AI for good – how data is helping to change the world

Artificial intelligence has been with us since the 1950s, but many people’s understanding of it still comes through sci-fi movies or shock newspaper headlines. Many worry that this technology is taking away our ability to think and act for ourselves, invading our privacy and taking our jobs. A recent poll by YouGov even found that 41 percent of the British public saw AI as a threat equivalent to nuclear weapons!

The reality is generally much more low key. Rather than creating new dystopias, AI has been most successful when applied to small, specific tasks, which are either too difficult or too time consuming for humans to carry out. As the potential of AI becomes more clear, ethical, or ‘Responsible AI’ has begun to be embraced by members of the tech community involved in solving some of humanity’s more intractable problems, potentially changing the world for good.

Agriculture

We’ve heard about the future of agriculture before thanks to the great GM revolution which promised to feed the planet with crops that were free from blight and disease. But it didn’t take long for GM foods to become as reviled as Victor Frankenstein’s final creation. Now AI is attempting to help farmers successfully produce more food. Sainsbury’s supermarket is testing sensors that will be able to provide data instantly to let farmers know the areas of their farm which most need water – perfect in drought prone countries or inaccessible locations. Meanwhile large scale farming is becoming more efficient thanks to AI powered drones. These drones are able to scan extremely large areas of farmland producing a large number of images, whilst also being able to use AI technology such as image recognition to be able to very quickly and accurately detect areas of farmland which are affected by disease in a way that even the most dedicated farmers could ever dream of.

Healthcare

AI’s role in assisting and sometimes replacing doctors is one of the more sensitive areas. In 2017 the UK’s data protection watchdog ruled that the NHS had illegally handed over the data of 1.6 million British patients to Google. The case showed that safeguards are needed whenever personal data is being used. However, when accessed responsibly, there is no denying that the results can be impressive. A two year partnership between Google’s DeepMind and London’s Moorfield hospital used data from thousands of retinal scans to train AI algorithms to detect signs of eye disease. It worked more quickly and efficiently than any human, cutting down the work done by a highly trained and expensive specialist from hours to just seconds. The next step is to use the same AI to analyse radiotherapy scans for cancer.

Endangered species

The appearance of AI driven drones in our skies bring with them fears of inescapable state surveillance. But studies by scientists tracking populations of endangered animals have found a new use for the technology – detecting and tracking species in the most remote locations. Using satellite data together with thermal and infrared imaging, drones are able to spot animals with between 43% and 96% more accuracy than human-made observation. At the moment, the limited range of drones means that success in tracking wide ranging species like polar bears is proving harder to achieve.

With the world now facing unprecedented challenges caused by climate change, epidemics and an ageing population, the importance of AI’s role in tackling these problems has never been greater. The battle to convince the public that it is in their best interest, however, is only just beginning.

Why AI is a lot like teenage sex – and how you can get better at it

In 2013 Dan Ariely, professor of behavioural economics at Duke University, got the analytics world all aquiver when he stated: “Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.” His risqué comments appeared in the midst of a data revolution, the experience of which was less than satisfactory for many companies.

Six years on and we’re doing it better. However, AI is in danger of being in the same position as Big Data was six years ago. Some data strategists would have you believe that AI and its bedfellow machine learning are better than sex. But as with anything in the data revolution, don’t expect to achieve total fulfilment overnight.

Cost vs kudos

A report from the McKinsey Global Institute predicts that early adopters of this technology could grow the value of their business by 120%. It adds that those who fail to jump on board the AI gravy train could lose a fifth of their cash flow. No surprise that companies are throwing money at the problem – but not necessarily always for the right reasons.

Kudos is not enough of a reward for a business to pump considerable sums of money into an AI project. A survey by the US analytics company Figure Eight showed that the majority of companies were spending at the very least $50,000, rising to over $5 million for those serious about making it a central part of their business.

AI has now been around for two decades. Advances in tech plus heavy investment from the likes of Google mean that the cost of leveraging AI tools will continue to fall, levelling the playing field and allowing smaller businesses to utilise AI. If you’ve made it your business to amass a wealth of clean, properly managed data you are already well positioned to launch an effective AI project.

Let’s not get ahead of ourselves

With any data project, there are things you need to think about before you get started. If you’re looking to get started with AI specifically, first consider whether the problem you would like to address is best served by the technology. Don’t expect AI to act as a sort of panacea; you need to be deploying it in the right way and for the right reasons. If you’re unsure, talk to an expert first (yes, we can help with that) to assess what sort of data analysis would be best for your particular problem.

Maybe there is an area of your business you are certain would benefit from an AI solution – if only you could convince the CFO to invest. If they’re keeping a tight hold of the purse strings ask yourself: does this align with the greater corporate strategy? If no, you’d probably be better focusing your efforts somewhere that does.

Finally, when you have identified the right AI project and hired yourself a crack analytics specialist (hello), don’t assume that the thing will just run itself. AI is smart but it still needs help. That means putting together the right team – and not just a couple of people borrowed from the IT department. Successful AI needs buy-in from people who understand the business need and who are working with the numbers on a daily basis.

Get it right and you’ll transform your AI experience from a meaningless one night stand to a satisfying relationship that grows into something really special.