What will happen the day robots become smarter than humans? And are we ready for it? Sam Harris asks these two fundamental questions in this mindboggling ted talk. "Just think about how we relate to ants. We don't go out of our way to harm them. In fact, sometimes we take pains not to harm them. We step over them on the sidewalk. But whenever their presence seriously conflicts with one of our goals, let's say when constructing a building like this one, we annihilate them without a qualm. The concern is that we will one day build machines that, whether they're conscious or not, could treat us with similar disregard."

In 2016, a driverless Tesla car crashed killing the test driver. It was not the first vehicle to be involved in a fatal crash, but was the first of its kind and the tragedy opened a can of ethical dilemmas. With autonomous systems such as driverless vehicles there are two main grey areas: responsibility and ethics. Widely discussed at various forums is a'dilemma' where a driverless car must choose between killing pedestrians or passengers. Here, both responsibility and ethics are at play.

The International Conference for Automated Planning and Scheduling (ICAPS) hosts competitions every other year where computer systems try to find solutions to planning problems (such as scheduling flights). Researchers at MIT's Computer Science and Artificial Intelligence Laboratory are discovering processes to augment the technology by imbuing human intuition in them. This is another reminder of how far the developments in artificial intelligence have come along with their pace especially when posed against the economic progress and ethical understanding they demand. Automated planning and scheduling is an aspect of artificial intelligence that is concerned with constructing strategies for machines (intelligent agents, autonomous robots, etc.) based on factors like the observability, determinism and variables involved in the situation. ICAPS is a forum for researchers and practitioners to ensure progress in the field.

In the face of growing workplace automation, a number of commentators have painted a grim future for American workers. But most human capital leaders see a much brighter future-- one where automation helps revitalize U.S. manufacturing and increases the demand for skilled workers. According to global talent management firm Randstad Sourceright's survey of over 400 corporate HR leaders, automation and robotics are likely to have a positive impact on U.S. business growth in 2017, and will be one of the driving forces behind new hiring trends over the next several years. Regardless of how you feel about robots, the move toward automation and artificial intelligence cannot be stopped. About 15 percent of global HR leaders say that robotics completely transformed their businesses in 2016, and more than double (31%) expect automation to have an even greater influence in 2017.

Summary: Here's some background on how 3rd generation Spiking Neural Nets are progressing and news about a first commercial rollout. Recently we wrote about the development of AI and neural nets beyond the second generation Convolutional and Recurrent Neural Nets (CNNs / RNNs) which have come on so strong and dominate the current conversation about deep learning. Our research shows that the next generation of neural nets is most likely to be led by Spiking Neural Nets (SNNs) that are a return to the'strong' AI tradition and closely mimic actual brain function. Unlike CNNs that fire signals to every one of their deep layer connections every time, SNNs are modeled after the fact that in the brain neurons do not constantly communicate with one another. Rather they communicate in spikes of signals or more correctly short trains of spiking signals.

Banks around the world are being confronted with a record number of regulations, and those falling short of institutional obligations are paying a high price for their errors. In response, major financial institutions are grasping big data solutions in a bid to comply with often dense regulations and reduce regulatory breaches. "Considering many banks have grown organically, often via merger and acquisition, their data is not always consistent and well organised," according to James Arnett, a partner at business and technology consulting firm Capco. Mr Arnett believes that new tools can be created through the application of data analytics, which will transform banks compliance programmes from manual, non-scalable projects into lower-cost and automated processes. "There is a real opportunity for banking clients to embrace data analytics to answer the underlying theme of regulation strategically rather than to treat each regulation as a'tick-the-box' exercise," he says.

For developers of artificial intelligence, the goal does not get much more grandiose than successfully creating a machine capable of feeling "real emotion". And according to Moscow-based Professor Alexei Samsonovich, Russia is on the verge of doing just that. Samsonovich recently announced that he expects a breakthrough in the next several years which will see the rise of "free thinking" machines capable of understanding human emotions, as well as feeling their own emotions. The human brain is devastatingly complex and machines are currently not capable of expressing what we would consider to be "human emotion". The announcement hints at robots ultimately being able to understand narratives of thinking, as well as being developed enough to foster their own narratives.

Discussing the research in this field, Dr.McGuckin stated that "as we enter 2017 we have very stark and very real decisions to make – do we continually tolerate aggression and violence like this among our children – or will we practice what we preach to each other on social media about the injustices across the world? Do we want to accept that bullying is just a fact of life and growing up – or do we want to assert ourselves and say that we will each take a stand against one of the biggest impediments to a happy childhood and enjoyable educational experience? We are the adults – they are the children. We must mind and protect the education, health, and well-being of our children."

Children learn to speak, as well as recognize objects, people, and places, long before they learn to read or write. They can learn from hearing, seeing, and interacting without being given any instructions. So why shouldn't artificial intelligence systems be able to work the same way? That's the key insight driving a research project under way at MIT that takes a novel approach to speech and image recognition: Teaching a computer to successfully associate specific elements of images with corresponding sound files in order to identify imagery (say, a lighthouse in a photographic landscape) when someone in an audio clip says the word "lighthouse." Though in the very early stages of what could be a years-long process of research and development, the implications of the MIT project, led by PhD student David Harwath and senior research scientist Jim Glass, are substantial. Along with being able to automatically surface images based on corresponding audio clips and vice versa, the research opens a path to creating language-to-language translation without needing to go through the laborious steps of training AI systems on the correlation between two languages' words.

Artificial intelligence is learning to take on an increasing number of sophisticated tasks. Google Deepmind's AI is now able to imitate human speech, and just this past August IBM's Watson successfully diagnosed a rare case of leukemia. Rather than viewing these advances as threats to job security, we can look at them as opportunities for AI to fill in critical gaps in existing service providers, such as mental healthcare professionals. In the US alone, nearly eight percent of the population suffers from depression (that's about one in every 13 American adults), and yet about 45 percent of this population does not seek professional care due to the costs. There are many barriers to getting quality mental healthcare, from searching for a provider who's within your insurance network to screening multiple potential therapists in order to find someone you feel comfortable speaking with.