Artificial intelligence is probably the greatest transformative technology of our generation. Experts predict that the value of the AI market will reach over $266 billion by 2027, representing an 880% increase compared to 2019. As exciting as AI innovation might be from a practical viewpoint, there are also some issues to consider when it comes to ethics in AI. AI is a technology that aims to enhance and unlock human potential. It is here to augment or replicate problem-solving and decision-making capabilities that require a certain level of "human intelligence".

AI is a complex field and there is both hype and hysteria around the subject. To help you explain it clearly to your audience, two community coordinators from the JournalismAI initiative asked four AI experts and tech reporters from across the world for their best tips. Karen Hao, senior AI editor at the MIT Technology Review, started covering AI spending lots of time on YouTube and learning the basics like: what is an algorithm? What are neural networks and how are they trained? What are the key milestones in the history of AI?

Artificial intelligence has been front and center in recent months. The global pandemic has pushed governments and private companies worldwide to propose AI solutions for everything from analyzing cough sounds to deploying disinfecting robots in hospitals. These efforts are part of a wider trend that has been picking up momentum: the deployment of projects by companies, governments, universities, and research institutes aiming to use AI for societal good. The goal of most of these programs is to deploy cutting-edge AI technologies to solve critical issues such as poverty, hunger, crime, and climate change, under the "AI for good" umbrella. But what makes an AI project good?

Artificial intelligence has been front and center in recent months. The global pandemic has pushed governments and private companies worldwide to propose AI solutions for everything from analyzing cough sounds to deploying disinfecting robots in hospitals. These efforts are part of a wider trend that has been picking up momentum: the deployment of projects by companies, governments, universities, and research institutes aiming to use AI for societal good. The goal of most of these programs is to deploy cutting-edge AI technologies to solve critical issues such as poverty, hunger, crime, and climate change, under the "AI for good" umbrella. But what makes an AI project good?

On February 6, 2018, Elon Musk's SpaceX launched the Falcon Heavy rocket, the largest ever, from NASA's Kennedy Space Center. Its cargo was a Tesla Roadster, which is now orbiting the sun somewhere between Mars and the asteroid belt. Between Elon Musk's numerous companies and passion projects (SpaceX, Tesla, Solar City, the Hyperloop, the Boring Company), and the quickly proceeding advances in VR/AR/MR, genetics/cloning, blockchain, AI, 3D printing, and other fields, someone who was in a coma since 1998 and just woke up yesterday would be forgiven for thinking they had jumped a hundred years into the future instead of a mere 20. But then this person would actually get up and go out into the real world and see that mostly everything else is the same, aside from more traffic on the roads, more people in general, most of whom now carry miniature computers with them wherever they go that are more powerful than any desktop from the 20th century. Born in apartheid-era South Africa, he lived the first 16 years of his life in various towns, including Pretoria, moving back and forth between divorced parents.

Last month, 42 countries signed up to the OECD's common artificial intelligence (AI) principles. Just before that, the European Commission published its own ethics guidelines for trustworthy AI. In fact, to date, there has been a huge amount of work on ethical AI principles, guidelines and standards across different organizations, including IEEE, ISO and the Partnership on AI. On top of these principles, there has been a growing body of work in the fairness, accountability, and transparency machine learning community with a growing number of solutions to tackle bias from a quantitative perspective. Both organizations and governments alike clearly recognize the importance of designing ethics into AI, there's no doubt about that.

Big data and analytics have undoubtedly been the business buzzwords of recent years. As we move through 2018, the digital revolution continues apace, technological capabilities accelerate, and we delve deeper into a world fueled by data -- a world of artificial intelligence and machine learning. But why should we care about these things? According to research from Stanford University's inaugural AI index: Given these statistics, it's no surprise that companies are piling the pounds behind innovation initiatives relating to AI and machine learning. CXOs know that tech-sceptics and conservatives will be left behind and, on top of this, there is added pressure from the start-up space which is filled by fast-moving challengers and innovators.