Elon Musk has built cars and rockets. OpenAI - the artificial-intelligence research nonprofit cochaired by Tesla Motors CEO Musk and Y Combinator President Sam Altman - wants to build a robot for your home. Building a robot, OpenAI's leadership explains in a blog entry on Monday, is a good way to test and refine a machine's ability to learn how to perform common tasks. By "build," the company means taking a current off-the-shelf robot and customizing it to do housework. "More generally, robotics is a good test bed for many challenges in AI," reads the blog entry.

Google has released a paper on AI safety in collaboration with researchers from Stanford University, University of California, Berkeley and OpenAI.

Musk's warnings should be heeded. OpenAI is his less dramatic way of confronting this threat. By making everything "open," humanity has a greater opportunity to control the growth and direction of AI. But NPQ readers might want to ask if anyone other than tech leaders should be making these decisions. Silicon Valley is at the center of innovation, but ethics and many other concerns are forced to the forefront with the advent of AI. Should there be government or United Nations oversight?

That's just one of "five practical research problems" proposed by scientists at Google, OpenAI, Stanford and Berkeley in a paper called "Concrete Problems in AI Safety" (pdf). Others included "safe exploration" issues, or how to stop a curious cleaning robot from sticking a wet mop in an electrical socket, and "avoiding negative side effects" such as a robot breaking granny's vase when cleaning in a rush. The problems may seem a bit silly, when compared to an AI-induced doomsday, but Google researcher Chris Olah wrote, "These are all forward thinking, long-term research questions – minor issues today, but important to address for future systems." A particularly interesting portion of the paper was devoted to avoiding reward hacking, or how to stop AI from gaming its reward function. "Imagine that an agent discovers a buffer overflow in its reward function: it may then use this to get extremely high reward in an unintended way."

There's been much talk about how artificial intelligence will benefit society, but what about the potential impacts that AI has when the system is poorly designed and creates problems? This is a question several researchers and OpenAI, a non-profit artificial intelligence research company, tackled in a recent paper. The paper was written by researchers from Google Brain, Stanford University and the University of California, Berkeley, as well as John Schulman, research scientist at OpenAI. It's titled Concrete Problems in AI Safety, and it looks at research problems around ensuring that modern machine learning systems operate as intended. Researchers have started to focus on safety research in the machine learning community, including a recent paper from DeepMind and the Future of Humanity Institute that looked at how to make sure that human interventions during the learning process would not induce a bias toward undesirable behaviors in machine learning robots. But, according to a blog post by OpenAI, many machine learning researchers are wondering just how much safety research can be done today.

DeepMind, the artificial intelligence research lab acquired by Google for a reported 400 million in 2014, has called on the UK government to consider funding degree courses that focus on machine learning, which is a subfield of AI. The company -- cofounded by Demis Hassabis, Shane Legg and Mustafa Suleyman in 2011 -- said the government needs to support the next generation of machine learning experts if it wants the UK to cement its position as a world leader in AI. Writing in evidence submitted to a parliamentary inquiry into robotics and AI last month, DeepMind said: "The government should consider funding for machine learning masters and PhD programmes at British universities, to encourage more research in the field and nurture the next generation of scientists who will help preserve the UK's preeminent position." The company added: "This funding could also include direct support for modules within programmes that train machine learning researchers in the ethics of data science and increasingly autonomous decision-making, to ensure that the pursuit of beneficial outcomes is embedded in the science of machine learning at every level." Machine learning masters degrees and PhDs can cost individuals upwards of 10,000 at the top universities.

Google Research cooperated with OpenAI, Stanford University, and the University of California to publish a research paper highlighting the five main problems with machine learning systems that can lead to accidents. The problems, although minor now, can escalate to concerning levels during artificial intelligence development and operation.

Google has released technical paper on AI safety produced in collaboration with researchers from Stanford University, University of California, Berkeley and OpenAI.

In a Monday blog post, the leadership of artificial intelligence (AI) research company OpenAI said that the group wants to modify'off-the-shelf' robots so they can perform common household tasks. "We're working to enable a physical robot (off-the-shelf; not manufactured by OpenAI) to perform basic housework," the group said in a blog post authored by Research Director Ilya Sutskever, Chief Technology Officer Greg Brockman, Sam Altman and Elon Musk. This futuristic target is second only to the primary goal laid out in the organization's blog post, which is to develop AI that could learn to improve its ability over time. Meeting such a goal would provide an underpinning for the perhaps more glamorous concept of robots that can clean your home, but the post goes onto say that domestic robots themselves would provide a solid foundation for approaching other problems in AI. "There are existing techniques for specific tasks, but we believe that learning algorithms can eventually be made reliable enough to create a general-purpose robot. More generally, robotics is a good testbed for many challenges in AI," the blog post reads.

There's been much talk about how artificial intelligence will benefit society, but what about the potential impacts that AI has when the system is poorly designed and creates problems? This is a question several researchers and OpenAI, a non-profit artificial intelligence research company, tackled in a recent paper. The paper was written by researchers from Google Brain, Stanford University and the University of California, Berkeley, as well as John Schulman, research scientist at OpenAI. It's titled Concrete Problems in AI Safety, and it looks at research problems around ensuring that modern machine learning systems operate as intended. Researchers have started to focus on safety research in the machine learning community, including a recent paper from DeepMind and the Future of Humanity Institute that looked at how to make sure that human interventions during the learning process would not induce a bias toward undesirable behaviors in machine learning robots.