Artificial intelligence could provide the'ultimate second opinion' as it is just as good as doctors at analysing X-rays, scientists have claimed. Tests using AI software on millions of old scans diagnosed conditions at least as accurately as radiologists 94 per cent of the time. The joint study by Warwick University and King's College London suggested it could prove vital in avoiding human error when checking patients' results. The AI software, which can scan X-rays as soon as they are taken, is able to understand the seriousness of each condition and flag the more urgent ones immediately. The study's authors suggested it could be used to screen X-rays, freeing up time for busy doctors to focus on more critical patients and helping deal with chronic NHS staffing shortages.

According to a recent study, artificial intelligence can assist in identifying early indications of cancer in chest x-rays. Researchers discovered that a cutting-edge AI technology can distinguish between normal and pathological chest x-rays in a clinical context. Chest X-rays are used to diagnose a number of heart and lung diseases. A chest X-ray that is abnormal can be a sign of a number of illnesses, including cancer and long-term lung problems. According to scientists, a machine learning technology that can distinguish between normal and pathological chest X-rays will significantly lessen the radiologists' enormous burden.

The great Pablo Picasso once quipped that'good artists borrow, great artists steal'. But would he still have felt that way if he saw one of his Cubist masterpieces reproduced by art robot Ai-Da, who addressed the House of Lords this week? New Artificial Intelligence tools have made it possible to create and copy intricate artwork with the click of a button, plumbing questions about the ethics of artistry and human creativity. Is creativity under attack from the rise of AI? Is AI-generated art created by increasingly sentient robots such as Ai-Da a sophisticated form of plagiarism or the biggest revolution in art history since Renaissance painters used oil paint and anatomical studies to produce realistic representations of the human figure?

Blake Lemoine, a senior software engineer in Google's Responsible AI organisation, recently made claims that one of the company's products was a sentient being with consciousness and a soul. Field experts have not backed him up, and Google has placed him on paid leave.Lemoine's claims are about the artificial intelligence (AI) chatbot called laMDA. But I am most interested in the general question: If an AI were sentient in some relevant sense, how would we know? What standard should we apply? It is easy to mock Lemoine, but will our own future guesses be much better? The most popular standard is what is known as the "Turing test": If a human converses with an AI programme but cannot tell it is an AI programme, then it has passed the Turing test.

From the coining of the term back in the 1950's to now, AI has taken remarkable leaps forward and only continues to grow in relevance and sophistication But despite these advancements, there's one problem that continues to plague AI technology – the internal bias and prejudice of its human creators. The issue of AI bias cannot be brushed under the carpet, given the potential detrimental effects it can have. A recent survey showed that 36% of respondents reported that their businesses suffered from AI bias in at least one algorithm, resulting in unequal treatment of users based on race, gender, sexual orientation, religion or age. These instances incurred a direct commercial impact: of those respondents, two-thirds reported that as a result they lost revenue (62%), customers (61%), or employees (43%). And 35% incurred legal fees because of lawsuits or legal action.

A lot of freaky stuff is happening in the world of artificial intelligence. Imagine a human brain, multiply its deduction capabilities by billions, and eliminate the human predisposition for self-doubt - that's a derivative definition of artificial intelligence. In the last decade, great strides have been made in machine learning and artificial intelligence, which scientists believe could quicken the pace of breakthroughs in almost all arenas - from medicine, economy, and even climate change. AI programmes are fed data through which they improve their results. The wider and accurate the database, the better results AI will produce.

Artificial Intelligence is already part of our lives, and as the technology matures it will play a key role in future wars. The accuracy and precision of today's weapons are steadily forcing contemporary battlefields to empty of human combatants. As more and more sensors fill the battlespace, sending vast amounts of data back to analysts, humans struggle to make sense of the mountain of information gathered. This is where artificial intelligence (AI) comes in – learning algorithms that thrive off big data; in fact, the more data these systems analyse, the more accurate they can be. In short, AI is the ability for a system to "think" in a limited way, working specifically on problems normally associated with human intelligence, such as pattern and speech recognition, translation and decision-making.

COVID-19 has triggered one of the most disruptive periods on record for air travel and the International Air Transport Association (IATA) has estimated that airlines will lose at least $314 billion due to the outbreak. As the industry looks to adapt to this new Covid-era, not only will airlines need to take a serious look at their overheads, but the standard of safety will need to remain the number one priority. With pilots and their training accounting for one of the biggest costs, airlines will need to re-think their pilot training strategy which is likely to include a need to outsource and decentralise to maximize efficiency. This resultant strain highlights the need for regulators to make changes to the training process. For example, there will need to be more reliance on e-learning in the initial cadet training and the acceptance of integrated technology in simulator training will also be important.

In industry as well as education as well as academics we see a growing need for knowledge on how to apply machine learning in software applications. With the educational programme ICT & AI at Fontys UAS we had to find an answer to the question: "How should we educate software engineers to become AI engineers?" This paper describes our educational programme, the open source tools we use, and the literature it is based on. After three years of experience, we present our lessons learned for both educational institutions and software engineers in practice.

There has never been a more significant time to work in data science and AI. There is recognition of the importance of these technologies to our economic and social future: the so-called fourth industrial revolution. The technical challenge of keeping our data secure and private has grown in its urgency and importance. At the same time, voices from academia, industry, and government are coming together to debate how these technologies should be governed and managed. The Alan Turing Institute, as the UK's national institute for data science and artificial intelligence, plays an important part in driving forward advances in these technologies in order to change the world for the better.