From my Northern Irish vantage point, I coordinate and facilitate a collaborative network around AI. Our 30 members range from micro SMEs through to multinational organisations, such as Liberty IT and Allstate. As such, I am privy to an incredible range of AI based applications and solutions that are coming down the line, and I am always surprised at the pace of change in the industry.
With every change, we need to take a few steps back and rethink how to frame the state of the art at that given time – so it’s worth keeping in mind that what is state of the art at any given time may well be seen as mundane in just a few short months.
For example, when the age of the AI personal assistant arrived with Google Assistant, Siri and Cortana, my framing focussed on trying to communicate that AI was no longer an abstract concept, but part of our everyday lives; albeit in a relatively limited manner. But it was only with the arrival of Amazon Alexa that many people were spending real money to own what is ultimately an AI product.
Today? Well… today things feel different again. Let me give you a few examples of applications of AI that we will all find hugely beneficial.
A deep look into artificial intelligence, machine learning and data science
Every day productivity gains powered by AI
From a personal perspective, I use an AI-powered application to track my expenses. I simply take a photo of the receipt with my phone and not only does the app upload and store this, removing any need to worry about the paper receipt, it also uses machine vision to extract all the relevant information about the expenditure. It’s not just handy, it saves time. This kind of effort-saving, advanced technology continues to blow me away: recently, when I took a photo of a poorly hand-written receipt, the app still extracted the amount. Seriously.
Yes, it actually worked.
This is just one example, but it exemplifies one of the most powerful applications of AI in recognising and converting images into a digital format in a really simple and easy to use way. We ran an AI Camp for students in Birmingham last month and the winner applied this use case to converting old paper-based mathematical books into a digital format; this sort of innovation can help us to capture all manner of data that may otherwise have been lost to the ages.
Similarly, I like hand writing notes but there are two main problems. First, I often can’t read my own handwriting. Yes. It’s that bad. Secondly, that makes it even less likely that I will ever go back and type this information up, which makes the whole thing feel like an exercise in futility. Now when taking notes, I use an app on my iPad with my Apple pencil. Even though I write in a semi-legible scrawl, Nebo figures out what I am trying to write and converts it to formatted text. And it’s VERY good. When I first got it I showed my kids, who regularly tease me about my atrocious handwriting. Neither of them can read it. I tapped the “convert this” button and immediately my awful penmanship was converted to nice crisp, clean, error free text. Again, we can see multiple applications of this technology in the workplace through to the classroom.
These are small applications. But you can probably already see how they can have a big impact for many people around the world. From a technology perspective, they have overcome challenges that just a few years ago would have seemed pretty impossible. Today, they are accepted, unquestioned and widely-used elements of applications that are in daily use on phones and tablets. But however incredible AI is as a productivity tool, there are many more opportunities for it to improve how we live.
How to implement artificial intelligence into your business
The big picture: Applying AI within healthcare
One area I am particularly interested in is healthcare, and this is an area where I have always felt that AI can make the most difference.
In 2017 – the early days of AI in healthcare – a company called Arterys managed to get FDA approval for its cardiology product. This shocked me because not only was it an FDA approval of a cloud-based solution, but a cloud-based solution that uses deep learning. Anyone familiar with the FDA will agree that this is an incredible leap forward and something I wouldn’t have anticipated for at least another few years.
Today, there has been a huge raft of FDA approvals and innovation taking place, and AI is sitting at the heart of it. Here are some cutting edge, FDA-approved, developments that have really caught my eye:
- Prevention and patient risk assessments: The world now has a patient surveillance and predictive algorithm platform, developed by Excel Medical, which carries out patient risk assessment and stratification in hospitals.
- Detection and diagnostics: IDx have developed a fully automated system for automatic detection of diabetic retinopathy. This is not a clinical decision support tool, it is a fully autonomous AI driven diagnostic that is in use in clinics now. Another solution, OsteoDetect uses AI to analyse 2d X-rays to spot wrist fractures, helping to improve detection and diagnosis.
- Triage and treatment: Viz has developed an AI solution which helps with identification and triage strokes. DreaMed is another solution which is being used to provide personalised insulin recommendations for diabetics.
All are genuine examples of AI based products that have the potential to improve healthcare in many ways and even save patients’ lives.
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The future is AI
In the last twelve months, we’ve seen the UK launch an industry strategy that firmly sets out AI as a key area for development. It is hoped it will generate an estimated £232 billion for the UK economy by 2030. Of course, the UK isn’t alone. At last count, 23 countries had released an AI strategy, action plan or sector deal.
I have met with people that work in healthcare, the pharma industry, manufacturing, banking, insurance, retail, security/ cyber security and government and they are all interested in the potential of AI. Many are making first steps to figure out how they can improve what they do with AI and machine learning, while others have moved beyond first steps to a point where AI/ML is an integral part of their day to day business. In every case, I have lots of reasons to be excited about what is coming forward in the very near future.
