There are two distinct types of AI. One is reactive machines, which have no memory and cannot use past experiences to inform future decisions. The other is a self-aware AI, which can understand its current state and make inferences about its environment. When choosing an AI system, organizations should consider factors such as its robustness, the likelihood of its errors, and the consequences of its consequences. These factors can help minimize the negative impacts of AI. But it is also important to recognize that the positive consequences of an AI system are possible.

In the intensifying race for global competitiveness in artificial intelligence (AI), the United States, China and the European Union are vying to be the home of what could be the most important technological revolution of our lifetimes. AI governance proposals are also developing rapidly, with the EU proposing an aggressive regulatory approach to add to its already-onerous regulatory regime. It would be imprudent for the U.S. to adopt Europe's more top-down regulatory model, however, which already decimated digital technology innovation in the past and now will do the same for AI. The key to competitive advantage in AI will be openness to entrepreneurialism, investment and talent, plus a flexible governance framework to address risks. The International Economyjournal recently asked 11 experts from Europe and the U.S. where the EU currently stood in global tech competition.

More and more people have started to pay attention to artificial intelligence (AI) in recent years. According to Edelman's special report on tech within its annual Trust Barometer report, people around the world have shown concern that AI and robots could replace human workers. As a result, fewer people are willing to share their personal data, as their trust in the media, online social platforms and search engines seems to have declined. Some say the chasm between trust and technology has formed for good reasons: For most of AI's existence, there hasn't been much regulation around it. At times, the rules may seem a bit loose and opaque for just how world-changing it could be.

The maturity of artificial intelligence (AI) was evident this year, as the conversations in the industry shifted focus from deployment and innovation to ethics and legislation of algorithms. Building better data foundations to make the most of AI The UK government's national artificial intelligence strategy relies on businesses putting in place the foundations for better use of data – EY research highlights the challenges ahead. Making machine learning operational As artificial intelligence matures, IT departments will need to take control of change management and governance of data models. Self-regulation of AI is not an option The House of Lords Communications and Digital Committee recently took evidence from two experts, who were asked to share their thoughts on regulating artificial intelligence. Europe's proposed AI regulation falls short on protecting rights The European Commission's proposal for artificial intelligence regulation focuses on creating a risk-based, market-led approach replete with self-assessments, transparency procedures and technical standards, but critics warn it falls short.

More and more organizations are beginning to use or expand their use of artificial intelligence (AI) tools and services in the workplace. Despite AI's proven potential for enhancing efficiency and decision-making, it has raised a host of issues in the workplace which, in turn, have prompted an array of federal and state regulatory efforts that are likely to increase in the near future. Artificial intelligence, defined very simply, involves machines performing tasks in a way that is intelligent. The AI field involves a number of subfields or forms of AI that solve complex problems associated with human intelligence--for example, machine learning (computers using data to make predictions), natural-language processing (computers processing and understanding a natural human language like English), and computer vision or image recognition (computers processing, identifying, and categorizing images based on their content). One area where AI is becoming increasingly prevalent is in talent acquisition and recruiting.

You submitted your questions about artificial intelligence and robotics, and we put them – and some of our own – to The Conversation's experts. It is 100% plausible that we'll have human-like artificial intelligence. I say this even though the human brain is the most complex system in the universe that we know of. But there are also no physical laws we know of that would prevent us reproducing or exceeding its capabilities. Popular AI from Issac Asimov to Steven Spielberg is plausible. What the question doesn't address is: when will it be plausible? Most AI researchers (including me) see little or no evidence of it coming anytime soon. Progress on the major AI challenges is slow, if real.