In my first post in this series, I wrote that one definition of artificial intelligence (AI) is a machine that thinks. Several people with technical backgrounds in the AI field reached out to me after reading that post. One comment I received that I found striking is that AI is neither A nor I. Instead, it is just computer code. Nothing is thinking; a computer is just following directions. And AI is just inputs to outputs for a goal.

The AI humanoid Sophia has been granted the world's first robot visa as she embarks on a world tour on behalf of her Hong Kongese creators. She was issued the electronic visa upon her arrival at Azerbaijan's Baku International Airport shortly before meeting the Caucasus nation's president, Ilham Aliyev. The AI celebrity is in Azerbaijan for a tech conference, where she is a keynote speaker. Sophia first emerged two years ago as a super-intelligent human-like head with a realistic face that was able to blink, look from side to side and talk. But the robot's eloquent use of language and intricate facial expressions have stirred suspicion among AI experts, who say Sophia is merely a'sophisticated puppet'.

Humans have a '50/50' chance of finding life on the red planet within three years, according to an astrobiologist working on the next Mars rover. The ExoMars rover is scheduled to land on the red planet in August 2021 and will be part of a mission to investigate how the planet evolved and whether it has conditions for life. Scientists working on the project believe plans to excavate below the surface of the red planet greatly increase their chance of finding life. Humans have a '50/50' chance of finding life on the red planet within three years, according to an astrobiologist working on the next Mars rover (artist's impression) Due to launch in 2020, the ExoMars rover will be the first of its kind to travel across the martian surface and drill-down to determine if evidence of life is buried underground. Dr Susanne Schwenzer, the astrobiologist on the ExoMars rover told the Daily Telegraph that the'chances are just about 50/50'.

The rise of robots in the workplace will trigger an'apocalypse' unless it is managed properly, an economics professor has warned. Johannes Moenius from the University of Redlands says mechanisation presents the most serious danger to unskilled workers employed in logistics and the service industry. His comments follow a study from last year that found as many as 44 per cent of work hours could be done by machines by 2030. The mechanisation of the workplace will trigger an'apocalypse' unless it is managed properly, an economics professor has warned (stock image) According to an in-depth feature by Melanie Mason in the Los Angeles Times, automation is shaping the job market like never before. If we don't do anything, then it will turn into an apocalypse', Professor Moenius said.

That's one of the surprising -- and unsettling -- questions Israeli historian Yuval Noah Harari asks in his much-quoted new book, 21 Lessons for the 21st Century. Whereas 20th-century technology favored democracies as they were able to distribute power to make decisions among many people and institutions, according to Harari, artificial intelligence (AI) might make centralized systems that concentrate all information and power far more efficient as machine learning works better with more information to analyze. "If you disregard all privacy concerns and concentrate all the information relating to a billion people in one database," Harari writes, "you'll wind up with much better algorithms than if you respect individual privacy and have in your database only partial information on a million people." The rise of AI swinging the pendulum from democracies toward authoritarian regimes is just one of the feared adverse impacts of technologies: Others include job displacement, concentration of power, diminishing privacy, rising income inequality and losing our "free will." Yet most people have little or no knowledge about how AI, blockchain, the Internet of Things or genetic engineering could affect their lives.

If the experts are to be believed, AI will develop its own consciousness. A closer look suggests they got it backwards – human consciousness will be embedded in AI. What kind of consciousness will Chinese AI reveal? Philosophers have traditionally debated consciousness along two lines: Plato, Descartes, and modern neuroscience claim that the brain produces consciousness and that it is the result of biological evolution. On the other hand, Indian philosophy, as well as Aristotle and some of those working in quantum physics, argue that consciousness is intrinsic to the universe and that it preceded life. The closest Chinese equivalent to the Western word consciousness is xin, literally "heart-mind." In the Chinese view, xin does not develop naturally but must be cultivated. Xin is rooted in Confucianism, which means it has an ethical connotation. A closer look at xin may shed light on how the Chinese will develop AI, and whether it leads to artificial consciousness.

On giant screens in the European parliament building in Brussels last week, the face of Mark Zuckerberg looked down on the world's data protection and privacy commissioners assembled there for their annual conference. What he said was cautious and rather bland, but the imagery was potent: a young Big Brother issuing a tailored message to those who administer the laws of many lands. Zuckerberg did not take questions – a Facebook executive in the chamber did, after Zuckerberg faded from the screens into the green and sunny background of his distant locale. An actual dialogue with the controller of Facebook might have been illuminating. For example, does Facebook anticipate, as others speculate, that the internet will split into two, or three – the US internet, the China internet and the EU internet?

In 2017, United Nations Secretary-General António Guterres noted the difficult challenge that policymakers, particularly those in the Global South face with respect to AI. He said that "The implications for development are enormous. Developing countries can gain from the benefits of AI, but they also face the highest risk of being left behind." For example, in Nigeria doctors are using AI to help reduce the incidence of birth asphyxia, a leading cause of under-five death in Africa, and yet at the same time there are real concerns about AI's impact on rising unemployment and the influence that Google, China, and others are exerting across the Global South. AI technologies are raising complex social, political, technological, economic, and ethical questions.

Vladimir Putin spoke with students about science in an open lesson on September 1, the start of the school year in Russia. He told them that "the future belongs to artificial intelligence," and whoever masters it first will rule the world. "Artificial intelligence is the future, not only for Russia, but for all humankind. It comes with colossal opportunities, but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world," Russian President Vladimir Putin said.

In a given scenario, simultaneously and accurately predicting every possible interaction of traffic participants is an important capability for autonomous vehicles. The majority of current researches focused on the prediction of an single entity without incorporating the environment information. Although some approaches aimed to predict multiple vehicles, they either predicted each vehicle independently with no considerations on possible interaction with surrounding entities or generated discretized joint motions which cannot be directly used in decision making and motion planning for autonomous vehicle. In this paper, we present a probabilistic framework that is able to jointly predict continuous motions for multiple interacting road participants under any driving scenarios and is capable of forecasting the duration of each interaction, which can enhance the prediction performance and efficiency. The proposed traffic scene prediction framework contains two hierarchical modules: the upper module and the lower module. The upper module forecasts the intention of the predicted vehicle, while the lower module predicts motions for interacting scene entities. An exemplar real-world scenario is used to implement and examine the proposed framework.