Robert Epstein was looking for love. The year being 2006, he was looking online. As he recounted in the journal Scientific American Mind, he began a promising email exchange with a pretty brunette in Russia. Epstein was disappointed - he wanted more than a penfriend, let's be frank - but she was warm and friendly. Soon she confessed she was developing a crush on him.

Are recent strides in artificial intelligence more about computers becoming better at matching patterns than about real human-like understanding of tasks? Plus, why a mysterious Russian satellite displaying "very abnormal behaviour" has raised alarm in the US. And is the richness of spoken English at risk from speaking to AI assistants?

Ever since the coining of the term big data, people have been hailing it as an asset of potentially immeasurable value to businesses and to medical science. But to master it, we need to master the patterns that data contains. A new firm claims to have done just that, with software that doesn't just recognise patterns in data, it discovers patterns we weren't even looking for. Tech entrepreneur Mark Anderson has pioneered pattern discovery technology, which has many uses, such as working out which gene combinations are causing a disease. He says it would it would take today's supercomputers centuries to do calculations at the same level as his pattern computer.

What humans do to earn a living has always evolved to suit the needs of society, and the capabilities of the technology at our disposal. But thanks to the rapid development of artificial intelligence and automation we are on the cusp of a whole new Industrial Revolution. Manual and low skilled labour are already feeling the impact of automation – Amazon is experimenting with delivery drones, the fast food industry may soon be staffed with burger-flipping bots, and driverless vehicles are already taking to the road. But those with high skill jobs should not rest on their laurels – legal services, medical care, and academia are all set to change as computers take over all the data crunching. People are either going to have to find new things to do, or risk being left behind as the world of work changes.

Do we really know the potential and the pitfalls of artificial intelligence? Maybe not, say the experts and innovators at the TED conference in Vancouver. Jane Wakefield hears from the creator of the infamous "fake Obama" videos, Dr Supasorn Suwajanakorn. And AI expert and pioneer Max Tegmark of MIT explains why we can't make any assumptions about the future, and must decide now how to navigate the problems of AI such as whether to ban autonomous weapons. Plus we hear from Pierre Barreau about his AI music, and why computers sometimes need reminding that human musicians need to take a breath.

Women in politics are sometimes accused of consciously exploiting their femininity to get ahead in a male-dominated world. Frances Perkins did that, but in an unusual way: she tried to remind men of their mothers. She dressed in a plain, three-cornered hat, and she refined the way she acted, based on careful observation of what seemed to be most effective in persuading men to accept her ideas. Perhaps it's no coincidence that those ideas could reasonably be described as maternal or parental. Any parent wants to shield their children from serious harm, and Perkins believed governments should do the same for their citizens. She became President Franklin D Roosevelt's Secretary of Labour in 1933.

For investors in Boo.com, WebVan and eToys, the bursting of the dotcom bubble came as a bit of a shock. Companies like this raised vast sums on the promise that the worldwide web would change everything. Then, in the spring of 2000, stock markets collapsed. Some economists had long been sceptical about the promise of computers. In 1987, we didn't have the web, but spreadsheets and databases were appearing in every workplace - and having, it seemed, no impact whatsoever.

Machines are about to get a lot smarter and machine learning will transform our lives. So says a report by the Royal Society in the UK, a fellowship of many of the world's most eminent scientists. Machine learning is a form of artificial intelligence that's already being used to tag people in photos, to interpret voice commands and to help internet retailers to make recommendations. Manuela Saragosa hears about a new technology that is set to revolutionise computing, developed by a UK company called Graphcore. Manuela talks to Graphcore's chief executive Nigel Toon, who is taking on the AI giants.

Murderers in early 19th-Century London sometimes tried to kill themselves before they were hanged. Failing that, they asked friends to give their legs a good, hard pull as they dangled from the gallows to ensure their death. Their freshly hanged bodies, they knew, would be handed to scientists for anatomical studies. They didn't want to survive the hanging and regain consciousness while being dissected. If George Foster, executed in 1803, had woken up on the lab table, it would have been in particularly undignified circumstances.

Emitting a gentle whirring noise, it travels across the warehouse floor while two arms raise or lower themselves on scissor lifts, ready for the next task. Each arm has a camera on its knuckle. The left one eases a cardboard box forward on the shelf, the right reaches in and extracts a bottle. Hitachi showcased it in 2015 and hopes to be selling it by 2020. It is broadcast on the BBC World Service.