This article was featured in One Story to Read Today, a newsletter in which our editors recommend a single must-read from The Atlantic, Monday through Friday. Diana Henriques was first stricken in late 1996. A business reporter for The New York Times, she was in the midst of a punishing effort to bring a reporting project to fruition. Then one morning she awoke to find herself incapable of pinching her contact lens between her thumb and forefinger. Henriques's hands were soon cursed with numbness, frailty, and a gnawing ache she found similar to menstrual cramps.

Generative AI is the is a technological marvel destined to change the way we work, but what does it do and what are its use cases for CTOs? Where better to start than with a definition straight from the horse's mouth? ChatGPT-4, from Microsoft-backed OpenAI, describes generative AI as "…a type of artificial intelligence that involves training algorithms to generate new content based on a given set of parameters or data. This technology has been used in a variety of fields, from image and video generation to natural language processing and music creation". Apart from being endearingly modest, generative AI also has the potential to transform economies.

What are the use cases for embedding generative AI in your enterprise? How can it help ease burden of repetitive admin? Research firm Gartner reports that venture capital companies have invested over $1.7bn in generative AI solutions over the last three years. With AI-enhanced chatbots taking media by storm, this is only going to sharply increase. As it gains popularity among millions of users worldwide, there is no denying the power of generative AI for enterprise.

Worldwide spending on artificial intelligence will hit half a billion dollars this year, according to IDC. Five artificial intelligence experts give Information Age their predictions as to how adoption of AI will accelerate in 2023. Expect to see AI playing a bigger role in frontline healthcars in 2023, says Adonis Celestine, director of automation at Applause. This will be particularly true in the UK and Europe where there is a shortage of doctors and general practitioners. Chatbots were used to diagnose symptoms during Covid, says Celestine, and in the future we'll see more instances of AI filtering patients through to the correct medical professionals, once the initial diagnosis has been identified.

Back in 2019, who could possibly have predicted just how tumultuous the early 2020s would be for digital transformation? When the pandemic hit, an urgent acceleration of digital transformation initiatives followed. Companies of all sizes, across a broad range of industries, were forced to invest in advanced, collaborative technologies in an effort to adapt to the new normal. Covid was certainly a shock to the system for those organisations that had not previously invested heavily in digital. However, it helped many to establish a solid foundation to begin building towards a brighter future, driven by technology.

While the field of artificial intelligence (AI) has made steady progress over the past few decades, only recently did progress rapidly accelerate, allowing scientific achievements to be translated into real-world use cases. In the last few years, AI has been developing at a consistently rapid pace and has achieved an inflection point. But before we can examine just how AI is revolutionizing our way of life, we must first look at how it got to where it is today. AI had already entered the minds of prominent scientists by the 1950s, as evidenced by Alan Turing's 1950 paper, "Computing Machinery and Intelligence." Between 1957 and 1974, computing capacity advanced to the point where people were able to improve machine learning algorithms and put AI to use.

Robot revolution to transform human workplaces Feature 18 April 2017 Over the last few months, the idea that a robotic revolution is just around the corner has become commonplace Nick Ismail Robots and artificial intelligence is set to intrude into many of the spheres of our lives – driverless cars are about be tested on Manchester roads, self-driving delivery robots are being trialled in London while a New York firm has developed a robot which can lay six times as many bricks in a day as its human counterpart A recent report from The International Bar Association, a global organisation for lawyers, said Governments could be forced to legislate for quotas of human workers, traditional working practices would be transformed over the coming years and that legal frameworks regulating employment and safety were becoming rapidly outdated. A third of graduate level jobs around the world may eventually be replaced by machines or software, the report said. See also: Robots: better saved for Sci-Fi believe UK consumers An estimate by PWC earlier this year said that 10 million UK workers were at high risk of being replaced by robots over the next 15 years. In some sectors half the jobs could go, it warned. The speed with which change is occurring and the broadness of impact being brought about by AI and robotics is incredible.

Artificial intelligence (AI) is everywhere, powering applications such as smart assistants, spam filters and search engines. The technology offers multiple advantages to businesses – such as the ability to provide a more personalised experience for customers. AI can also boost business efficiency and improve security by helping to predict and mitigate cyber-attacks. But while AI offers benefits, the technology poses significant risks to privacy, including the potential to de-anonymise data. Recent research revealed AI-based deep learning models are able to determine the race of patients based on radiologic images such as chest x-rays or mammograms – and with "significantly better" accuracy than human experts.

The more data you can feed a machine learning algorithm, the better it can spot patterns, make decisions, predict behaviours, personalise content, diagnose medical conditions, power smart everything, detect cyber threats and fraud; indeed, AI and data make for a happy partnership: "The algorithm without data is blind. Data without algorithms is dumb." Not everyone wants to share, at least, not under the current rules of digital engagement. Some individuals disengage entirely, becoming digital hermits. Others proceed with caution, using privacy-enhancing technologies (PETs) to plug the digital leak: a kind karate chop, digital self defense -- they don't trust website privacy notices, they verify them with tools like DuckDuckGo's Privacy Grade extension and soon, machine-readable privacy notices.

Thorsten Stremlau, co-chair of TCG's Marketing Work Group, discusses how security of data systems for AI can be kept strong Attacks on artificial intelligence (AI) differ from the typical cyber security threats seen on a daily basis, but this does not mean they are at all infrequent. Hacking continues to become increasingly sophisticated, and has evolved from simply hiding bugs in code. Unless properly secured, hackers are able to tamper with these systems and alter its behaviour in order to'weaponise' AI. This provides a perfect way for hackers to obtain sensitive data or corrupt systems designed to authenticate and validate users, with no easy fix should an attack be successful. Where security is considered, it is not only important to look at the aspects of a rogue AI, but also how the data sets of a system can be secured.