Faced with an attempt by a new chatbot to imitate (模仿) his own songs, the musician Nick Cave delivered a strong response: it was “an absolutely horrible attempt”. He understood that AI was in its babyhood, but could only conclude that the true horror might be that “it will forever be in its babyhood”. While a robot might one day be able to create a song, he wrote, it would never grow beyond “a kind of burlesque (滑稽的模仿)”, because robots-being composed of data-are unable to suffer, while songs arise out of suffering.

Fans of Cave and his band will agree that his music is inimitable, but that doesn’t mean they would necessarily be able to tell the difference. A few days before Cave’s remarks, experts were asked to distinguish between four genuine artworks and their AI imitations. Their conclusions were wrong five times out of 12, and they were only unitedly right in one of the four picture comparisons.

These are party games, but they point to an unfolding challenge that must be managed as a matter of urgency because, like it or not, AI art is upon us. The arrival of the human-impersonating ChatGPT might have increased general awareness, but artists across a wide range of disciplines are already exploring its potential, with the dancer Wayne McGregor and London’s Young Vic Theatre among those who have created AI-based works.

A strongly-worded report from Communications and Digital Committee (CDC) issued a wake-up call to the government, urging it to raise its game in educating future generations of tech-savvy professionals, and tackling key regulatory challenges. These included reviewing reforms to intellectual property law, strengthening the rights of performers and artists, and taking action to support the creative sector in adapting to the disturbances caused by swift and stormy technological change.

While developing AI is important, it should not be pursued at all costs, the CDC stressed. It deplored the failure of the Department for Digital, Culture, and Media to offer a defence against proposed changes to intellectual property law that would give copyright exemption (版权豁免) to any work, anywhere in the world, involving AI text and data mining.

The challenges of AI are both philosophical, as Cave suggested, and practical. They will unfold over the short and long term. State-of-the-art creative industries have a key role to play in shaping and exploring the philosophical ones, but they must have the practical help they require to survive and be successful. They need it now.

The Amazon Echo, a voice-driven computer that sits on a table top and answers to the name Alexa, can call up music tracks and radio stations, tell jokes, answer simple questions and control smart appliances. Even before Christmas it was already resident in about 4% of American households. Voice assistants are being widely used in smart phones, too: Apple’s Siri handles over 2 billion commands a week, and 20% of Google searches on Android-powered handsets in America are input by voice. Dictating e-mails and text messages now works reliably enough to be useful. Why type when you can talk?

Simple though it may seem, voice has the power to transform computing, by providing a natural means of interaction. Windows, icons and menus, and then touch screens, were welcomed as much easier ways to deal with computers than entering complex keyboard commands. But being able to talk to computers abolishes the need for a “user interface(界面)” at all. Just as mobile phones were more than existing phones without wires, and cars were more than carriages without horses, so computers without screens and keyboards have the potential to be more useful, more powerful than people can imagine today.

Voice will not wholly replace other forms of input and output. Sometimes it will remain more convenient to converse with a machine by typing rather than talking (Amazon is said to be working on an Echo device with a built-in screen). But voice is sure to account for a growing share of people’s interactions with the technology around them, from washing machines that tell you how much of the cycle they have left to virtual assistants in corporate call centres. However, to reach its full potential, the technology requires further breakthroughs and a resolution of the tricky questions it raises around the trade-off between convenience and privacy.

Computer-dictation systems have been around for years. But they were unreliable and required lengthy training to learn a specific user’s voice. Computer’s new ability to recognise almost anyone’s speech dependably without training is the latest manifestation (证明) of the power of “deep learning”, an artificial intelligence technique in which a software system is trained to use millions of examples, usually selected from the Internet. Thanks to deep learning, machines now nearly equal humans in transcription accuracy, computerized translation systems are improving rapidly and text-to-speech systems are becoming less robotic and more natural-sounding. Computers are, in short, getting much better at handling natural language in all its forms.

Although deep learning means that machines can recognize speech more reliably and talk in a more natural manner, they still don’t understand the meaning of language. That is the most difficult aspect of the problem and, if voice-driven computing is truly to flourish, one that must be overcome. Computers must be able to understand context in order to maintain a coherent conversation about something, rather than just responding to simple, one-off (一次性的) voice commands, as they mostly do today (“Hey, Siri, set a timer for ten minutes”). Researchers in universities and at companies are working on this problem, building “bots” that can hold more detailed conversations about more complex tasks, from searching information to making travel arrangements.

Many voice-driven devices are always listening, waiting to be activated(激活). Some people are already concerned about the implications of internet-connected microphones listening in every room and from every smart phone. Not all audio is sent to the cloud - devices wait for a trigger phrase (“Alexa”, “OK, Google”, “Hey, Cortana”, or “Hey, Siri”) before they start passing the user’s voice to the servers that actually handle the requests - but when it comes to storing audio, it is unclear who keeps what and when.

Children may not be putting coins into piggy banks for much longer. With the move towards a cashless society, pocket money is moving digital.

To reflect this trend, a number of mobile budgeting apps for children has sprung up worldwide. 【小题1】Parents can add money to children’s accounts, set limits and monitor transactions, while children can choose to save their money or spend it using a prepaid card. The companies behind the apps argue that in an increasingly cashless society, they can be a valuable way of teaching young children about money.

【小题2】These apps aim to overcome this, claiming to teach children financial concepts, such as budgeting, interest rates and income.

For instance, the Swedish app Gimi has virtual savings jars where children can deposit money; parents can pay children interest as they save. Philip Haglund, CEO of Gimi believes the app has certain advantages, like teaching responsible real-life spending habits. 【小题3】

One concern is that introducing digital money apps to young children could help to encourage irresponsible spending habits. “What if children don’t have a good foundation in financial capability? 【小题4】 They might develop bad money habits.” says an expert.

However, Haglund says it is important for kids to learn and make mistakes, “We want to help kids and teenagers gain financial skills for   life. 【小题5】 If you’re going to make a mistake of £10 at eight, it’s better than making a mistake of £1,000 when you’re 28,” he says.