The ominous spread of coronavirus has bolstered the case for such advances as telemedicine; drones; artificial intelligence/machine learning; Big Data; and more flexible regulation of health care personnel and institutions. During a social conversation via FaceTime, her grandson, a physician, realized Mom was in the early stages of septic shock. A day's delay in treatment might have proven fatal. Similar tales emerge from professional telemedicine doctors. The advantages of telemedicine for, say, a migrant worker family on a remote ranch whose child becomes ill in the wee hours.

Fighting fake news has become a growing problem in the past few years, and one that begs for a solution involving artificial intelligence. Verifying the near-infinite amount of content being generated on news websites, video streaming services, blogs, social media, etc. is virtually impossible There has been a push to use machine learning in the moderation of online content, but those efforts have only had modest success in finding spam and removing adult content, and to a much lesser extent detecting hate speech. Fighting fake news is a much more complicated challenge. But they have limited reach. It would be unreasonable to expect current artificial intelligence technologies to fully automate the fight against fake news.

Science gets a lot of respect these days. Seven in 10 Americans think the benefits from science outweigh the harms, and nine in 10 think science and technology will create more opportunities for future generations. Scientists have made dramatic progress in understanding the universe and the mechanisms of biology, and advances in computation benefit all fields of science. On the other hand, Americans are surrounded by a rising tide of misinformation and fake science. Scientists are in almost complete agreement that people are the primary cause of global warming.

Google today made available Neural Tangents, an open source software library written in JAX, a system for high-performance machine learning research. It's intended to help build AI models of variable width simultaneously, which Google says could allow "unprecedented" insight into the models' behavior and "help … open the black box" of machine learning. As Google senior research scientist Samuel S. Schoenholz and research engineer Roman Novak explain in a blog post, one of the key insights enabling progress in AI research is that increasing the width of models results in more regular behavior and makes them easier to understand. By way of refresher, all neural network models contain neurons (mathematical functions) arranged in interconnected layers that transmit signals from input data and slowly adjust the synaptic strength (weights) of each connection. That's how they extract features and learn to make predictions.

Can the mind connect directly with artificial intelligence, robots and other minds through brain-computer interface (BCI) technologies to transcend our human limitations? For some, it is a necessity to our survival. Indeed, we would need to become cyborgs to be relevant in an artificial intelligence age. Brain-Computer Interface (BCI): devices that enable its users to interact with computers by mean of brain-activity only, this activity being generally measured by ElectroEncephaloGraphy (EEG). Electroencephalography (EEG): physiological method of choice to record the electrical activity generated by the brain via electrodes placed on the scalp surface. Functional magnetic resonance imaging (fMRI): measures brain activity by detecting changes associated with blood flow.

On January 6th, the US Centers for Disease Control and Prevention (CDC) notified the public that a flu-like outbreak was propagating in Wuhan City, in the Hubei Province of China. Subsequently, the World Health Organization (WHO) released a similar report on January 9th. While these responses may seem timely, they were slow when compared to an AI company called BlueDot. BlueDot released a report on December 31st, a full week before the CDC released similar information. Even more impressive, BlueDot predicted the Zika outbreak in Florida six months before the first case in 2016.

Artificial Intelligence is coming for education. It's not going to replace college faculty or teaching as we know it. Instead, AI is going to give faculty superpowers, extending their reach and expanding their time. A good teacher is a role model, a sage, able to become what the student needs. Teaching is too personal, too human, to be turned over to AI.

Artificial intelligence (AI) may play an increasingly essentialFootnote 1 role in criminal acts in the future. Criminal acts are defined here as any act (or omission) constituting an offence punishable under English criminal law,Footnote 2 without loss of generality to jurisdictions that similarly define crime. Evidence of "AI-Crime" (AIC) is provided by two (theoretical) research experiments. In the first one, two computational social scientists (Seymour and Tully 2016) used AI as an instrument to convince social media users to click on phishing links within mass-produced messages. Because each message was constructed using machine learning techniques applied to users' past behaviours and public profiles, the content was tailored to each individual, thus camouflaging the intention behind each message. If the potential victim had clicked on the phishing link and filled in the subsequent web-form, then (in real-world circumstances) a criminal would have obtained personal and private information that could be used for theft and fraud. AI-fuelled crime may also impact commerce. In the second experiment, three computer scientists (Martínez-Miranda et al. 2016) simulated a market and found that trading agents could learn and execute a "profitable" market manipulation campaign comprising a set of deceitful false-orders. These two experiments show that AI provides a feasible and fundamentally novel threat, in the form of AIC. The importance of AIC as a distinct phenomenon has not yet been acknowledged. The literature on AI's ethical and social implications focuses on regulating and controlling AI's civil uses, rather than considering its possible role in crime (Kerr 2004).

India, till not so long ago, could not churn out enough software programmers to keep up with demand. Although the demand still exists, it has become more complex and specialised. Thomas Frey, who advises companies on future trends, says every job will be a technology job going forward. "Emerging technology will provide a lot more opportunities, where every job will have a technology element to it. It will not be about humans versus artificial intelligence, but about working with them. People, however, need to be taught how to do this and enhance their skills," the famed futurist and celebrity speaker said.

In the late 1940s, pioneering computer genius Alan Turing proposed that a computer can be said to possess artificial intelligence if it can fool a human into thinking it is real by mimicking human responses under specific conditions. But what if human responses are greed, hatred and ruthlessly self-serving dominance over others? At the heart of that question is fear of technology, one which science fiction writer Isaac Asimov had already attempted to pacify in his 1942 Three Laws of Robotics, the first of which is that a robot may not allow a human being to come to harm. The question is, do we - the public - believe and trust that Artificial Intelligence will not be used, by either authorities or corporations, for their own benefit rather than ours? As writer and broadcaster Paul Mason tells CGTN, "The basic philosophical problem posed by artificial intelligence is this: On whose behalf are we developing this stuff? And what kind of society does it assume it's going to create?"