As a result, both the industry approach and regulatory framework are failing in the fight against money laundering. Despite the vast resources deployed by financial institutions to combat money laundering, the current approach is not delivering sustainable results. Money-laundering activity is estimated to be between 2 and 5 percent of global gross domestic product (GDP). In the United Kingdom alone, the social and economic cost is estimated to be least £24 billion a year. According to a report by Europol, around 10 percent of the Suspicious Activity Reports (SARs) filed by financial-services institutions lead to further investigation by competent authorities.

Fingerprint scanners, voice recognition, targeted ads, home voice assistants. These technologies are all part of everyday modern life and are revolutionising the way retailers sell their products to consumers across the world. But have we actually taken the time to stop and consider what customers think of our ever increasing arsenal of tech tricks to entice and persuade? Every year we survey consumers in the UK, France and Germany to gain an understanding into what technologies they think are'creepy' or'cool'. The results from this year's survey are just in – giving us a top 5 'creepy' and top 5 'cool' list of tech that shoppers love or loathe.

Last year, Elon Musk made headlines by describing AI as a "fundamental risk to the existence of civilization." At the time, Facebook CEO Mark Zuckerburg described such warnings as "pretty irresponsible." More recently, Google CEO Eric Schmidt suggested that the answer to fears about AI was to police it: "The example I would offer is, would you not invent the telephone because of the possible misuse of the telephone by evil people? No, you would build the telephone and you would try to find a way to police the misuse of the telephone," he said at the VivaTech conference in Paris last month. Others talk about the singularity – the point at which an AI suddenly becomes sentient – and use that possibility to stoke fears already fueled by dozens of sci-fi movies.

Thousands of the top names in tech have come together to take a stand against the development of killer robots. Tesla and SpaceX CEO Elon Musk, who has long been outspoken about the dangers of AI, joined the founders of Google DeepMind, the XPrize Foundation, and over 2,500 individuals and companies in signing a pledge this week condemning lethal autonomous weapons. The industry experts vowed to'neither participate in nor support' the use of such weapons, arguing that'the decision to take a human life should never be delegated to a machine.' The move comes amid growing fears of AI systems that could target and kill a person without a human at the reins to make the final judgement call. 'There is an urgent opportunity and necessity for citizens, policymakers, and leaders to distinguish between acceptable and unacceptable uses of AI,' industry experts argue in the pledge, which was released on Wednesday at the 2018 International Joint Conference on Artificial Intelligence in Stockholm.

No Man's Sky might finally be fixed. Developers Hello Games have announced a vast number of changes that hope to fix the problems that have dogged the game since it was first released two years ago. Before its launch, No Man's Sky was one of the most lauded games of the decade. Critics were thrilled by the way the game offered an entire universe that would be generated by computers, all of which would be waiting for players to discover. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.

Thousands of the world's pre-eminent technology experts called for a global ban on the development of lethal autonomous weapons, warning they could become instruments of "violence and oppression". More than 2,400 individuals and 150 companies from 90 different countries vowed to play no part in the construction, trade, or use of autonomous weapons in a pledge signed on Wednesday at the 2018 International Joint Conference on Artificial Intelligence in Stockholm, Sweden. Elon Musk, CEO of SpaceX and Tesla, and representatives of Google's DeepMind subsidiary were among supporters of the pledge. "The decision to take a human life should never be delegated to a machine," a statement said. "Lethal autonomous weapons - selecting and engaging targets without human intervention - would be dangerously destabilising for every country and individual."

Today, many companies are entrusting their top business-critical operations and decisions to artificial intelligence. Rather than traditional, rule-based programming, users now have the ability to provide machine data, define outcomes, and let it create its own algorithms and provide recommendations to the business. For instance, an auto insurance company can feed a machine a library of photos of previous totaled cars with data on their make, model and payout. The system can then be "trained" to review future incidents, determine if a car is totaled, and give a recommended payout amount. This streamlines the review process, which is both a positive for the company and customer.

Goldman Sachs' statistical model for the World Cup sounded impressive: The investment bank mined data about the teams and individual players, used artificial intelligence to predict the factors that might affect game scores and simulated 1 million possible evolutions of the tournament. The model was updated as the games unfolded, and it was wrong again and again. It certainly didn't predict the final between France and Croatia. The failure to accurately predict the outcome of soccer games is a good opportunity to laugh at the hubris of elite bankers, who use similar complex models for investment decisions. Tom Pair, founder of the Upper Left Opportunities Fund, a hedge fund, tweeted recently: "Of course, past data don't always predict the future; Goldman Sachs never tells clients to make decisions solely on the basis of its models' findings. And in any case, the model only generated probabilities of winning a game and advancing, and no team was given more than an 18.5 per cent chance of winning the World Cup. The moral of the story is probably that buzz-generating technologies such as big data and AI don't necessarily make statistical forecasting more accurate."

Goldman Sachs' statistical model for the World Cup sounded impressive: The investment bank mined data about the teams and individual players, used artificial intelligence to predict the factors that might affect game scores and simulated 1 million possible evolutions of the tournament. The model was updated as the games unfolded, and it was wrong again and again. It certainly didn't predict the final between France and Croatia. The failure to accurately predict the outcome of soccer games is a good opportunity to laugh at the hubris of elite bankers, who use similar complex models for investment decisions. Tom Pair, founder of the Upper Left Opportunities Fund, a hedge fund, tweeted recently: "Of course, past data don't always predict the future; Goldman Sachs never tells clients to make decisions solely on the basis of its models' findings. And in any case, the model only generated probabilities of winning a game and advancing, and no team was given more than an 18.5 per cent chance of winning the World Cup. The moral of the story is probably that buzz-generating technologies such as big data and AI don't necessarily make statistical forecasting more accurate."

Many workers in industry sectors such as technology, manufacturing and health have been concerned about how artificial intelligence and robotics may directly affect their employment in the near future. While we've heard numerous stories over the years about how AI will streamline job processes, and robots will even be able to make humans redundant in some industries, there appears to be a battle between furthering this technology, and making sure the UK's workforce isn't left out in the cold. A new report from PricewaterhouseCoopers should put both parties at ease as we move into the age of AI. PwC has found that AI is set to create 7.2 million new jobs in the UK across healthcare, science and education sectors by the year 2037. It predicts that 7 million workers would be displaced by advancements in this technology.