to 10,000 reported deaths in England in the winter of 2016-2107 due to homes being cold. While it is recognized by governments as a social, public health and environmental policy issue, the European Union (EU) has failed to provide a common definition of fuel poverty or a conventional set of indicators to measure it. This chapter discusses current fuel poverty strategies across the EU and proposes a new and foundational behavior measurement indicator designed to directly assess and monitor fuel poverty risks in households using smart meters, Consumer Access Device (CAD) data and machine learning. By detecting Activities of Daily Living (ADLS) through household appliance usage, it is possible to spot the early signs of financial difficulty and identify when support packages are required.

Artificial Intelligence (AI) is permeating across various sectors. This includes even the defense sector. With this, it is important to identify the implications of this rising technology in our current way of handling national security and what must be done in order to ensure that the nation remains safe if AI continues to assert domination. This matter is the central issue in the published book, The Department of Defense Posture for Artificial Intelligence, made by the RAND Corporation as mandated by the US Department of National Defense (DoD). If you want to read the book, you may download the free ebook.

Together with the UN Refugee Agency (UNHCR) 34 collaborators built several AI and machine learning based solutions to predict forced displacement, violent conflicts, and climate change in Somalia. In addition, an exploratory data analysis resulted in powerful insights regarding conflict types, areas, and reasons. The findings will help UNHCR to execute necessary support mechanism for people at need in a faster and more effective way. Millions of people in Somalia are forced to leave their current area of residence or community due to resource shortage and natural disasters like droughts and floods as well as violent conflicts. Our challenge partner, UNHCR, provides assistance and protection for those who are forcibly displaced inside of Somalia.

There are four main types of data breaches that advances in machine learning can help thwart. Although we hear a lot about major cybersecurity breaches in non-insurance organizations – Target, Experian, the IRS, etc. – there have been breaches in the insurance industry, too, albeit less publicized. Nationwide faces a $5 million fine from a breach back in 2012. Horizon Blue Cross Blue Shield is still the defendant in a class action suit over a 2013 breach that affected 800,000 of its insured. As hard as organizations try to secure their data and systems, hackers continue to become more sophisticated in their methods of breaching.

The Evaluation Committee has completed the evaluations for the AI Time Journal TOP 25 Artificial Intelligence Companies 2019. The objective of the AI Time Journal TOP 25 Artificial Intelligence Companies 2019 Initiative is to give recognition and showcase AI companies for their contribution in 2019 to applying Artificial Intelligence, Machine Learning and Deep Learning to solve significant and complex problems and improve people's lives in a multitude of domains including Healthcare, Education, Finance, Autonomous Vehicles and more. Note: companies that employ evaluation committee members have not been included in the evaluations. Alvin Foo: "The adoption of Artificial Intelligence, Deep Learning and Machine Learning to facilitate human decision-making will continue to accelerate. While it creates opportunities to automate, it will also open up new challenges for IT team to address the potential increase in cyberattack. The advancement of AI provides a scalable cybersecurity solution for companies to automate and protect their IT assets. The future of cybersecurity will be AI-powered!"

Once a quarter, VentureBeat publishes a special issue to take an in-depth look at trends of great importance. This week, we launched issue two, examining AI and security. Across a spectrum of stories, the VentureBeat editorial team took a close look at some of the most important ways AI and security are colliding today. It's a shift with high costs for individuals, businesses, cities, and critical infrastructure targets -- data breaches alone are expected to cost more than $5 trillion by 2024 -- and high stakes. Throughout the stories, you may find a theme that AI does not appear to be used much in cyberattacks today.

The White House released a budget proposal this week that at first glance, looks like a big win for the fields of artificial intelligence and machine learning. The budget for fiscal year 2021 (which begins in October) would ramp up spending for AI research at DARPA (the Pentagon's research arm) and the National Science Foundation by roughly $549 million. The budget request, which still needs to be approved by Congress, increases AI funding from $50 million to $249 million at DARPA, and from $500 million to $850 million at NSF. But while technologists applaud the increased investment in AI, the White House budget proposal is giving many in the science community pause. Overall, the budget proposes $142.2 billion in spending for research and development, a 9% cut from current levels.

The US military is developing a portable face-recognition device capable of identifying individuals from a kilometre away. The Advanced Tactical Facial Recognition at a Distance Technology project is being carried out for US Special Operations Command (SOCOM). It commenced in 2016, and a working prototype was demonstrated in December 2019, paving the way for a production version. SOCOM says the research is ongoing, but declined to comment further. Initially designed for hand-held use, the technology could also be used from drones.

The artificial intelligence community has a problem; their data sources are riddled with bias. "We live in an era of AI, and data requirements are increasing rapidly. AI & Machine Learning have the potential to shape industries like Healthcare, Mobility, Insurance, etc. Because of this, there is a significant rise in concerns about the ethical implications of AI and inherent bias, as these applications are used in life-threatening scenarios," said Sukesh Kumar Tedla, Unbiased founder and CEO. "We decided to build a transparent platform that ethically meets the data needs of the AI industry to address what we see as the AI industry's current shortcomings."