And what does the future hold for eNASCAR and the sport's overall sim racing ambitions? Officials like Clark and Myers suggest that a host of options are on the table: increased prize pools, additional TV coverage and more involvement from real-life, professional NASCAR drivers. Parker Kligerman, part owner of eNASCAR team Burton Kligerman eSports and a racing analyst for NBC Sports Network, said he's pushing his drivers to be more visible, streaming more frequently and creating digital content. "We have the opportunity to do things real-world racing can't," Kligerman said. "I continue to believe that there's huge potential here, and we've only just hit the tip of the iceberg."

Describe why we--the "social good sector"--should care about and help shape the role AI plays in our society

Artificial Intelligence (AI) as an idea seems to have caught the imagination of both industry and academia alike. Although AI-related academic research has been in place since the late nineties but it is recently that products and services inspired by AI have emerged out of labs into our daily routine activities. Whether it is the buzz around autonomic vehicles, drones, speech recognition, various voice response systems like Alexa and Google assistant, every single one of these products has some form of AI at its core. Undoubtedly, ever-increasing processing speeds and storage capacities along with possibilities of machine to machine (M2M) communication have let the cat out of the bag. Today we produce more data in a single day then possibly we did in the entire year in the eighties.

Earlier this month Google quietly unveiled an incredibly unique opportunity for seasoned developers to explore pilot experiments based on some of Google's frontier AI research, aptly called "AI Workshop." Google already makes a wealth of AI research available on platforms from GitHub to its own AI Hub, complete with a searchable library of ready-to-use code examples, demonstrations and even wrappers around production systems. What makes AI Workshop so different from these other mediums is that it presents an early glimpse at selections from Google's bleeding edge enterprise AI research that might become future product offerings, allowing the research and developer community to provide feedback that can help influence those innovations, granting a rare opportunity to help shape the future of AI in the enterprise. The rise of deep learning has represented a unique era of collaboration between the commercial and research sectors. Many of the underlying toolkits, workflows, algorithms and even research models have all been released under open source licenses, with companies, academics and citizen researchers collaborating together to create innovative new applications and to improve the underlying infrastructure powering the modern deep learning revolution.

Potential applications of machine learning are very broad indeed. But, although AI conjures up images of robot butlers and promises big changes to customer experience, marketing teams who are already making use of AI-powered tech are doing so to sell. Machine learning refers to statistical approaches to train models which incrementally improve the output of a system. This sort of predictive modelling is used to increase the likelihood that a customer will take a particular action – this could be opening an email, clicking an ad or viewing a recommended product. Marketers are therefore mostly using machine learning in their push for personalisation – fuelled by a desire to improve sales.

According to several outlets briefed over the weekend on the White House's plans, President Trump will today sign an executive order establishing a program -- the American AI Initiative -- that'll task federal agencies with devoting more resources to artificial intelligence (AI) research, training, and promotion. It comes after President Trump promised "investments in the cutting-edge industries of the future" during his State of the Union speech last week, and after companies like Amazon, Microsoft, and Google called for guidelines governing the use and development of AI technologies such as facial recognition. "AI is something that touches every aspect of people's lives," a White House official told Reuters. "What this initiative attempts to do is to bring all those together under one umbrella and show the promise of this technology for the American people." There isn't any funding attached to the executive order, which follows the Trump Administration's AI summit on the role of AI in May 2018.

A report from the House of Lords recommends that ethics be a key focus in the future of artificial intelligence, saying it should be developed "for the common good and benefit of humanity" and never given "autonomous power to hurt, destroy or deceive" people. AI in the UK: Ready, Willing and Able highlights the UK's opportunity to become a world-leading nation in the development of artificial intelligence but insists that clear-cut ethics must be established around the development and deployment of such technology. The report claims that, as a world leader, the UK can "help shape the ethical development of artificial intelligence" on a global scale; thus helping to set the fundamental guidelines for all future AI development. The report also addresses other key issues surrounding the development of AI – the potential effect on workers and data privacy rights. For some time now the issue of job losses due to the introduction of AI and robotics has been discussed, with conflicting claims of job losses and exaggeration of figures.

The "technology of the future" is constantly changing. Remember when Google Glass was the future and venture capitalists launched huge funds dedicated to financial Glass app developers? Remember when chat bots were the future and every tech company on the planet burned time and money developing Facebook Messenger bots? Yeah, most "technologies of the future" end up being little more than silly trends that vanish almost as quickly as they arrived. This time around, however, things feel like the might be a bit different when it comes to the latest "technology of the future."

At times, progress occurs so quickly that it's difficult to separate science fiction from real life. Just five decades ago, computers were massive, unwieldy machines running on punch cards and primitive circuits. Today, a single smartphone has more processing power than the computer used on the Apollo missions. AI has benefited greatly from this explosion in computing power and capability. Today, highly complex deep learning algorithms, patterned on the structure of the human brain, can master Go, trade stocks, and even write Harry Potter novels (though admittedly not very good ones). Given this versatility, some fear that deep learning AIs will reshape our economy by force, rendering hundreds, if not thousands, of occupations obsolete.

The New York City Council met early in December to pass a law on algorithmic decision-making transparency that could have real significance for cities and states in the rest of the nation. With the passage of an algorithmic accountability bill, the city gains a task force that will monitor the fairness and validity of algorithms used by municipal agencies. The public is in the dark about AI (artificial intelligence) and how it is deployed and used, said Bronx City Council representative James Vacca. "I strongly believe the public has a right to know when decisions are made using algorithms," said Vacca during the December City Council Technology Committee meeting. New York uses algorithms to determine if a lower bail will be assigned to an indigent defendant, where firehouses are established, student placement for public schools, accessing teacher performance, identifying Medicaid fraud and to determine where crime will happen next.