It's important to remember that these images aren't created from scratch. They're built from "training sets" of images that human researchers feed into the AI to help it learn and recognise patterns. If you're not familiar with how such AI apps work, this old article from 2015 does a pretty good job of explaining this. I suspect that while the process has become more sophisticated over the years, the basic principle of recursively feeding images back into neural nets until the AI "gets it" hasn't changed. Therefore, human biases do exist in the patterns chosen and images generated, which turns these images into AI interpretations of human biases.

When is too much knowledge a bad thing? According to the International Association of Scientific, Technical and Medical Publishers there are about 10,000 publishers of scientific journals worldwide producing some 33,000 active peer-reviewed journals in English, plus a further 9400 non-English journals. Together they publish around 3 million research articles each year. Professor Michael Witbrock of the School of Computer Science at the University of Auckland says, "Every few seconds another paper is published in molecular biology. Humans can't keep up with this. We are missing out on potential medical advances because we can't read our own literature."

Artificial Intelligence is using advances to help medical professionals detect and treat cancers; emergency responders predict and prepare for impending natural disasters; police identify criminals and safely disarm bombs; organisations improve products, services and processes and school children receive tailored help from virtual teachers suited to their learning style. Through the use of robots and software agents, the machine may even perform these tasks alone or as a team member collaborating with humans. If we are going to build machines that play roles that simulate human reasoning, behaviour and activities, as a society we should ensure that those machines benefit all members of society, regardless of their age, gender, religion or status in society, rather than replicate human biases, perpetuate disparities or widen the gap between the haves and have nots. If AI is a simulation of human intelligence, who does it simulate and does it have a gender? Whether you view gender as socially constructed by one's environment and culture, a biologically determined factor as in the essentialist perspective, or adhere to the theory of individual differences, gender plays a role in who we are.

AI-enabled automation has generated its share of controversy. We've all heard the predictions: 40% of jobs will be eliminated by AI, echoed venture capitalist Kai-Fu Lee on 60 Minutes recently. And experts say this is even worse news for women. According to the Institute for Women's Policy Research, women "… are 58% of the workers at the highest risk." Women tend to hold the types of job ripe for automation: customer service and administrative positions that involve routine, repeatable tasks, according to the research.

He predicts computers will have human-level intelligence by 2029, and that by 2045 computers will surpass human intelligence. He and I agree that artificial intelligence is a positive force to augment human capacity. Like eye glasses and hearing aids, we will come to see AI as an extension of the human experience. AI may be the biggest disruptor society has ever experienced. But it's not just a disruptor; AI is also an accelerant with the potential to enrich human learning, discovery, and productivity personally and professionally.

The escalation of interest in AI in financial services during the past 12 months is justified, given that AI represents the next wave of computing and will unleash major change in all industries, bringing benefits in all aspects of our lives. For financial institutions, specifically, AI represents an opportunity to radically improve efficiency, risk management and fraud detection as well as customer service. These are among the key findings of a new research paper, entitled: The next big wave: How financial institutions can stay ahead of the AI revolution, featuring interview with top banking executives and produced by Finextra in association with Intel. As Roberto Ferrari, managing director, CheBanca!, puts it in the paper: "AI will become the most defining technology of the new banking and financial services of the future." There is no question, banks need to move, the research finds, but to stay ahead of the AI revolution they must navigate a complex array of techniques, possible application areas, cultural challenges and technology decisions, to ensure they lay solid foundations for their AI-driven futures.

You can credit IBM's Watson for creating a platform for artificial intelligence integration into a multitude of business and customer-facing applications. You can thank Facebook for all the buzz about chatbots and the gold rush of developers and venture capital creating an onslaught of bot companies. However, the truth is we are only just starting to realise the potential of artificial intelligence and one of the most promising applications for AI to make a more than welcome impact is in customer experience. It can be debated that for all of the good technology has offered businesses over the last several decades, it has also comprised key elements of the customer experience. Call centres, websites, email, apps, et al, have allowed companies to scale and automate customer engagement while also introducing process efficiencies and cost management systems.

Artificial intelligence is learning to drive. Within the next 20 years it will take over from humans as the main entity behind the wheel. However, AI in the automotive industry is more than the technology merely passing its driving test. This piece explores not only the impact of AI on driving, but how it will fundamentally alter the way OEMs do business and the laws surrounding road use across the world. Manufacturers are sitting on a huge amount of information from cars already on the road, but are unable to harness it for sales purposes with insights buried amongst mountains of data. In thinking about AI in the automotive industry, there is one trend that can't be ignored: autonomous vehicles.

Curiously, consumers seem more prepared to engage with AI in private than in public. Many customers feel more relaxed talking to their virtual home assistant such as Alexa but would feel reluctant to converse with a machine in public. A study by Creative Strategies found that whilst 39% of voice assistant users were happy to use the technology in their homes, under 2% were prepared to do so at work and only 6% would use them in public. One theory states that the way to get customers to accept AI is to make them more human. Purna Virji, a training manager at Bing ads, says that the key is to make customer forget they're not dealing with a human being.

You can credit IBM's Watson for creating a platform for artificial intelligence integration into a multitude of business and customer-facing applications. You can thank Facebook for all the buzz about chatbots and the gold rush of developers and venture capital creating an onslaught of bot companies. However, the truth is we are only just starting to realise the potential of artificial intelligence and one of the most promising applications for AI to make a more than welcome impact is in customer experience. It can be debated that for all of the good technology has offered businesses over the last several decades, it has also comprised key elements of the customer experience. Call centres, websites, email, apps, et al, have allowed companies to scale and automate customer engagement while also introducing process efficiencies and cost management systems.