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The idea of an artificial mind that can think by itself has always loomed large in the human imagination – the ancient Greeks told myths of mechanical men. As an academic discipline, the field of Artificial Intelligence (AI) has been studied since the 1950s, after computer scientist Alan Turing first asked, “can machines do what we, as thinking entities, do?”
But in 2018, AI is firmly out of the realms of science fiction or academic theory. Last week UK prime minister Theresa May stood up in her keynote address to the World Economic Forum and announced her ambition to establish the UK as a “world leader” in AI, alongside plans for its ethical oversight.
These days, voice assistants like Google Now and Microsoft’s Cortana are in every smart device and computer, and smart speakers like the Amazon Echo and Google Home are selling in their tens of millions.
Voice-based virtual assistants might be the first thing that comes to mind when we think of AI today, but the term actually applies to a broad set of technologies programmed to mimic the cognitive function of human minds in many different ways.
Machine learning is an enabler for AI that gives computers the ability to learn and solve problems by themselves, expanding their knowledge as they get more data input. Systems are ‘trained’ on an initial amount of data, and then the algorithm is left to improve itself over time.
This technology is now everywhere – think natural language processing seen in the likes of Siri and Alexa, to facial recognition used in biometric security at airports, smarter Google searches and traffic prediction on Google Maps, recommendations on Netflix and Spotify, and arrival time and location estimation in Uber. Google even has AI built into its latest camera phone.
As well as front-of-house service delivery for most of the major tech companies, AI is also being used behind the scenes across most industries as a cost-effective and reliable way to do an enormous number of data-related tasks – everything from detecting fraud and calculating risk in insurance, to monitoring customer satisfaction and targeting people with social media or ad campaigns.
Technology analyst Forrester predicts up to 80% of firms will rely on ‘insights-as-a-service‘ in at least some capacity in 2018, using machine learning to process, trend and analyse data.
Some of these robots are even being put to task solving the world’s most difficult social problems, such as sustainably managing resources, reducing traffic congestion, diagnosing a medical condition before a doctor can, and preventing the spread of diseases like HIV.
In the charity sector, one area where AI might might soon be replacing humans is where advice is offered online – the equivalent of retail sector chatbots like Amazon’s, which is already answering customer questions online in place of a human customer service agent.
While most chatbots are still in their infancy and not able to accurately imitate human-to-human conversation, the big tech companies such as Google, Microsoft, Amazon and Facebook have all been putting heavy bets on chatbot services, and the technology is likely to become dramatically more useful and intelligent over the next few years.
As this happens, AI is likely to become a common way of interacting with organisations. Technology analyst Gartner projects that more than 85% of customer interactions around the world will be managed without a human by 2020.
“Very few people are going to turn around and say they’d much rather have this charity service provided by a chatbot or robot. But actually, in the longer term, the more we become used to taking advice from AI in one form or another, the less weird it is going to seem in other contexts.”
In cases where there is a large amount of information buried in the pages of a website, charities could use text-based AI conversations to present that information in a way that is easier to navigate and interact with and saves time for human helpdesk-operators.
HAL from 2001: A Space Odyssey, The Terminator, I, Robot. It’s a well-known science fiction trope: humans create AI beings – they rebel against their creators and try to annihilate us. Professor Stephen Hawking has even warned us that this could be our ultimate fate, should we fail to keep intelligent machines in check.
But the ethical considerations of AI today fall a lot closer to home. In the near term, it will mean ensuring that AI tools are used fairly and appropriately for everybody, and the responsibility falls squarely in the hands of the humans that use it.
In 2016, Microsoft had to withdraw its AI experiment, a Twitter-based chatbot called Tay, after it began to spew racist and inflammatory Tweets, parroting the sentiments of Twitter users. It may have been funny, but this experiment raised serious questions. It showed us that putting any technology out into the world and expecting it to act morally of its own accord is not going to work, as like with any tools they are only as good as the people that create and use them.
The sophistication of AI is encouraging the development of high-stakes applications such as self-driving cars, automated surgical assistants and stock market trading. Because pretty much any task that involves processing large amounts of data will soon fall to AI, it is inevitable that this data-driven decision making will have some major ethical implications.
One of the big things charities need to be aware of, says Davies, is algorithmic bias.
“Algorithms themselves don’t have entrenched social biases, but if they are not designed with those things in mind and you let them go to work on data sets that contains historical or statistical bias, then they start to not only demonstrate the same bias but demonstrate it even more starkly.”
It seems like one step away from the dystopia portrayed in the film Minority Report, where police use technology to convict people for crimes before they happen – but in the US, this has already had negative consequences on real peoples’ lives.
An AI system (COMPAS) has been used in risk profiling, to forecast which prisoners are likely to reoffend if released from jail, informing decisions about bail and sentencing. These systems have been found to inaccurately identify black defendants as future criminals more often than whites.
Researchers from the Alan Turing Institute are working on building better AI systems that prevent unfair discrimination by modelling how these sorts of incidents occur.
Resources like this one from the BBC News Labs provide a good starting point for charities to gain a deeper understanding the implications of AI, so they can start to engage in meaningful discussions and stay one step ahead.
Read the full article at Charity Digital News